├── .gitattributes
├── .gitignore
├── DeepAlignmentNetwork.sln
├── DeepAlignmentNetwork
├── AffineTransformLayer.py
├── CameraDemo.py
├── DANtesting.py
├── DANtraining.py
├── DeepAlignmentNetwork.pyproj
├── FaceAlignment.py
├── FaceAlignmentTraining.py
├── HoloFaceBackend.py
├── ImageDemo.py
├── ImageServer.py
├── LandmarkImageLayer.py
├── LandmarkInitLayer.py
├── LandmarkTranformLayer.py
├── MenpoEval.py
├── TestSetPreparation.py
├── TrainingSetPreparation.py
├── TransformParamsLayer.py
├── tests.py
└── utils.py
├── LICENSE
├── README.md
└── data
├── boxes300WIndoor.pkl
├── boxes300WOutdoor.pkl
├── boxesAFW.pkl
├── boxesHelenTest.pkl
├── boxesHelenTrain.pkl
├── boxesIBUG.pkl
├── boxesLFPWTest.pkl
├── boxesLFPWTrain.pkl
├── haarcascade_frontalface_alt.xml
└── meanFaceShape.npz
/.gitattributes:
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1 | * text=auto
2 |
3 | *.sln text eol=crlf
4 | *.pyproj text eol=crlf
5 |
6 | *.pkl binary
7 | *.npz binary
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/.gitignore:
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1 | *.pyc
2 | /data/images/
3 |
4 | #Ignore thumbnails created by Windows
5 | Thumbs.db
6 | #Ignore files built by Visual Studio
7 | *.obj
8 | *.exe
9 | *.pdb
10 | *.user
11 | *.aps
12 | *.pch
13 | *.vspscc
14 | *_i.c
15 | *_p.c
16 | *.ncb
17 | *.suo
18 | *.tlb
19 | *.tlh
20 | *.bak
21 | *.cache
22 | *.ilk
23 | *.log
24 | [Bb]in
25 | [Dd]ebug*/
26 | *.lib
27 | *.sbr
28 | obj/
29 | [Rr]elease*/
30 | _ReSharper*/
31 | [Tt]est[Rr]esult*
32 | .vs/
33 | #Nuget packages folder
34 | packages/
35 |
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/DeepAlignmentNetwork.sln:
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1 |
2 | Microsoft Visual Studio Solution File, Format Version 12.00
3 | # Visual Studio 14
4 | VisualStudioVersion = 14.0.25420.1
5 | MinimumVisualStudioVersion = 10.0.40219.1
6 | Project("{888888A0-9F3D-457C-B088-3A5042F75D52}") = "DeepAlignmentNetwork", "DeepAlignmentNetwork\DeepAlignmentNetwork.pyproj", "{AEB3B95A-95F2-4B4E-99E4-DD648CEE5679}"
7 | EndProject
8 | Global
9 | GlobalSection(SolutionConfigurationPlatforms) = preSolution
10 | Debug|Any CPU = Debug|Any CPU
11 | Release|Any CPU = Release|Any CPU
12 | EndGlobalSection
13 | GlobalSection(ProjectConfigurationPlatforms) = postSolution
14 | {AEB3B95A-95F2-4B4E-99E4-DD648CEE5679}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
15 | {AEB3B95A-95F2-4B4E-99E4-DD648CEE5679}.Release|Any CPU.ActiveCfg = Release|Any CPU
16 | EndGlobalSection
17 | GlobalSection(SolutionProperties) = preSolution
18 | HideSolutionNode = FALSE
19 | EndGlobalSection
20 | EndGlobal
21 |
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/DeepAlignmentNetwork/AffineTransformLayer.py:
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1 | from lasagne.layers import MergeLayer
2 | import theano
3 | from theano import tensor as T
4 | import numpy as np
5 |
6 |
7 | class AffineTransformLayer(MergeLayer):
8 | def __init__(self, images, transform_params, output_shape=None, **kwargs):
9 | super(AffineTransformLayer, self).__init__([images, transform_params], **kwargs)
10 |
11 | img_shape, _ = self.input_shapes
12 |
13 | if output_shape is None:
14 | self.out_img_height = img_shape[2]
15 | self.out_img_width = img_shape[3]
16 | else:
17 | self.out_img_height = output_shape[0]
18 | self.out_img_width = output_shape[1]
19 |
20 | self.in_img_height = img_shape[2]
21 | self.in_img_width = img_shape[3]
22 |
23 | def affine_transform(self, img, A, t):
24 | pixels = [(x, y) for x in range(self.out_img_width) for y in range(self.out_img_height)]
25 | pixels = np.array(pixels, dtype=np.float32)
26 |
27 | outPixels = T.dot(pixels, A) + t
28 |
29 | outPixels = T.set_subtensor(outPixels[:, 0], T.clip(outPixels[:, 0], 0, self.in_img_height - 2))
30 | outPixels = T.set_subtensor(outPixels[:, 1], T.clip(outPixels[:, 1], 0, self.in_img_height - 2))
31 |
32 | outPixelsMinMin = outPixels.astype('int32')
33 | outPixelsMaxMin = outPixelsMinMin + [1, 0]
34 | outPixelsMinMax = outPixelsMinMin + [0, 1]
35 | outPixelsMaxMax = outPixelsMinMin + [1, 1]
36 |
37 | dx = outPixels[:, 0] - outPixelsMinMin[:, 0]
38 | dy = outPixels[:, 1] - outPixelsMinMin[:, 1]
39 |
40 | pixels = pixels.astype('int32')
41 |
42 | outImg = T.zeros((1, self.out_img_height, self.out_img_width))
43 | outImg = T.inc_subtensor(outImg[0, pixels[:, 1], pixels[:, 0]], (1 - dx) * (1 - dy) * img[outPixelsMinMin[:, 1], outPixelsMinMin[:, 0]])
44 | outImg = T.inc_subtensor(outImg[0, pixels[:, 1], pixels[:, 0]], dx * (1 - dy) * img[outPixelsMaxMin[:, 1], outPixelsMaxMin[:, 0]])
45 | outImg = T.inc_subtensor(outImg[0, pixels[:, 1], pixels[:, 0]], (1 - dx) * dy * img[outPixelsMinMax[:, 1], outPixelsMinMax[:, 0]])
46 | outImg = T.inc_subtensor(outImg[0, pixels[:, 1], pixels[:, 0]], dx * dy * img[outPixelsMaxMax[:, 1], outPixelsMaxMax[:, 0]])
47 |
48 | return outImg
49 |
50 | def affine_transform_helper(self, img, transform):
51 | A = T.zeros((2, 2))
52 |
53 | A = T.set_subtensor(A[0, 0], transform[0])
54 | A = T.set_subtensor(A[0, 1], transform[1])
55 | A = T.set_subtensor(A[1, 0], transform[2])
56 | A = T.set_subtensor(A[1, 1], transform[3])
57 | t = transform[4:6]
58 |
59 | A = T.nlinalg.matrix_inverse(A)
60 | t = T.dot(-t, A)
61 |
62 | return self.affine_transform(img[0], A, t)
63 |
64 | def get_output_shape_for(self, input_shapes):
65 | return (None, 1, self.out_img_height, self.out_img_width)
66 |
67 | def get_output_for(self, inputs, **kwargs):
68 | outImgs, updates = theano.scan(self.affine_transform_helper, inputs)
69 |
70 | return outImgs
71 |
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/DeepAlignmentNetwork/CameraDemo.py:
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1 | from FaceAlignment import FaceAlignment
2 | import numpy as np
3 | import cv2
4 | import utils
5 |
6 | #Change this to True if you want to use the DAN-Menpo-tracking.npz model, which is able to detect when face tracking is lost.
7 | useTrackingModel = False
8 |
9 | if useTrackingModel:
10 | model = FaceAlignment(112, 112, 1, 1, True)
11 | model.loadNetwork("../DAN-Menpo-tracking.npz")
12 | else:
13 | model = FaceAlignment(112, 112, 1, 2)
14 | model.loadNetwork("../DAN-Menpo.npz")
15 |
16 | vidIn = cv2.VideoCapture(0)
17 | cascade = cv2.CascadeClassifier("../data/haarcascade_frontalface_alt.xml")
18 |
19 | reset = True
20 | landmarks = None
21 |
22 | print ("Press space to detect the face, press escape to exit")
23 |
24 | while True:
25 | vis = vidIn.read()[1]
26 | if len(vis.shape) > 2:
27 | img = np.mean(vis, axis=2).astype(np.uint8)
28 | else:
29 | img = vis.astype(np.uint8)
30 |
31 | if reset:
32 | rects = cascade.detectMultiScale(img, scaleFactor=1.2, minNeighbors=3, minSize=(50, 50))
33 | if len(rects) > 0:
34 | minX = rects[0][0]
35 | maxX = rects[0][0] + rects[0][2]
36 | minY = rects[0][1]
37 | maxY = rects[0][1] + rects[0][3]
38 | cv2.rectangle(vis, (minX, minY), (maxX, maxY), (255, 0, 0))
39 | initLandmarks = utils.bestFitRect(None, model.initLandmarks, [minX, minY, maxX, maxY])
40 | reset = False
41 |
42 | if model.confidenceLayer:
43 | landmarks, confidence = model.processImg(img[np.newaxis], initLandmarks)
44 | if confidence < 0.1:
45 | reset = True
46 | else:
47 | landmarks = model.processImg(img[np.newaxis], initLandmarks)
48 | landmarks = landmarks.astype(np.int32)
49 | for i in range(landmarks.shape[0]):
50 | cv2.circle(vis, (landmarks[i, 0], landmarks[i, 1]), 2, (0, 255, 0))
51 | else:
52 | initLandmarks = utils.bestFitRect(landmarks, model.initLandmarks)
53 | if model.confidenceLayer:
54 | landmarks, confidence = model.processImg(img[np.newaxis], initLandmarks)
55 | if confidence < 0.1:
56 | reset = True
57 | else:
58 | landmarks = model.processImg(img[np.newaxis], initLandmarks)
59 | landmarks = np.round(landmarks).astype(np.int32)
60 |
61 | for i in range(landmarks.shape[0]):
62 | cv2.circle(vis, (landmarks[i, 0], landmarks[i, 1]), 2, (0, 255, 0))
63 |
64 |
65 | cv2.imshow("image", vis)
66 | key = cv2.waitKey(1)
67 |
68 | if key == 27:
69 | break
70 |
71 | if key == 32:
72 | reset = True
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/DeepAlignmentNetwork/DANtesting.py:
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1 | import numpy as np
2 | from ImageServer import ImageServer
3 | from FaceAlignment import FaceAlignment
4 | import tests
5 |
6 | datasetDir ="../data/"
7 |
8 | verbose = False
9 | showResults = False
10 | showCED = True
11 |
12 | normalization = 'corners'
13 | failureThreshold = 0.08
14 |
15 | networkFilename = "..\\DAN.npz"
16 | network = FaceAlignment(112, 112, 1, nStages=2)
17 | network.loadNetwork(networkFilename)
18 |
19 | print ("Network being tested: " + networkFilename)
20 | print ("Normalization is set to: " + normalization)
21 | print ("Failure threshold is set to: " + str(failureThreshold))
22 |
23 | commonSet = ImageServer.Load(datasetDir + "commonSet.npz")
24 | challengingSet = ImageServer.Load(datasetDir + "challengingSet.npz")
25 | w300 = ImageServer.Load(datasetDir + "w300Set.npz")
26 |
27 | print ("Processing common subset of the 300W public test set (test sets of LFPW and HELEN)")
28 | commonErrs = tests.LandmarkError(commonSet, network, normalization, showResults, verbose)
29 | print ("Processing challenging subset of the 300W public test set (IBUG dataset)")
30 | challengingErrs = tests.LandmarkError(challengingSet, network, normalization, showResults, verbose)
31 |
32 | fullsetErrs = commonErrs + challengingErrs
33 | print ("Showing results for the entire 300W pulic test set (IBUG dataset, test sets of LFPW and HELEN")
34 | print("Average error: {0}".format(np.mean(fullsetErrs)))
35 | tests.AUCError(fullsetErrs, failureThreshold, showCurve=showCED)
36 |
37 | print ("Processing 300W private test set")
38 | w300Errs = tests.LandmarkError(w300, network, normalization, showResults, verbose)
39 | tests.AUCError(w300Errs, failureThreshold, showCurve=showCED)
40 |
41 |
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/DeepAlignmentNetwork/DANtraining.py:
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1 | from ImageServer import ImageServer
2 | from FaceAlignmentTraining import FaceAlignmentTraining
3 |
4 | datasetDir = "../data/"
5 |
6 | trainSet = ImageServer.Load(datasetDir + "dataset_nimgs=60960_perturbations=[0.2, 0.2, 20, 0.25]_size=[112, 112].npz")
7 | validationSet = ImageServer.Load(datasetDir + "dataset_nimgs=100_perturbations=[]_size=[112, 112].npz")
8 |
9 |
10 | #The parameters to the FaceAlignmentTraining constructor are: number of stages and indices of stages that will be trained
11 | #first stage training only
12 | training = FaceAlignmentTraining(1, [0])
13 | #second stage training only
14 | #training = FaceAlignmentTraining(2, [1])
15 |
16 | training.loadData(trainSet, validationSet)
17 | training.initializeNetwork()
18 |
19 | #load previously saved moved
20 | #training.loadNetwork("../DAN-Menpo.npz")
21 |
22 | training.train(0.001, num_epochs=1000)
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/DeepAlignmentNetwork/DeepAlignmentNetwork.pyproj:
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1 |
2 |
3 |
4 | Debug
5 | 2.0
6 | aeb3b95a-95f2-4b4e-99e4-dd648cee5679
7 | .
8 | CameraDemo.py
9 |
10 |
11 | .
12 | .
13 | DeepAlignmentNetwork
14 | DeepAlignmentNetwork
15 |
16 |
17 | true
18 | false
19 |
20 |
21 | true
22 | false
23 |
24 |
25 |
26 |
27 | Code
28 |
29 |
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31 |
32 |
33 | Code
34 |
35 |
36 | Code
37 |
38 |
39 |
40 |
41 |
42 |
43 |
44 |
45 |
46 |
47 |
48 |
49 |
50 | 10.0
51 | $(MSBuildExtensionsPath32)\Microsoft\VisualStudio\v$(VisualStudioVersion)\Python Tools\Microsoft.PythonTools.targets
52 |
53 |
54 |
55 |
58 |
59 |
60 |
61 |
62 |
63 |
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/DeepAlignmentNetwork/FaceAlignment.py:
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1 | from __future__ import print_function
2 |
3 | import lasagne
4 | from lasagne.layers import Conv2DLayer, batch_norm
5 | from lasagne.init import GlorotUniform
6 |
7 | import numpy as np
8 | import theano
9 |
10 | from scipy import ndimage
11 |
12 | from AffineTransformLayer import AffineTransformLayer
13 | from TransformParamsLayer import TransformParamsLayer
14 | from LandmarkImageLayer import LandmarkImageLayer
15 | from LandmarkInitLayer import LandmarkInitLayer
16 | from LandmarkTranformLayer import LandmarkTransformLayer
17 |
18 | import utils
19 |
20 | class FaceAlignment(object):
21 | def __init__(self, height, width, nChannels, nStages, confidenceLayer=False):
22 | self.landmarkPatchSize = 16
23 |
24 | self.data = theano.tensor.tensor4('inputs', dtype=theano.config.floatX)
25 | self.targets = theano.tensor.tensor4('targets')
26 |
27 | self.imageHeight = height
28 | self.imageWidth = width
29 | self.nChannels = nChannels
30 |
31 | self.errors = []
32 | self.errorsTrain = []
33 |
34 | self.nStages = nStages
35 | self.confidenceLayer = confidenceLayer
36 |
37 | def initializeNetwork(self):
38 | self.layers = self.createCNN()
39 | self.network = self.layers['output']
40 |
41 | self.prediction = lasagne.layers.get_output(self.network, deterministic=True)
42 | self.generate_network_output = theano.function([self.data], [self.prediction])
43 |
44 | def addDANStage(self, stageIdx, net):
45 | prevStage = 's' + str(stageIdx - 1)
46 | curStage = 's' + str(stageIdx)
47 |
48 | #CONNNECTION LAYERS OF PREVIOUS STAGE
49 | net[prevStage + '_transform_params'] = TransformParamsLayer(net[prevStage + '_landmarks'], self.initLandmarks)
50 | net[prevStage + '_img_output'] = AffineTransformLayer(net['input'], net[prevStage + '_transform_params'])
51 |
52 | net[prevStage + '_landmarks_affine'] = LandmarkTransformLayer(net[prevStage + '_landmarks'], net[prevStage + '_transform_params'])
53 | net[prevStage + '_img_landmarks'] = LandmarkImageLayer(net[prevStage + '_landmarks_affine'], (self.imageHeight, self.imageWidth), self.landmarkPatchSize)
54 |
55 | net[prevStage + '_img_feature'] = lasagne.layers.DenseLayer(net[prevStage + '_fc1'], num_units=56 * 56, W=GlorotUniform('relu'))
56 | net[prevStage + '_img_feature'] = lasagne.layers.ReshapeLayer(net[prevStage + '_img_feature'], (-1, 1, 56, 56))
57 | net[prevStage + '_img_feature'] = lasagne.layers.Upscale2DLayer(net[prevStage + '_img_feature'], 2)
58 |
59 | #CURRENT STAGE
60 | net[curStage + '_input'] = batch_norm(lasagne.layers.ConcatLayer([net[prevStage + '_img_output'], net[prevStage + '_img_landmarks'], net[prevStage + '_img_feature']], 1))
61 |
62 | net[curStage + '_conv1_1'] = batch_norm(Conv2DLayer(net[curStage + '_input'], 64, 3, pad='same', W=GlorotUniform('relu')))
63 | net[curStage + '_conv1_2'] = batch_norm(Conv2DLayer(net[curStage + '_conv1_1'], 64, 3, pad='same', W=GlorotUniform('relu')))
64 | net[curStage + '_pool1'] = lasagne.layers.Pool2DLayer(net[curStage + '_conv1_2'], 2)
65 |
66 | net[curStage + '_conv2_1'] = batch_norm(Conv2DLayer(net[curStage + '_pool1'], 128, 3, pad=1, W=GlorotUniform('relu')))
67 | net[curStage + '_conv2_2'] = batch_norm(Conv2DLayer(net[curStage + '_conv2_1'], 128, 3, pad=1, W=GlorotUniform('relu')))
68 | net[curStage + '_pool2'] = lasagne.layers.Pool2DLayer(net[curStage + '_conv2_2'], 2)
69 |
70 | net[curStage + '_conv3_1'] = batch_norm (Conv2DLayer(net[curStage + '_pool2'], 256, 3, pad=1, W=GlorotUniform('relu')))
71 | net[curStage + '_conv3_2'] = batch_norm (Conv2DLayer(net[curStage + '_conv3_1'], 256, 3, pad=1, W=GlorotUniform('relu')))
72 | net[curStage + '_pool3'] = lasagne.layers.Pool2DLayer(net[curStage + '_conv3_2'], 2)
73 |
74 | net[curStage + '_conv4_1'] = batch_norm(Conv2DLayer(net[curStage + '_pool3'], 512, 3, pad=1, W=GlorotUniform('relu')))
75 | net[curStage + '_conv4_2'] = batch_norm (Conv2DLayer(net[curStage + '_conv4_1'], 512, 3, pad=1, W=GlorotUniform('relu')))
76 | net[curStage + '_pool4'] = lasagne.layers.Pool2DLayer(net[curStage + '_conv4_2'], 2)
77 |
78 | net[curStage + '_pool4'] = lasagne.layers.FlattenLayer(net[curStage + '_pool4'])
79 | net[curStage + '_fc1_dropout'] = lasagne.layers.DropoutLayer(net[curStage + '_pool4'], p=0.5)
80 |
81 | net[curStage + '_fc1'] = batch_norm(lasagne.layers.DenseLayer(net[curStage + '_fc1_dropout'], num_units=256, W=GlorotUniform('relu')))
82 |
83 | net[curStage + '_output'] = lasagne.layers.DenseLayer(net[curStage + '_fc1'], num_units=136, nonlinearity=None)
84 | net[curStage + '_landmarks'] = lasagne.layers.ElemwiseSumLayer([net[prevStage + '_landmarks_affine'], net[curStage + '_output']])
85 |
86 | net[curStage + '_landmarks'] = LandmarkTransformLayer(net[curStage + '_landmarks'], net[prevStage + '_transform_params'], True)
87 |
88 | def createCNN(self):
89 | net = {}
90 | net['input'] = lasagne.layers.InputLayer(shape=(None, self.nChannels, self.imageHeight, self.imageWidth), input_var=self.data)
91 | print("Input shape: {0}".format(net['input'].output_shape))
92 |
93 | #STAGE 1
94 | net['s1_conv1_1'] = batch_norm(Conv2DLayer(net['input'], 64, 3, pad='same', W=GlorotUniform('relu')))
95 | net['s1_conv1_2'] = batch_norm(Conv2DLayer(net['s1_conv1_1'], 64, 3, pad='same', W=GlorotUniform('relu')))
96 | net['s1_pool1'] = lasagne.layers.Pool2DLayer(net['s1_conv1_2'], 2)
97 |
98 | net['s1_conv2_1'] = batch_norm(Conv2DLayer(net['s1_pool1'], 128, 3, pad=1, W=GlorotUniform('relu')))
99 | net['s1_conv2_2'] = batch_norm(Conv2DLayer(net['s1_conv2_1'], 128, 3, pad=1, W=GlorotUniform('relu')))
100 | net['s1_pool2'] = lasagne.layers.Pool2DLayer(net['s1_conv2_2'], 2)
101 |
102 | net['s1_conv3_1'] = batch_norm (Conv2DLayer(net['s1_pool2'], 256, 3, pad=1, W=GlorotUniform('relu')))
103 | net['s1_conv3_2'] = batch_norm (Conv2DLayer(net['s1_conv3_1'], 256, 3, pad=1, W=GlorotUniform('relu')))
104 | net['s1_pool3'] = lasagne.layers.Pool2DLayer(net['s1_conv3_2'], 2)
105 |
106 | net['s1_conv4_1'] = batch_norm(Conv2DLayer(net['s1_pool3'], 512, 3, pad=1, W=GlorotUniform('relu')))
107 | net['s1_conv4_2'] = batch_norm (Conv2DLayer(net['s1_conv4_1'], 512, 3, pad=1, W=GlorotUniform('relu')))
108 | net['s1_pool4'] = lasagne.layers.Pool2DLayer(net['s1_conv4_2'], 2)
109 |
110 | net['s1_fc1_dropout'] = lasagne.layers.DropoutLayer(net['s1_pool4'], p=0.5)
111 | net['s1_fc1'] = batch_norm(lasagne.layers.DenseLayer(net['s1_fc1_dropout'], num_units=256, W=GlorotUniform('relu')))
112 |
113 | net['s1_output'] = lasagne.layers.DenseLayer(net['s1_fc1'], num_units=136, nonlinearity=None)
114 | net['s1_landmarks'] = LandmarkInitLayer(net['s1_output'], self.initLandmarks)
115 |
116 | if self.confidenceLayer:
117 | net['s1_confidence'] = lasagne.layers.DenseLayer(net['s1_fc1'], num_units=2, W=GlorotUniform('relu'), nonlinearity=lasagne.nonlinearities.softmax)
118 |
119 | for i in range(1, self.nStages):
120 | self.addDANStage(i + 1, net)
121 |
122 | net['output'] = net['s' + str(self.nStages) + '_landmarks']
123 | if self.confidenceLayer:
124 | net['output'] = lasagne.layers.ConcatLayer([net['output'], net['s1_confidence']])
125 |
126 | return net
127 |
128 | def loadNetwork(self, filename):
129 | print('Loading network...')
130 |
131 | with np.load(filename) as f:
132 | param_values = [f['arr_%d' % i] for i in range(len(f.files) - 5)]
133 | self.errors = f["errors"].tolist()
134 | self.errorsTrain = f["errorsTrain"].tolist()
135 | self.meanImg = f["meanImg"]
136 | self.stdDevImg = f["stdDevImg"]
137 | self.initLandmarks = f["initLandmarks"]
138 |
139 | self.initializeNetwork()
140 | nParams = len(lasagne.layers.get_all_param_values(self.network))
141 | lasagne.layers.set_all_param_values(self.network, param_values[:nParams])
142 |
143 | def processImg(self, img, inputLandmarks):
144 | inputImg, transform = self.CropResizeRotate(img, inputLandmarks)
145 | inputImg = inputImg - self.meanImg
146 | inputImg = inputImg / self.stdDevImg
147 |
148 | output = self.generate_network_output([inputImg])[0][0]
149 | if self.confidenceLayer:
150 | landmarkOutput = output[:-2]
151 | confidenceOutput = output[-2:]
152 |
153 | landmarks = landmarkOutput.reshape((-1, 2))
154 | confidence = confidenceOutput[1]
155 |
156 | return np.dot(landmarks - transform[1], np.linalg.inv(transform[0])), confidence
157 | else:
158 | landmarks = output.reshape((-1, 2))
159 | return np.dot(landmarks - transform[1], np.linalg.inv(transform[0]))
160 |
161 | def processNormalizedImg(self, img):
162 | inputImg = img.astype(np.float32)
163 | inputImg = inputImg - self.meanImg
164 | inputImg = inputImg / self.stdDevImg
165 |
166 | output = self.generate_network_output([inputImg])[0][0]
167 | if self.confidenceLayer:
168 | landmarkOutput = output[:-2]
169 | confidenceOutput = output[-2:]
170 |
171 | landmarks = landmarkOutput.reshape((-1, 2))
172 | confidence = confidenceOutput[1]
173 | return landmarks, confidence
174 | else:
175 | landmarks = output.reshape((-1, 2))
176 | return landmarks
177 |
178 | def CropResizeRotate(self, img, inputShape):
179 | A, t = utils.bestFit(self.initLandmarks, inputShape, True)
180 |
181 | A2 = np.linalg.inv(A)
182 | t2 = np.dot(-t, A2)
183 |
184 | outImg = np.zeros((self.nChannels, self.imageHeight, self.imageWidth), dtype=np.float32)
185 | for i in range(img.shape[0]):
186 | outImg[i] = ndimage.interpolation.affine_transform(img[i], A2, t2[[1, 0]], output_shape=(self.imageHeight, self.imageWidth))
187 |
188 | return outImg, [A, t]
189 |
--------------------------------------------------------------------------------
/DeepAlignmentNetwork/FaceAlignmentTraining.py:
--------------------------------------------------------------------------------
1 | from __future__ import print_function
2 |
3 | import os
4 | import time
5 | import datetime
6 | import lasagne
7 | from lasagne.layers import Conv2DLayer, batch_norm
8 | from lasagne.init import GlorotUniform
9 |
10 | from matplotlib import pyplot as plt
11 | import numpy as np
12 | import theano
13 | import theano.tensor as T
14 |
15 | from AffineTransformLayer import AffineTransformLayer
16 | from TransformParamsLayer import TransformParamsLayer
17 | from LandmarkImageLayer import LandmarkImageLayer
18 | from LandmarkInitLayer import LandmarkInitLayer
19 | from LandmarkTranformLayer import LandmarkTransformLayer
20 |
21 | class FaceAlignmentTraining(object):
22 | def __init__(self, nStages, stagesToTrain):
23 | self.batchsize = 64
24 | self.landmarkPatchSize = 16
25 |
26 | self.data = theano.tensor.tensor4('inputs', dtype=theano.config.floatX)
27 | self.targets = theano.tensor.tensor4('targets')
28 |
29 | self.errors = []
30 | self.errorsTrain = []
31 |
32 | self.nStages = nStages
33 | self.stagesToTrain = stagesToTrain
34 |
35 | def initializeNetwork(self):
36 | self.layers = self.createCNN()
37 | self.network = self.layers['output']
38 |
39 | self.prediction = lasagne.layers.get_output(self.network, deterministic=False)
40 | self.prediction_test = lasagne.layers.get_output(self.network, deterministic=True)
41 |
42 |
43 | self.generate_network_output = theano.function([self.data], [self.prediction])
44 | self.generate_network_output_deterministic = theano.function([self.data], [self.prediction_test])
45 |
46 | self.loss = self.landmarkErrorNorm(self.prediction, self.targets)
47 | self.test_loss = self.landmarkErrorNorm(self.prediction_test, self.targets)
48 |
49 | self.test_fn = theano.function([self.data, self.targets], self.test_loss)
50 |
51 | def landmarkPairErrorNorm(self, output, landmarks):
52 | gtLandmarks = landmarks[1]
53 | initLandmarks = landmarks[0]
54 |
55 | transformedLandmarks = T.reshape(output[:136], (68, 2))
56 |
57 | meanError = T.mean(T.sqrt(T.sum((transformedLandmarks - gtLandmarks)**2, axis=1)))
58 | eyeDist = (T.mean(gtLandmarks[36:42], axis=0) - T.mean(gtLandmarks[42:48], axis=0)).norm(2)
59 | res = meanError / eyeDist
60 |
61 | return res
62 |
63 | def landmarkErrorNorm(self, transforms, landmarks):
64 | errors, updates = theano.scan(self.landmarkPairErrorNorm, [transforms, landmarks])
65 |
66 | return T.mean(errors)
67 |
68 | def addDANStage(self, stageIdx, net):
69 | prevStage = 's' + str(stageIdx - 1)
70 | curStage = 's' + str(stageIdx)
71 |
72 | #CONNNECTION LAYERS OF PREVIOUS STAGE
73 | net[prevStage + '_transform_params'] = TransformParamsLayer(net[prevStage + '_landmarks'], self.initLandmarks)
74 | net[prevStage + '_img_output'] = AffineTransformLayer(net['input'], net[prevStage + '_transform_params'])
75 |
76 | net[prevStage + '_landmarks_affine'] = LandmarkTransformLayer(net[prevStage + '_landmarks'], net[prevStage + '_transform_params'])
77 | net[prevStage + '_img_landmarks'] = LandmarkImageLayer(net[prevStage + '_landmarks_affine'], (self.imageHeight, self.imageWidth), self.landmarkPatchSize)
78 |
79 | net[prevStage + '_img_feature'] = lasagne.layers.DenseLayer(net[prevStage + '_fc1'], num_units=56 * 56, W=GlorotUniform('relu'))
80 | net[prevStage + '_img_feature'] = lasagne.layers.ReshapeLayer(net[prevStage + '_img_feature'], (-1, 1, 56, 56))
81 | net[prevStage + '_img_feature'] = lasagne.layers.Upscale2DLayer(net[prevStage + '_img_feature'], 2)
82 |
83 | #CURRENT STAGE
84 | net[curStage + '_input'] = batch_norm(lasagne.layers.ConcatLayer([net[prevStage + '_img_output'], net[prevStage + '_img_landmarks'], net[prevStage + '_img_feature']], 1))
85 |
86 | net[curStage + '_conv1_1'] = batch_norm(Conv2DLayer(net[curStage + '_input'], 64, 3, pad='same', W=GlorotUniform('relu')))
87 | net[curStage + '_conv1_2'] = batch_norm(Conv2DLayer(net[curStage + '_conv1_1'], 64, 3, pad='same', W=GlorotUniform('relu')))
88 | net[curStage + '_pool1'] = lasagne.layers.Pool2DLayer(net[curStage + '_conv1_2'], 2)
89 |
90 | net[curStage + '_conv2_1'] = batch_norm(Conv2DLayer(net[curStage + '_pool1'], 128, 3, pad=1, W=GlorotUniform('relu')))
91 | net[curStage + '_conv2_2'] = batch_norm(Conv2DLayer(net[curStage + '_conv2_1'], 128, 3, pad=1, W=GlorotUniform('relu')))
92 | net[curStage + '_pool2'] = lasagne.layers.Pool2DLayer(net[curStage + '_conv2_2'], 2)
93 |
94 | net[curStage + '_conv3_1'] = batch_norm (Conv2DLayer(net[curStage + '_pool2'], 256, 3, pad=1, W=GlorotUniform('relu')))
95 | net[curStage + '_conv3_2'] = batch_norm (Conv2DLayer(net[curStage + '_conv3_1'], 256, 3, pad=1, W=GlorotUniform('relu')))
96 | net[curStage + '_pool3'] = lasagne.layers.Pool2DLayer(net[curStage + '_conv3_2'], 2)
97 |
98 | net[curStage + '_conv4_1'] = batch_norm(Conv2DLayer(net[curStage + '_pool3'], 512, 3, pad=1, W=GlorotUniform('relu')))
99 | net[curStage + '_conv4_2'] = batch_norm (Conv2DLayer(net[curStage + '_conv4_1'], 512, 3, pad=1, W=GlorotUniform('relu')))
100 | net[curStage + '_pool4'] = lasagne.layers.Pool2DLayer(net[curStage + '_conv4_2'], 2)
101 |
102 | net[curStage + '_pool4'] = lasagne.layers.FlattenLayer(net[curStage + '_pool4'])
103 | net[curStage + '_fc1_dropout'] = lasagne.layers.DropoutLayer(net[curStage + '_pool4'], p=0.5)
104 |
105 | net[curStage + '_fc1'] = batch_norm(lasagne.layers.DenseLayer(net[curStage + '_fc1_dropout'], num_units=256, W=GlorotUniform('relu')))
106 |
107 | net[curStage + '_output'] = lasagne.layers.DenseLayer(net[curStage + '_fc1'], num_units=136, nonlinearity=None)
108 | net[curStage + '_landmarks'] = lasagne.layers.ElemwiseSumLayer([net[prevStage + '_landmarks_affine'], net[curStage + '_output']])
109 |
110 | net[curStage + '_landmarks'] = LandmarkTransformLayer(net[curStage + '_landmarks'], net[prevStage + '_transform_params'], True)
111 |
112 | def createCNN(self):
113 | net = {}
114 | net['input'] = lasagne.layers.InputLayer(shape=(None, self.nChannels, self.imageHeight, self.imageWidth), input_var=self.data)
115 | print("Input shape: {0}".format(net['input'].output_shape))
116 |
117 | #STAGE 1
118 | net['s1_conv1_1'] = batch_norm(Conv2DLayer(net['input'], 64, 3, pad='same', W=GlorotUniform('relu')))
119 | net['s1_conv1_2'] = batch_norm(Conv2DLayer(net['s1_conv1_1'], 64, 3, pad='same', W=GlorotUniform('relu')))
120 | net['s1_pool1'] = lasagne.layers.Pool2DLayer(net['s1_conv1_2'], 2)
121 |
122 | net['s1_conv2_1'] = batch_norm(Conv2DLayer(net['s1_pool1'], 128, 3, pad=1, W=GlorotUniform('relu')))
123 | net['s1_conv2_2'] = batch_norm(Conv2DLayer(net['s1_conv2_1'], 128, 3, pad=1, W=GlorotUniform('relu')))
124 | net['s1_pool2'] = lasagne.layers.Pool2DLayer(net['s1_conv2_2'], 2)
125 |
126 | net['s1_conv3_1'] = batch_norm (Conv2DLayer(net['s1_pool2'], 256, 3, pad=1, W=GlorotUniform('relu')))
127 | net['s1_conv3_2'] = batch_norm (Conv2DLayer(net['s1_conv3_1'], 256, 3, pad=1, W=GlorotUniform('relu')))
128 | net['s1_pool3'] = lasagne.layers.Pool2DLayer(net['s1_conv3_2'], 2)
129 |
130 | net['s1_conv4_1'] = batch_norm(Conv2DLayer(net['s1_pool3'], 512, 3, pad=1, W=GlorotUniform('relu')))
131 | net['s1_conv4_2'] = batch_norm (Conv2DLayer(net['s1_conv4_1'], 512, 3, pad=1, W=GlorotUniform('relu')))
132 | net['s1_pool4'] = lasagne.layers.Pool2DLayer(net['s1_conv4_2'], 2)
133 |
134 | net['s1_fc1_dropout'] = lasagne.layers.DropoutLayer(net['s1_pool4'], p=0.5)
135 | net['s1_fc1'] = batch_norm(lasagne.layers.DenseLayer(net['s1_fc1_dropout'], num_units=256, W=GlorotUniform('relu')))
136 |
137 | net['s1_output'] = lasagne.layers.DenseLayer(net['s1_fc1'], num_units=136, nonlinearity=None)
138 | net['s1_landmarks'] = LandmarkInitLayer(net['s1_output'], self.initLandmarks)
139 |
140 | for i in range(1, self.nStages):
141 | self.addDANStage(i + 1, net)
142 |
143 | net['output'] = net['s' + str(self.nStages) + '_landmarks']
144 |
145 | return net
146 |
147 | def getLabelsForDataset(self, imageServer):
148 | nSamples = imageServer.gtLandmarks.shape[0]
149 | nLandmarks = imageServer.gtLandmarks.shape[1]
150 |
151 | y = np.zeros((nSamples, 2, nLandmarks, 2), dtype=np.float32)
152 | y[:, 0] = imageServer.initLandmarks
153 | y[:, 1] = imageServer.gtLandmarks
154 |
155 | return y
156 |
157 | def loadData(self, trainSet, validationSet):
158 | self.nSamples = trainSet.gtLandmarks.shape[0]
159 | self.imageHeight = trainSet.imgSize[0]
160 | self.imageWidth = trainSet.imgSize[1]
161 | self.nChannels = trainSet.imgs.shape[1]
162 |
163 | self.Xtrain = trainSet.imgs
164 | self.Xvalid = validationSet.imgs
165 |
166 | self.Ytrain = self.getLabelsForDataset(trainSet)
167 | self.Yvalid = self.getLabelsForDataset(validationSet)
168 |
169 | self.testIdxsTrainSet = range(len(self.Xvalid))
170 | self.testIdxsValidSet = range(len(self.Xvalid))
171 |
172 | self.meanImg = trainSet.meanImg
173 | self.stdDevImg = trainSet.stdDevImg
174 | self.initLandmarks = trainSet.initLandmarks[0]
175 |
176 |
177 | def iterate_minibatches(self, inputs, targets, batchsize, shuffle=False):
178 | assert len(inputs) == len(targets)
179 | if shuffle:
180 | indices = np.arange(len(inputs))
181 | np.random.shuffle(indices)
182 | for start_idx in range(0, len(inputs) - batchsize + 1, batchsize):
183 | if shuffle:
184 | excerpt = indices[start_idx:start_idx + batchsize]
185 | else:
186 | excerpt = slice(start_idx, start_idx + batchsize)
187 | yield inputs[excerpt], targets[excerpt]
188 |
189 | def loadNetwork(self, filename):
190 | print('Loading network...')
191 |
192 | with np.load(filename) as f:
193 | param_values = [f['arr_%d' % i] for i in range(len(f.files) - 5)]
194 | self.errors = f["errors"].tolist()
195 | self.errorsTrain = f["errorsTrain"].tolist()
196 | self.meanImg = f["meanImg"]
197 | self.stdDevImg = f["stdDevImg"]
198 | self.initLandmarks = f["initLandmarks"]
199 |
200 | prev_parameters = lasagne.layers.get_all_param_values(self.network);
201 |
202 | if (len(prev_parameters)!=len(param_values)):
203 | print("Loading warning: different network shape, trying to do something useful")
204 |
205 | n_assigned_parameters = 0
206 | for i in range(len(prev_parameters)):
207 | if prev_parameters[i].shape == param_values[n_assigned_parameters].shape:
208 | prev_parameters[i] = param_values[n_assigned_parameters]
209 | n_assigned_parameters += 1
210 | if n_assigned_parameters == len(param_values):
211 | break
212 | else:
213 | break
214 |
215 | if (n_assigned_parameters != len(param_values)):
216 | print("Assigned " + str(n_assigned_parameters) + "/" + str(len(param_values)) + " parameters")
217 |
218 | param_values = prev_parameters
219 |
220 | lasagne.layers.set_all_param_values(self.network, param_values)
221 |
222 | def saveNetwork(self, dir="../networks/"):
223 | if not os.path.exists(dir):
224 | os.makedirs(dir)
225 | network_filename = dir + "network_" + str(len(self.errors)).zfill(5) + "_" + str(datetime.datetime.now().strftime("%Y-%m-%d-%H-%M"))
226 |
227 | np.savez(network_filename, *lasagne.layers.get_all_param_values(self.layers["output"]), errors = self.errors, errorsTrain = self.errorsTrain,
228 | meanImg = self.meanImg, stdDevImg=self.stdDevImg, initLandmarks=self.initLandmarks)
229 |
230 | def getOutput(self, imgs, chunkSize=50):
231 | output = []
232 | nImages = len(imgs)
233 | nChunks = 1 + nImages / chunkSize
234 |
235 | imgs = np.array_split(imgs, nChunks)
236 | for imgSet in imgs:
237 | if len(output) == 0:
238 | output = self.generate_network_output_deterministic(imgSet)[0]
239 | else:
240 | output = np.vstack((output, self.generate_network_output_deterministic(imgSet)[0]))
241 |
242 | return output
243 |
244 | def validateNetwork(self):
245 | error = self.getErrors(self.Xvalid, self.Yvalid, self.test_fn, self.testIdxsValidSet)
246 | errorTrain = self.getErrors(self.Xtrain, self.Ytrain, self.test_fn, self.testIdxsTrainSet)
247 | print("Validation error: " + str(error))
248 | print("Train error: " + str(errorTrain))
249 | self.errors.append(error)
250 | self.errorsTrain.append(errorTrain)
251 | self.drawErrors()
252 |
253 | textRepresentation = np.column_stack((range(len(self.errors)), self.errors, self.errorsTrain))
254 |
255 | np.savetxt("../errors.txt", textRepresentation)
256 |
257 | def drawErrors(self):
258 | plt.plot(self.errors)
259 | plt.plot(self.errorsTrain)
260 | plt.ylim(ymax=np.max([self.errors[0], self.errorsTrain[0]]))
261 | plt.savefig("../errors.jpg")
262 | plt.clf()
263 |
264 | def getErrors(self, X, y, loss, idxs, chunkSize=50):
265 | error = 0
266 |
267 | nImages = len(idxs)
268 | nChunks = 1 + nImages / chunkSize
269 |
270 | idxs = np.array_split(idxs, nChunks)
271 | for i in range(len(idxs)):
272 | error += loss(X[idxs[i]], y[idxs[i]])
273 |
274 | error = error / len(idxs)
275 | return error
276 |
277 | def getParamsForStage(self, stageIdx):
278 | if stageIdx == 0:
279 | return lasagne.layers.get_all_params(self.layers['s1_landmarks'], trainable=True)
280 |
281 | allParams = lasagne.layers.get_all_params(self.layers['s' + str(stageIdx + 1) + '_landmarks'], trainable=True)
282 | prevParams = lasagne.layers.get_all_params(self.layers['s' + str(stageIdx) + '_landmarks'], trainable=True)
283 |
284 | params = [x for x in allParams if x not in prevParams]
285 |
286 | return params
287 |
288 | def train(self, learning_rate = 0.05, num_epochs=10000):
289 | params = []
290 | for stage in self.stagesToTrain:
291 | params += self.getParamsForStage(stage)
292 |
293 | updates = lasagne.updates.adam(self.loss, params, learning_rate=learning_rate)
294 |
295 | self.train_fn = theano.function([self.data, self.targets], self.loss, updates=updates)
296 |
297 |
298 | print("Starting training...")
299 | self.validateNetwork()
300 | lowestError = np.min(self.errors)
301 |
302 | for epoch in range(num_epochs):
303 | print("Starting epoch " + str(epoch))
304 |
305 | train_err = 0
306 | train_batches = 0
307 | start_time = time.time()
308 |
309 | for batch in self.iterate_minibatches(self.Xtrain, self.Ytrain, self.batchsize, True):
310 | inputs, targets = batch
311 | train_batches += 1
312 | train_err += self.train_fn(inputs, targets)
313 |
314 | if train_batches %40 == 0:
315 | self.validateNetwork()
316 | if self.errors[-1] < lowestError:
317 | self.saveNetwork("../")
318 | lowestError = self.errors[-1]
319 |
320 | print(train_batches)
321 |
322 | self.validateNetwork()
323 | print("training loss:\t\t{:.6f}".format(train_err / train_batches))
324 | self.saveNetwork()
325 |
--------------------------------------------------------------------------------
/DeepAlignmentNetwork/HoloFaceBackend.py:
--------------------------------------------------------------------------------
1 | import socket
2 | import sys
3 | import cv2
4 | import struct
5 | import numpy as np
6 | from FaceAlignment import FaceAlignment
7 | import utils
8 | import time
9 | import sys
10 |
11 | port = 43002
12 | nLandmarks = 51
13 | firstLandmarkIdx = 17
14 |
15 | def ReadNBytes(socket, nBytes):
16 | data = ''
17 | while len(data) < nBytes:
18 | newData = socket.recv(min(1024, nBytes - len(data)))
19 | if not newData:
20 | print "Socket disconnected"
21 | return
22 |
23 | data += newData
24 | return data;
25 |
26 | def ReceiveImg(socket):
27 | data = ReadNBytes(sock, 8)
28 | if data is None:
29 | return None
30 | imageHeight, imageWidth = struct.unpack('ii', data)
31 | print("Receiving image, height={0}, width={1}".format(imageHeight, imageWidth))
32 | data = ReadNBytes(sock, imageHeight * imageWidth)
33 | if data is None:
34 | return None
35 | img = np.fromstring(data, dtype=np.uint8).reshape((imageHeight, imageWidth))
36 |
37 | return img
38 |
39 | def ShowImageAndLandmarks(img, landmarks):
40 | intLandmarks = landmarks.astype(np.int32)
41 | for i in range(landmarks.shape[0]):
42 | cv2.circle(img, (intLandmarks[i][0], intLandmarks[i][1]), 2, (255, 0, 0))
43 |
44 | cv2.imshow("image", img)
45 | cv2.waitKey(1)
46 |
47 | def HandleFrame(sock, model):
48 | data = ReadNBytes(sock, nLandmarks * 2 * 4)
49 | if data is None:
50 | return
51 | prevFrameLandmarks = np.fromstring(data, dtype=np.float32).reshape((-1, 2))
52 | prevFrameLandmarks = prevFrameLandmarks
53 |
54 | img = ReceiveImg(sock)
55 | if img is None:
56 | return
57 |
58 | landmarks, confidence = model.processNormalizedImg(img[np.newaxis])
59 | landmarks = landmarks[firstLandmarkIdx:]
60 |
61 | A, t = utils.bestFit(prevFrameLandmarks, model.initLandmarks[firstLandmarkIdx:], True)
62 | landmarksToSend = np.dot(landmarks, A) + t
63 |
64 | confidenceAndLandmarks = np.concatenate(([confidence], landmarksToSend.flatten()))
65 | sock.sendall(confidenceAndLandmarks.astype(np.float32).tostring())
66 |
67 | ShowImageAndLandmarks(img, landmarks)
68 |
69 | def SendSettings(sock, model):
70 | print("Sending settings")
71 | sock.sendall(model.initLandmarks[17:].astype(np.float32).tostring())
72 |
73 |
74 | if __name__ == "__main__":
75 | if len(sys.argv) != 2:
76 | print ("Usage: python HoloFaceBackend.py IP_OF_HOLOLENS_DEVICE")
77 | sys.exit()
78 |
79 | HoloFaceIP = sys.argv[1]
80 | model = FaceAlignment(112, 112, 1, 1, True)
81 | model.loadNetwork("../DAN-Menpo-tracking.npz")
82 |
83 | print("Face alignment model loaded")
84 |
85 | while True:
86 | try:
87 | sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
88 | sock.settimeout(2.0)
89 | sock.connect((HoloFaceIP, port))
90 | sock.settimeout(20.0)
91 |
92 | while True:
93 | try:
94 | data = ReadNBytes(sock, 1)
95 | if data is None:
96 | continue
97 |
98 | if ord(data[0]) == 0:
99 | HandleFrame(sock, model)
100 | elif ord(data[0]) == 1:
101 | SendSettings(sock, model)
102 | except socket.timeout:
103 | pass
104 | except Exception as e:
105 | print "No connection to HoloFace"
106 |
107 | sock.close()
108 |
109 |
110 |
--------------------------------------------------------------------------------
/DeepAlignmentNetwork/ImageDemo.py:
--------------------------------------------------------------------------------
1 | from FaceAlignment import FaceAlignment
2 | import numpy as np
3 | import cv2
4 | import utils
5 |
6 | model = FaceAlignment(112, 112, 1, 1, True)
7 | model.loadNetwork("../data/DAN-Menpo-tracking.npz")
8 |
9 | cascade = cv2.CascadeClassifier("../data/haarcascade_frontalface_alt.xml")
10 |
11 | color_img = cv2.imread("../data/jk.jpg")
12 | if len(color_img.shape) > 2:
13 | gray_img = np.mean(color_img, axis=2).astype(np.uint8)
14 | else:
15 | gray_img = color_img.astype(np.uint8)
16 |
17 | # reset = True
18 | landmarks = None
19 |
20 | # if reset:
21 | rects = cascade.detectMultiScale(gray_img, scaleFactor=1.2, minNeighbors=3, minSize=(50, 50))
22 |
23 | for rect in rects:
24 | tl_x = rect[0]
25 | tl_y = rect[1]
26 | br_x = tl_x + rect[2]
27 | br_y = tl_y + rect[3]
28 |
29 | cv2.rectangle(color_img, (tl_x, tl_y), (br_x, br_y), (255, 0, 0))
30 |
31 | initLandmarks = utils.bestFitRect(None, model.initLandmarks, [tl_x, tl_y, br_x, br_y])
32 |
33 | if model.confidenceLayer:
34 | landmarks, confidence = model.processImg(gray_img[np.newaxis], initLandmarks)
35 | if confidence < 0.1:
36 | reset = True
37 | else:
38 | landmarks = model.processImg(gray_img[np.newaxis], initLandmarks)
39 |
40 | landmarks = landmarks.astype(np.int32)
41 | for i in range(landmarks.shape[0]):
42 | cv2.circle(color_img, (landmarks[i, 0], landmarks[i, 1]), 2, (0, 255, 0))
43 |
44 | cv2.imshow("image", color_img)
45 |
46 | key = cv2.waitKey(0)
47 |
--------------------------------------------------------------------------------
/DeepAlignmentNetwork/ImageServer.py:
--------------------------------------------------------------------------------
1 | from scipy import ndimage
2 | import numpy as np
3 | import utils
4 | import cPickle as pickle
5 | import glob
6 | from os import path
7 |
8 | class ImageServer(object):
9 | def __init__(self, imgSize=[112, 112], frameFraction=0.25, initialization='box', color=False):
10 | self.origLandmarks = []
11 | self.filenames = []
12 | self.mirrors = []
13 | self.meanShape = np.array([])
14 |
15 | self.meanImg = np.array([])
16 | self.stdDevImg = np.array([])
17 |
18 | self.perturbations = []
19 |
20 | self.imgSize = imgSize
21 | self.frameFraction = frameFraction
22 | self.initialization = initialization
23 | self.color = color;
24 |
25 | self.boundingBoxes = []
26 |
27 | @staticmethod
28 | def Load(filename):
29 | imageServer = ImageServer()
30 | arrays = np.load(filename)
31 | imageServer.__dict__.update(arrays)
32 |
33 | if (len(imageServer.imgs.shape) == 3):
34 | imageServer.imgs = imageServer.imgs[:, np.newaxis]
35 |
36 | return imageServer
37 |
38 | def Save(self, datasetDir, filename=None):
39 | if filename is None:
40 | filename = "dataset_nimgs={0}_perturbations={1}_size={2}".format(len(self.imgs), list(self.perturbations), self.imgSize)
41 | if self.color:
42 | filename += "_color={0}".format(self.color)
43 | filename += ".npz"
44 |
45 | arrays = {key:value for key, value in self.__dict__.items() if not key.startswith('__') and not callable(key)}
46 | np.savez(datasetDir + filename, **arrays)
47 |
48 | def PrepareData(self, imageDirs, boundingBoxFiles, meanShape, startIdx, nImgs, mirrorFlag):
49 | filenames = []
50 | landmarks = []
51 | boundingBoxes = []
52 |
53 |
54 | for i in range(len(imageDirs)):
55 | filenamesInDir = glob.glob(imageDirs[i] + "*.jpg")
56 | filenamesInDir += glob.glob(imageDirs[i] + "*.png")
57 |
58 | if boundingBoxFiles is not None:
59 | boundingBoxDict = pickle.load(open(boundingBoxFiles[i], 'rb'))
60 |
61 | for j in range(len(filenamesInDir)):
62 | filenames.append(filenamesInDir[j])
63 |
64 | ptsFilename = filenamesInDir[j][:-3] + "pts"
65 | landmarks.append(utils.loadFromPts(ptsFilename))
66 |
67 | if boundingBoxFiles is not None:
68 | basename = path.basename(filenamesInDir[j])
69 | boundingBoxes.append(boundingBoxDict[basename])
70 |
71 |
72 | filenames = filenames[startIdx : startIdx + nImgs]
73 | landmarks = landmarks[startIdx : startIdx + nImgs]
74 | boundingBoxes = boundingBoxes[startIdx : startIdx + nImgs]
75 |
76 | mirrorList = [False for i in range(nImgs)]
77 | if mirrorFlag:
78 | mirrorList = mirrorList + [True for i in range(nImgs)]
79 | filenames = np.concatenate((filenames, filenames))
80 |
81 | landmarks = np.vstack((landmarks, landmarks))
82 | boundingBoxes = np.vstack((boundingBoxes, boundingBoxes))
83 |
84 | self.origLandmarks = landmarks
85 | self.filenames = filenames
86 | self.mirrors = mirrorList
87 | self.meanShape = meanShape
88 | self.boundingBoxes = boundingBoxes
89 |
90 | def LoadImages(self):
91 | self.imgs = []
92 | self.initLandmarks = []
93 | self.gtLandmarks = []
94 |
95 | for i in range(len(self.filenames)):
96 | img = ndimage.imread(self.filenames[i])
97 |
98 | if self.color:
99 | if len(img.shape) == 2:
100 | img = np.dstack((img, img, img))
101 | else:
102 | if len(img.shape) > 2:
103 | img = np.mean(img, axis=2)
104 | img = img.astype(np.uint8)
105 |
106 | if self.mirrors[i]:
107 | self.origLandmarks[i] = utils.mirrorShape(self.origLandmarks[i], img.shape)
108 | img = np.fliplr(img)
109 |
110 | if self.color:
111 | img = np.transpose(img, (2, 0, 1))
112 | else:
113 | img = img[np.newaxis]
114 |
115 | groundTruth = self.origLandmarks[i]
116 |
117 | if self.initialization == 'rect':
118 | bestFit = utils.bestFitRect(groundTruth, self.meanShape)
119 | elif self.initialization == 'similarity':
120 | bestFit = utils.bestFit(groundTruth, self.meanShape)
121 | elif self.initialization == 'box':
122 | bestFit = utils.bestFitRect(groundTruth, self.meanShape, box=self.boundingBoxes[i])
123 |
124 | self.imgs.append(img)
125 | self.initLandmarks.append(bestFit)
126 | self.gtLandmarks.append(groundTruth)
127 |
128 | self.initLandmarks = np.array(self.initLandmarks)
129 | self.gtLandmarks = np.array(self.gtLandmarks)
130 |
131 | def GeneratePerturbations(self, nPerturbations, perturbations):
132 | self.perturbations = perturbations
133 | meanShapeSize = max(self.meanShape.max(axis=0) - self.meanShape.min(axis=0))
134 | destShapeSize = min(self.imgSize) * (1 - 2 * self.frameFraction)
135 | scaledMeanShape = self.meanShape * destShapeSize / meanShapeSize
136 |
137 | newImgs = []
138 | newGtLandmarks = []
139 | newInitLandmarks = []
140 |
141 | translationMultX, translationMultY, rotationStdDev, scaleStdDev = perturbations
142 |
143 | rotationStdDevRad = rotationStdDev * np.pi / 180
144 | translationStdDevX = translationMultX * (scaledMeanShape[:, 0].max() - scaledMeanShape[:, 0].min())
145 | translationStdDevY = translationMultY * (scaledMeanShape[:, 1].max() - scaledMeanShape[:, 1].min())
146 | print "Creating perturbations of " + str(self.gtLandmarks.shape[0]) + " shapes"
147 |
148 | for i in range(self.initLandmarks.shape[0]):
149 | print(i)
150 | for j in range(nPerturbations):
151 | tempInit = self.initLandmarks[i].copy()
152 |
153 | angle = np.random.normal(0, rotationStdDevRad)
154 | offset = [np.random.normal(0, translationStdDevX), np.random.normal(0, translationStdDevY)]
155 | scaling = np.random.normal(1, scaleStdDev)
156 |
157 | R = np.array([[np.cos(angle), -np.sin(angle)],[np.sin(angle), np.cos(angle)]])
158 |
159 | tempInit = tempInit + offset
160 | tempInit = (tempInit - tempInit.mean(axis=0)) * scaling + tempInit.mean(axis=0)
161 | tempInit = np.dot(R, (tempInit - tempInit.mean(axis=0)).T).T + tempInit.mean(axis=0)
162 |
163 | tempImg, tempInit, tempGroundTruth = self.CropResizeRotate(self.imgs[i], tempInit, self.gtLandmarks[i])
164 |
165 | newImgs.append(tempImg)
166 | newInitLandmarks.append(tempInit)
167 | newGtLandmarks.append(tempGroundTruth)
168 |
169 | self.imgs = np.array(newImgs)
170 | self.initLandmarks = np.array(newInitLandmarks)
171 | self.gtLandmarks = np.array(newGtLandmarks)
172 |
173 | def CropResizeRotateAll(self):
174 | newImgs = []
175 | newGtLandmarks = []
176 | newInitLandmarks = []
177 |
178 | for i in range(self.initLandmarks.shape[0]):
179 | tempImg, tempInit, tempGroundTruth = self.CropResizeRotate(self.imgs[i], self.initLandmarks[i], self.gtLandmarks[i])
180 |
181 | newImgs.append(tempImg)
182 | newInitLandmarks.append(tempInit)
183 | newGtLandmarks.append(tempGroundTruth)
184 |
185 | self.imgs = np.array(newImgs)
186 | self.initLandmarks = np.array(newInitLandmarks)
187 | self.gtLandmarks = np.array(newGtLandmarks)
188 |
189 | def NormalizeImages(self, imageServer=None):
190 | self.imgs = self.imgs.astype(np.float32)
191 |
192 | if imageServer is None:
193 | self.meanImg = np.mean(self.imgs, axis=0)
194 | else:
195 | self.meanImg = imageServer.meanImg
196 |
197 | self.imgs = self.imgs - self.meanImg
198 |
199 | if imageServer is None:
200 | self.stdDevImg = np.std(self.imgs, axis=0)
201 | else:
202 | self.stdDevImg = imageServer.stdDevImg
203 |
204 | self.imgs = self.imgs / self.stdDevImg
205 |
206 | from matplotlib import pyplot as plt
207 |
208 | meanImg = self.meanImg - self.meanImg.min()
209 | meanImg = 255 * meanImg / meanImg.max()
210 | meanImg = meanImg.astype(np.uint8)
211 | if self.color:
212 | plt.imshow(np.transpose(meanImg, (1, 2, 0)))
213 | else:
214 | plt.imshow(meanImg[0], cmap=plt.cm.gray)
215 | plt.savefig("../meanImg.jpg")
216 | plt.clf()
217 |
218 | stdDevImg = self.stdDevImg - self.stdDevImg.min()
219 | stdDevImg = 255 * stdDevImg / stdDevImg.max()
220 | stdDevImg = stdDevImg.astype(np.uint8)
221 | if self.color:
222 | plt.imshow(np.transpose(stdDevImg, (1, 2, 0)))
223 | else:
224 | plt.imshow(stdDevImg[0], cmap=plt.cm.gray)
225 | plt.savefig("../stdDevImg.jpg")
226 | plt.clf()
227 |
228 | def CropResizeRotate(self, img, initShape, groundTruth):
229 | meanShapeSize = max(self.meanShape.max(axis=0) - self.meanShape.min(axis=0))
230 | destShapeSize = min(self.imgSize) * (1 - 2 * self.frameFraction)
231 |
232 | scaledMeanShape = self.meanShape * destShapeSize / meanShapeSize
233 |
234 | destShape = scaledMeanShape.copy() - scaledMeanShape.mean(axis=0)
235 | offset = np.array(self.imgSize[::-1]) / 2
236 | destShape += offset
237 |
238 | A, t = utils.bestFit(destShape, initShape, True)
239 |
240 | A2 = np.linalg.inv(A)
241 | t2 = np.dot(-t, A2)
242 |
243 | outImg = np.zeros((img.shape[0], self.imgSize[0], self.imgSize[1]), dtype=img.dtype)
244 | for i in range(img.shape[0]):
245 | outImg[i] = ndimage.interpolation.affine_transform(img[i], A2, t2[[1, 0]], output_shape=self.imgSize)
246 |
247 | initShape = np.dot(initShape, A) + t
248 |
249 | groundTruth = np.dot(groundTruth, A) + t
250 | return outImg, initShape, groundTruth
251 |
252 |
253 |
--------------------------------------------------------------------------------
/DeepAlignmentNetwork/LandmarkImageLayer.py:
--------------------------------------------------------------------------------
1 | from lasagne.layers import Layer
2 | import theano
3 | from theano import tensor as T
4 | import itertools
5 | import numpy as np
6 |
7 | class LandmarkImageLayer(Layer):
8 | def __init__(self, increments, img_shape, patch_size, **kwargs):
9 | super(LandmarkImageLayer, self).__init__(increments, **kwargs)
10 |
11 | self.img_shape = img_shape
12 | self.patch_size = patch_size
13 | self.half_size = int(patch_size / 2)
14 |
15 | self.offsets = np.array(list(itertools.product(range(-self.half_size, self.half_size + 1), range(-self.half_size, self.half_size + 1))))
16 |
17 | def get_output_shape_for(self, input_shape):
18 | return (input_shape[0], 1, self.img_shape[0], self.img_shape[1])
19 |
20 | def draw_landmarks_helper(self, landmark):
21 | img = T.zeros((1, self.img_shape[0], self.img_shape[1]))
22 |
23 | intLandmark = landmark.astype('int32')
24 | locations = self.offsets + intLandmark
25 | dxdy = landmark - intLandmark
26 |
27 | offsetsSubPix = self.offsets - dxdy
28 | vals = 1 / (1 + T.sqrt(T.sum(offsetsSubPix * offsetsSubPix, axis=1) + 1e-6))
29 |
30 | img = T.set_subtensor(img[0, locations[:, 1], locations[:, 0]], vals)
31 | return img
32 |
33 | def draw_landmarks(self, input):
34 | landmarks = input.reshape((-1, 2))
35 | landmarks = T.set_subtensor(landmarks[:, 0], T.clip(landmarks[:, 0], self.half_size, self.img_shape[1] - 1 - self.half_size))
36 | landmarks = T.set_subtensor(landmarks[:, 1], T.clip(landmarks[:, 1], self.half_size, self.img_shape[0] - 1 - self.half_size))
37 |
38 | imgs, updates = theano.scan(self.draw_landmarks_helper, landmarks)
39 | img = T.max(imgs, 0)
40 |
41 | return img
42 |
43 | def get_output_for(self, input, **kwargs):
44 | output, updates = theano.scan(self.draw_landmarks, [input])
45 |
46 | return output
47 |
48 |
--------------------------------------------------------------------------------
/DeepAlignmentNetwork/LandmarkInitLayer.py:
--------------------------------------------------------------------------------
1 | from lasagne.layers import Layer
2 |
3 | class LandmarkInitLayer(Layer):
4 | def __init__(self, increments, init_landmarks, **kwargs):
5 | super(LandmarkInitLayer, self).__init__(increments, **kwargs)
6 |
7 | self.init_landmarks = init_landmarks.flatten()
8 |
9 | def get_output_shape_for(self, input_shape):
10 | return input_shape
11 |
12 | def get_output_for(self, input, **kwargs):
13 | output = input + self.init_landmarks
14 |
15 | return output
16 |
--------------------------------------------------------------------------------
/DeepAlignmentNetwork/LandmarkTranformLayer.py:
--------------------------------------------------------------------------------
1 | from lasagne.layers import MergeLayer
2 | import theano
3 | from theano import tensor as T
4 |
5 |
6 | class LandmarkTransformLayer(MergeLayer):
7 | def __init__(self, landmarks, transform_params, inverse=False, **kwargs):
8 | super(LandmarkTransformLayer, self).__init__([landmarks, transform_params], **kwargs)
9 |
10 | self.inverse = inverse
11 |
12 | def affine_transform_helper(self, landmarks, transform):
13 | A = T.zeros((2, 2))
14 |
15 | A = T.set_subtensor(A[0, 0], transform[0])
16 | A = T.set_subtensor(A[0, 1], transform[1])
17 | A = T.set_subtensor(A[1, 0], transform[2])
18 | A = T.set_subtensor(A[1, 1], transform[3])
19 | t = transform[4:6]
20 |
21 | if self.inverse:
22 | A = T.nlinalg.matrix_inverse(A)
23 | t = T.dot(-t, A)
24 |
25 | output = (T.dot(landmarks.reshape((-1, 2)), A) + t).flatten()
26 | return output
27 |
28 | def get_output_shape_for(self, input_shapes):
29 | output_shape = list(input_shapes[0])
30 | return tuple(output_shape)
31 |
32 | def get_output_for(self, inputs, **kwargs):
33 | outImgs, updates = theano.scan(self.affine_transform_helper, inputs)
34 |
35 | return outImgs
36 |
--------------------------------------------------------------------------------
/DeepAlignmentNetwork/MenpoEval.py:
--------------------------------------------------------------------------------
1 | from FaceAlignment import FaceAlignment
2 | import utils
3 | import numpy as np
4 | import os
5 | import glob
6 | import cv2
7 | import ntpath
8 | from matplotlib import pyplot as plt
9 |
10 | ptsOutputDir = "../results/pts/"
11 | imgOutputDir = "../results/imgs/"
12 | MenpoDir = "../data/images/Menpo testset/semifrontal/"
13 | imageHeightFraction = 0.46
14 |
15 | networkFilename = "../DAN-Menpo.npz"
16 | network = FaceAlignment(112, 112, 1, nStages=2)
17 | network.loadNetwork(networkFilename)
18 |
19 | print "Image height fraction: " + str(imageHeightFraction)
20 |
21 | if not os.path.exists(ptsOutputDir):
22 | os.makedirs(ptsOutputDir)
23 | if not os.path.exists(imgOutputDir):
24 | os.makedirs(imgOutputDir)
25 | filenames = glob.glob(MenpoDir + "\\*.*")
26 |
27 |
28 | for i in range(len(filenames)):
29 | print(i)
30 |
31 | img = cv2.imread(filenames[i])
32 | imgColor = np.copy(img[:, :, [2, 1, 0]])
33 | if len(img.shape) > 2:
34 | img = np.mean(img, axis=2)
35 |
36 | faceHeight = img.shape[0] * imageHeightFraction
37 | faceWidth = faceHeight
38 | center = np.array(img.shape) / 2
39 |
40 | box = [center[1] - faceWidth / 2, center[0] - faceHeight / 2, center[1] + faceWidth / 2, center[0] + faceHeight / 2]
41 |
42 | #first step
43 | initLandmarks = utils.bestFitRect([], network.initLandmarks, box)
44 | firstStepLandmarks = network.processImg(img[np.newaxis], initLandmarks)
45 |
46 | #second step
47 | normImg, transform = network.CropResizeRotate(img[np.newaxis], firstStepLandmarks)
48 | normFirstStepLandmarks = np.dot(firstStepLandmarks, transform[0]) + transform[1]
49 | initLandmarks2 = utils.bestFitRect(normFirstStepLandmarks, network.initLandmarks)
50 |
51 | finalLandmarks = network.processImg(normImg, initLandmarks2)
52 | finalLandmarks = np.dot(finalLandmarks - transform[1], np.linalg.inv(transform[0]))
53 |
54 |
55 | baseName = ntpath.basename(filenames[i])[:-4]
56 | utils.saveToPts(ptsOutputDir + baseName + ".pts", finalLandmarks)
57 |
58 | plt.plot((box[2], box[0], box[0], box[2], box[2]), (box[1], box[1], box[3], box[3], box[1]), 'b', linewidth=3.0)
59 | plt.plot(finalLandmarks[:, 0], finalLandmarks[:, 1], 'go')
60 | plt.imshow(imgColor, cmap=plt.cm.gray)
61 | plt.savefig(imgOutputDir + baseName + ".png", dpi=200)
62 | plt.clf()
63 |
--------------------------------------------------------------------------------
/DeepAlignmentNetwork/TestSetPreparation.py:
--------------------------------------------------------------------------------
1 | from ImageServer import ImageServer
2 | import numpy as np
3 |
4 | commonSetImageDirs = ["../data/images/lfpw/testset/", "../data/images/helen/testset/"]
5 | commonSetBoundingBoxFiles = ["../data/boxesLFPWTest.pkl", "../data/boxesHelenTest.pkl"]
6 |
7 | challengingSetImageDirs = ["../data/images/ibug/"]
8 | challengingSetBoundingBoxFiles = ["../data/boxesIBUG.pkl"]
9 |
10 | w300SetImageDirs = ["../data/images/300W/01_Indoor/", "../data/images/300W/02_Outdoor/"]
11 | w300SetBoundingBoxFiles = ["../data/boxes300WIndoor.pkl", "../data/boxes300WOutdoor.pkl"]
12 |
13 | datasetDir = "../data/"
14 |
15 | meanShape = np.load("../data/meanFaceShape.npz")["meanShape"]
16 |
17 | commonSet = ImageServer(initialization='box')
18 | commonSet.PrepareData(commonSetImageDirs, commonSetBoundingBoxFiles, meanShape, 0, 1000, False)
19 | commonSet.LoadImages()
20 | commonSet.CropResizeRotateAll()
21 | commonSet.imgs = commonSet.imgs.astype(np.float32)
22 | commonSet.Save(datasetDir, "commonSet.npz")
23 |
24 | challengingSet = ImageServer(initialization='box')
25 | challengingSet.PrepareData(challengingSetImageDirs, challengingSetBoundingBoxFiles, meanShape, 0, 1000, False)
26 | challengingSet.LoadImages()
27 | challengingSet.CropResizeRotateAll()
28 | challengingSet.imgs = challengingSet.imgs.astype(np.float32)
29 | challengingSet.Save(datasetDir, "challengingSet.npz")
30 |
31 | w300Set = ImageServer(initialization='box')
32 | w300Set.PrepareData(w300SetImageDirs, w300SetBoundingBoxFiles, meanShape, 0, 1000, False)
33 | w300Set.LoadImages()
34 | w300Set.CropResizeRotateAll()
35 | w300Set.imgs = w300Set.imgs.astype(np.float32)
36 | w300Set.Save(datasetDir, "w300Set.npz")
--------------------------------------------------------------------------------
/DeepAlignmentNetwork/TrainingSetPreparation.py:
--------------------------------------------------------------------------------
1 | from ImageServer import ImageServer
2 | import numpy as np
3 |
4 | imageDirs = ["../data/images/lfpw/trainset/", "../data/images/helen/trainset/", "../data/images/afw/"]
5 | boundingBoxFiles = ["../data/boxesLFPWTrain.pkl", "../data/boxesHelenTrain.pkl", "../data/boxesAFW.pkl"]
6 |
7 | datasetDir = "../data/"
8 |
9 | meanShape = np.load("../data/meanFaceShape.npz")["meanShape"]
10 |
11 | trainSet = ImageServer(initialization='rect')
12 | trainSet.PrepareData(imageDirs, None, meanShape, 100, 100000, True)
13 | trainSet.LoadImages()
14 | trainSet.GeneratePerturbations(10, [0.2, 0.2, 20, 0.25])
15 | trainSet.NormalizeImages()
16 | trainSet.Save(datasetDir)
17 |
18 | validationSet = ImageServer(initialization='box')
19 | validationSet.PrepareData(imageDirs, boundingBoxFiles, meanShape, 0, 100, False)
20 | validationSet.LoadImages()
21 | validationSet.CropResizeRotateAll()
22 | validationSet.imgs = validationSet.imgs.astype(np.float32)
23 | validationSet.NormalizeImages(trainSet)
24 | validationSet.Save(datasetDir)
--------------------------------------------------------------------------------
/DeepAlignmentNetwork/TransformParamsLayer.py:
--------------------------------------------------------------------------------
1 | from lasagne.layers import Layer
2 | import theano
3 | from theano import tensor as T
4 |
5 | class TransformParamsLayer(Layer):
6 | def __init__(self, shape_updates, mean_shape, **kwargs):
7 | super(TransformParamsLayer, self).__init__(shape_updates, **kwargs)
8 |
9 | self.mean_shape = mean_shape
10 |
11 | def get_output_shape_for(self, input_shapes):
12 | return (None, 6)
13 |
14 | def bestFit(self, transformed_shape):
15 | destination = self.mean_shape
16 | source = transformed_shape.reshape((-1, 2))
17 |
18 | destMean = T.mean(destination, axis=0)
19 | srcMean = T.mean(source, axis=0)
20 |
21 | srcVec = (source - srcMean).flatten()
22 | destVec = (destination - destMean).flatten()
23 |
24 | a = T.dot(srcVec, destVec) / T.nlinalg.norm(srcVec, 2)**2
25 | b = 0
26 | for i in range(self.mean_shape.shape[0]):
27 | b += srcVec[2*i] * destVec[2*i+1] - srcVec[2*i+1] * destVec[2*i]
28 | b = b / T.nlinalg.norm(srcVec, 2)**2
29 |
30 | A = T.zeros((2, 2))
31 | A = T.set_subtensor(A[0, 0], a)
32 | A = T.set_subtensor(A[0, 1], b)
33 | A = T.set_subtensor(A[1, 0], -b)
34 | A = T.set_subtensor(A[1, 1], a)
35 | srcMean = T.dot(srcMean, A)
36 |
37 | return T.concatenate((A.flatten(), destMean - srcMean))
38 |
39 | def get_output_for(self, input, **kwargs):
40 | transforms, updates = theano.scan(self.bestFit, [input])
41 |
42 | return transforms
--------------------------------------------------------------------------------
/DeepAlignmentNetwork/tests.py:
--------------------------------------------------------------------------------
1 | import numpy as np
2 | from matplotlib import pyplot as plt
3 | from scipy.integrate import simps
4 | from matplotlib import pyplot as plt
5 |
6 | def LandmarkError(imageServer, faceAlignment, normalization='centers', showResults=False, verbose=False):
7 | errors = []
8 | nImgs = len(imageServer.imgs)
9 |
10 | for i in range(nImgs):
11 | initLandmarks = imageServer.initLandmarks[i]
12 | gtLandmarks = imageServer.gtLandmarks[i]
13 | img = imageServer.imgs[i]
14 |
15 | if img.shape[0] > 1:
16 | img = np.mean(img, axis=0)[np.newaxis]
17 |
18 | resLandmarks = initLandmarks
19 | resLandmarks = faceAlignment.processImg(img, resLandmarks)
20 |
21 | if normalization == 'centers':
22 | normDist = np.linalg.norm(np.mean(gtLandmarks[36:42], axis=0) - np.mean(gtLandmarks[42:48], axis=0))
23 | elif normalization == 'corners':
24 | normDist = np.linalg.norm(gtLandmarks[36] - gtLandmarks[45])
25 | elif normalization == 'diagonal':
26 | height, width = np.max(gtLandmarks, axis=0) - np.min(gtLandmarks, axis=0)
27 | normDist = np.sqrt(width ** 2 + height ** 2)
28 |
29 | error = np.mean(np.sqrt(np.sum((gtLandmarks - resLandmarks)**2,axis=1))) / normDist
30 | errors.append(error)
31 | if verbose:
32 | print("{0}: {1}".format(i, error))
33 |
34 | if showResults:
35 | plt.imshow(img[0], cmap=plt.cm.gray)
36 | plt.plot(resLandmarks[:, 0], resLandmarks[:, 1], 'o')
37 | plt.show()
38 |
39 | if verbose:
40 | print "Image idxs sorted by error"
41 | print np.argsort(errors)
42 | avgError = np.mean(errors)
43 | print "Average error: {0}".format(avgError)
44 |
45 | return errors
46 |
47 |
48 | def AUCError(errors, failureThreshold, step=0.0001, showCurve=False):
49 | nErrors = len(errors)
50 | xAxis = list(np.arange(0., failureThreshold + step, step))
51 |
52 | ced = [float(np.count_nonzero([errors <= x])) / nErrors for x in xAxis]
53 |
54 | AUC = simps(ced, x=xAxis) / failureThreshold
55 | failureRate = 1. - ced[-1]
56 |
57 | print "AUC @ {0}: {1}".format(failureThreshold, AUC)
58 | print "Failure rate: {0}".format(failureRate)
59 |
60 | if showCurve:
61 | plt.plot(xAxis, ced)
62 | plt.show()
63 |
64 |
--------------------------------------------------------------------------------
/DeepAlignmentNetwork/utils.py:
--------------------------------------------------------------------------------
1 | import numpy as np
2 |
3 | def loadFromPts(filename):
4 | landmarks = np.genfromtxt(filename, skip_header=3, skip_footer=1)
5 | landmarks = landmarks - 1
6 |
7 | return landmarks
8 |
9 | def saveToPts(filename, landmarks):
10 | pts = landmarks + 1
11 |
12 | header = 'version: 1\nn_points: {}\n{{'.format(pts.shape[0])
13 | np.savetxt(filename, pts, delimiter=' ', header=header, footer='}', fmt='%.3f', comments='')
14 |
15 | def bestFitRect(points, meanS, box=None):
16 | if box is None:
17 | box = np.array([points[:, 0].min(), points[:, 1].min(), points[:, 0].max(), points[:, 1].max()])
18 | boxCenter = np.array([(box[0] + box[2]) / 2, (box[1] + box[3]) / 2 ])
19 |
20 | boxWidth = box[2] - box[0]
21 | boxHeight = box[3] - box[1]
22 |
23 | meanShapeWidth = meanS[:, 0].max() - meanS[:, 0].min()
24 | meanShapeHeight = meanS[:, 1].max() - meanS[:, 1].min()
25 |
26 | scaleWidth = boxWidth / meanShapeWidth
27 | scaleHeight = boxHeight / meanShapeHeight
28 | scale = (scaleWidth + scaleHeight) / 2
29 |
30 | S0 = meanS * scale
31 |
32 | S0Center = [(S0[:, 0].min() + S0[:, 0].max()) / 2, (S0[:, 1].min() + S0[:, 1].max()) / 2]
33 | S0 += boxCenter - S0Center
34 |
35 | return S0
36 |
37 | def bestFit(destination, source, returnTransform=False):
38 | destMean = np.mean(destination, axis=0)
39 | srcMean = np.mean(source, axis=0)
40 |
41 | srcVec = (source - srcMean).flatten()
42 | destVec = (destination - destMean).flatten()
43 |
44 | a = np.dot(srcVec, destVec) / np.linalg.norm(srcVec)**2
45 | b = 0
46 | for i in range(destination.shape[0]):
47 | b += srcVec[2*i] * destVec[2*i+1] - srcVec[2*i+1] * destVec[2*i]
48 | b = b / np.linalg.norm(srcVec)**2
49 |
50 | T = np.array([[a, b], [-b, a]])
51 | srcMean = np.dot(srcMean, T)
52 |
53 | if returnTransform:
54 | return T, destMean - srcMean
55 | else:
56 | return np.dot(srcVec.reshape((-1, 2)), T) + destMean
57 |
58 | def mirrorShape(shape, imgShape=None):
59 | imgShapeTemp = np.array(imgShape)
60 | shape2 = mirrorShapes(shape.reshape((1, -1, 2)), imgShapeTemp.reshape((1, -1)))[0]
61 |
62 | return shape2
63 |
64 | def mirrorShapes(shapes, imgShapes=None):
65 | shapes2 = shapes.copy()
66 |
67 | for i in range(shapes.shape[0]):
68 | if imgShapes is None:
69 | shapes2[i, :, 0] = -shapes2[i, :, 0]
70 | else:
71 | shapes2[i, :, 0] = -shapes2[i, :, 0] + imgShapes[i][1]
72 |
73 | lEyeIndU = range(36, 40)
74 | lEyeIndD = [40, 41]
75 | rEyeIndU = range(42, 46)
76 | rEyeIndD = [46, 47]
77 | lBrowInd = range(17, 22)
78 | rBrowInd = range(22, 27)
79 |
80 | uMouthInd = range(48, 55)
81 | dMouthInd = range(55, 60)
82 | uInnMouthInd = range(60, 65)
83 | dInnMouthInd = range(65, 68)
84 | noseInd = range(31, 36)
85 | beardInd = range(17)
86 |
87 | lEyeU = shapes2[i, lEyeIndU].copy()
88 | lEyeD = shapes2[i, lEyeIndD].copy()
89 | rEyeU = shapes2[i, rEyeIndU].copy()
90 | rEyeD = shapes2[i, rEyeIndD].copy()
91 | lBrow = shapes2[i, lBrowInd].copy()
92 | rBrow = shapes2[i, rBrowInd].copy()
93 |
94 | uMouth = shapes2[i, uMouthInd].copy()
95 | dMouth = shapes2[i, dMouthInd].copy()
96 | uInnMouth = shapes2[i, uInnMouthInd].copy()
97 | dInnMouth = shapes2[i, dInnMouthInd].copy()
98 | nose = shapes2[i, noseInd].copy()
99 | beard = shapes2[i, beardInd].copy()
100 |
101 | lEyeIndU.reverse()
102 | lEyeIndD.reverse()
103 | rEyeIndU.reverse()
104 | rEyeIndD.reverse()
105 | lBrowInd.reverse()
106 | rBrowInd.reverse()
107 |
108 | uMouthInd.reverse()
109 | dMouthInd.reverse()
110 | uInnMouthInd.reverse()
111 | dInnMouthInd.reverse()
112 | beardInd.reverse()
113 | noseInd.reverse()
114 |
115 | shapes2[i, rEyeIndU] = lEyeU
116 | shapes2[i, rEyeIndD] = lEyeD
117 | shapes2[i, lEyeIndU] = rEyeU
118 | shapes2[i, lEyeIndD] = rEyeD
119 | shapes2[i, rBrowInd] = lBrow
120 | shapes2[i, lBrowInd] = rBrow
121 |
122 | shapes2[i, uMouthInd] = uMouth
123 | shapes2[i, dMouthInd] = dMouth
124 | shapes2[i, uInnMouthInd] = uInnMouth
125 | shapes2[i, dInnMouthInd] = dInnMouth
126 | shapes2[i, noseInd] = nose
127 | shapes2[i, beardInd] = beard
128 |
129 | return shapes2
130 |
131 |
--------------------------------------------------------------------------------
/LICENSE:
--------------------------------------------------------------------------------
1 | The MIT License (MIT)
2 |
3 | Copyright (c) 2017 Marek Kowalski
4 |
5 | Permission is hereby granted, free of charge, to any person obtaining a copy
6 | of this software and associated documentation files (the "Software"), to deal
7 | in the Software without restriction, including without limitation the rights
8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
9 | copies of the Software, and to permit persons to whom the Software is
10 | furnished to do so, subject to the following conditions:
11 |
12 | The above copyright notice and this permission notice shall be included in all
13 | copies or substantial portions of the Software.
14 |
15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
21 | SOFTWARE.
22 |
23 |
--------------------------------------------------------------------------------
/README.md:
--------------------------------------------------------------------------------
1 | # Deep Alignment Network #
2 | This is a reference implementation of the face alignment method described in "Deep Alignment Network: A convolutional neural network for robust face alignment" which has been accepted to the First Faces in-the-wild Workshop-Challenge at CVPR 2017. You can read the entire paper on Arxiv [here](https://arxiv.org/abs/1706.01789). You can download the presentation and poster from Dropbox [here](https://www.dropbox.com/sh/u4g2o5kha0mt1uc/AADDMkoMKG2t4iiTxMUC6e2Ta?dl=0) or Google drive [here](https://drive.google.com/drive/folders/1QFZk_ED_FLW0xZC_gNuAKsYjLyKRMPPy).
3 |
4 |
5 |
6 | ## Getting started ##
7 | First of all you need to make sure you have installed Python 2.7. For that purpose we recommend Anaconda, it has all the necessary libraries except:
8 | * Theano 0.9.0
9 | * Lasagne 0.2
10 | * OpenCV 3.1.0 or newer
11 |
12 | OpenCV can be downloaded from Christoph Gohlke's [website](http://www.lfd.uci.edu/~gohlke/pythonlibs/).
13 | Theano and Lasagne can be installed with the following commands:
14 | ```
15 | pip install Theano==0.9.0
16 | pip install https://github.com/Lasagne/Lasagne/archive/master.zip
17 | ```
18 | Once you have installed Python and the dependencies download at least one of the two pre-trained models available on Dropbox [here](https://www.dropbox.com/sh/v754z1egib0hamh/AADGX1SE9GCj4h3eDazsc0bXa?dl=0) or Google drive [here](https://drive.google.com/open?id=168tC2OxS5DjyaiuDy_JhIV3eje8K_PLJ).
19 |
20 | The easiest way to see our method in action is to run the CameraDemo.py script which performs face tracking on a local webcam.
21 |
22 | ## Running the experiments from the article ##
23 | Before continuing download the model files as described above.
24 |
25 | ### Comparison with state-of-the-art ###
26 | Download the 300W, LFPW, HELEN, AFW and IBUG datasets from https://ibug.doc.ic.ac.uk/resources/facial-point-annotations/ and extract them to /data/images/ into separate directories: 300W, lfpw, helen, afw and ibug.
27 | Run the TestSetPreparation.py script, it may take a while.
28 |
29 | Use the DANtesting.py script to perform the experiments. It will calculate the average error for all of the test subsets as well as the AUC@0.08 score and failure rate for the 300W public and private test sets.
30 |
31 | The parameters you can set in the script are as follows:
32 | * verbose: if True the script will display the error for each image,
33 | * showResults: if True it will show the localized landmarks for each image,
34 | * showCED: if True the Cumulative Error Distribution curve will be shown along with the AUC score,
35 | * normalization: 'centers' for inter-pupil distance, 'corners' for inter-ocular distance, 'diagonal' for bounding box diagonal normalization.
36 | * failureThreshold: the error threshold over which the results are considered to be failures, for inter-ocular distance it should be set to 0.08,
37 | * networkFilename: either '../DAN.npz' or '../DAN-Menpo.npz'.
38 |
39 | ### Results on the Menpo test set ###
40 | Download the Menpo test set from https://ibug.doc.ic.ac.uk/resources/ and extract it. Open the MenpoEval.py script and make sure that MenpoDir is set to the directory with images that you just extracted.
41 | Run the scripts to process the dataset. The results will be saved as images and pts files in the directories indicated in the imgOutputDir and ptsOutputDir variables.
42 |
43 | ## TensorFlow implementation ##
44 | Two TensorFlow implementations of Deep Alignment Network have been published by other GitHub users:
45 | - [zjjMaiMai's implementatation](https://github.com/zjjMaiMai/Deep-Alignment-Network-A-convolutional-neural-network-for-robust-face-alignment),
46 | - [mariolew's implementatation](https://github.com/mariolew/Deep-Alignment-Network-tensorflow).
47 |
48 | ## Citation ##
49 | If you use this software in your research, then please cite the following paper:
50 |
51 | Kowalski, M.; Naruniec, J.; Trzcinski, T.: "Deep Alignment Network: A convolutional neural network for robust face alignment", CVPRW 2017
52 |
53 | ## License ##
54 | While the code is licensed under the MIT license, which allows for commercial use, keep in mind that the models linked above were trained on the 300-W dataset, which allows for research use only. For details please see: https://ibug.doc.ic.ac.uk/resources/facial-point-annotations/
55 |
56 | ## Contact ##
57 | If you have any questions or suggestions feel free to contact me at .
58 |
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455 | Rp188
456 | (I1
457 | (L4L
458 | tp189
459 | g12
460 | I00
461 | S'\x00\x00\x00\x00\x00\xe8z@\x00\x00\x00\x00\x004\x84@\x00\x00\x00\x00\x004\x81@\x00\x00\x00\x00\x00\x94\x89@'
462 | p190
463 | tp191
464 | bsS'indoor_106.png'
465 | p192
466 | g2
467 | (g3
468 | (I0
469 | tp193
470 | g5
471 | tp194
472 | Rp195
473 | (I1
474 | (L4L
475 | tp196
476 | g12
477 | I00
478 | S'\x00\x00\x00\x00\x00\xf2\x9b@\x00\x00\x00\x00\x00\xe4\x88@\x00\x00\x00\x00\x00)\xa0@\x00\x00\x00\x00\x00\xf2\x90@'
479 | p197
480 | tp198
481 | bsS'indoor_272.png'
482 | p199
483 | g2
484 | (g3
485 | (I0
486 | tp200
487 | g5
488 | tp201
489 | Rp202
490 | (I1
491 | (L4L
492 | tp203
493 | g12
494 | I00
495 | S'H\xe1z\x14\xae\xbd{@\xe5\xd0"\xdb\xf9\xcai@\x85\xebQ\xb8\x1e}\x82@w\xbe\x9f\x1a/qx@'
496 | p204
497 | tp205
498 | bsS'indoor_115.png'
499 | p206
500 | g2
501 | (g3
502 | (I0
503 | tp207
504 | g5
505 | tp208
506 | Rp209
507 | (I1
508 | (L4L
509 | tp210
510 | g12
511 | I00
512 | S"}?5^\xba\xd0\x80@Nb\x10X9\x9c}@\x17\xd9\xce\xf7S'\x8b@+\x87\x16\xd9\xce\xdd\x8a@"
513 | p211
514 | tp212
515 | bsS'indoor_271.png'
516 | p213
517 | g2
518 | (g3
519 | (I0
520 | tp214
521 | g5
522 | tp215
523 | Rp216
524 | (I1
525 | (L4L
526 | tp217
527 | g12
528 | I00
529 | S'\x00\x00\x00\x00\x00@N@\x00\x00\x00\x00\x00@J@\x00\x00\x00\x00\x00\x10h@\x00\x00\x00\x00\x00\x10c@'
530 | p218
531 | tp219
532 | bsS'indoor_293.png'
533 | p220
534 | g2
535 | (g3
536 | (I0
537 | tp221
538 | g5
539 | tp222
540 | Rp223
541 | (I1
542 | (L4L
543 | tp224
544 | g12
545 | I00
546 | S'\x00\x00\x00\x00\x00\x90j@\x00\x00\x00\x00\x00\x10g@\x00\x00\x00\x00\x00\x08t@\x00\x00\x00\x00\x00\x88q@'
547 | p225
548 | tp226
549 | bsS'indoor_127.png'
550 | p227
551 | g2
552 | (g3
553 | (I0
554 | tp228
555 | g5
556 | tp229
557 | Rp230
558 | (I1
559 | (L4L
560 | tp231
561 | g12
562 | I00
563 | S'\xcf\xf7S\xe3\xa5\xac\x80@T\xe3\xa5\x9b\xc4\x1ck@Zd;\xdfO@\x89@o\x12\x83\xc0\xca\xfb\x82@'
564 | p232
565 | tp233
566 | bsS'indoor_018.png'
567 | p234
568 | g2
569 | (g3
570 | (I0
571 | tp235
572 | g5
573 | tp236
574 | Rp237
575 | (I1
576 | (L4L
577 | tp238
578 | g12
579 | I00
580 | S'\xdfO\x8d\x97n\xda\\@\xe3\xa5\x9b\xc4 |k@\xe9&1\x08\xacrv@\xa4p=\n\xd7\xab{@'
581 | p239
582 | tp240
583 | bsS'indoor_019.png'
584 | p241
585 | g2
586 | (g3
587 | (I0
588 | tp242
589 | g5
590 | tp243
591 | Rp244
592 | (I1
593 | (L4L
594 | tp245
595 | g12
596 | I00
597 | S'\x00\x00\x00\x00\x00\x90g@\x00\x00\x00\x00\x00\x90j@\x00\x00\x00\x00\x00\xc8|@\x00\x00\x00\x00\x00\xc8}@'
598 | p246
599 | tp247
600 | bsS'indoor_209.png'
601 | p248
602 | g2
603 | (g3
604 | (I0
605 | tp249
606 | g5
607 | tp250
608 | Rp251
609 | (I1
610 | (L4L
611 | tp252
612 | g12
613 | I00
614 | S'\x00\x00\x00\x00\x00\x10j@\x00\x00\x00\x00\x00 S@\x00\x00\x00\x00\x00\xc8r@\x00\x00\x00\x00\x00\x90d@'
615 | p253
616 | tp254
617 | bsS'indoor_061.png'
618 | p255
619 | g2
620 | (g3
621 | (I0
622 | tp256
623 | g5
624 | tp257
625 | Rp258
626 | (I1
627 | (L4L
628 | tp259
629 | g12
630 | I00
631 | S'\xe7\xfb\xa9\xf1\xd2\x9e\x84@q=\n\xd7\xa3\xe0c@\x85\xebQ\xb8\x1e\xca\x89@\x9c\xc4 \xb0r\x90t@'
632 | p260
633 | tp261
634 | bsS'indoor_253.png'
635 | p262
636 | g2
637 | (g3
638 | (I0
639 | tp263
640 | g5
641 | tp264
642 | Rp265
643 | (I1
644 | (L4L
645 | tp266
646 | g12
647 | I00
648 | S'\xa8\xc6K7\x89\xd7x@fffff\xcal@F\xb6\xf3\xfd\xd4\xa7\x8b@L7\x89A` \x85@'
649 | p267
650 | tp268
651 | bsS'indoor_250.png'
652 | p269
653 | g2
654 | (g3
655 | (I0
656 | tp270
657 | g5
658 | tp271
659 | Rp272
660 | (I1
661 | (L4L
662 | tp273
663 | g12
664 | I00
665 | S'9\xb4\xc8v\xbe\xe5}@\xfc\xa9\xf1\xd2Mvf@B`\xe5\xd0"\x8b\x83@H\xe1z\x14\xaekt@'
666 | p274
667 | tp275
668 | bsS'indoor_189.png'
669 | p276
670 | g2
671 | (g3
672 | (I0
673 | tp277
674 | g5
675 | tp278
676 | Rp279
677 | (I1
678 | (L4L
679 | tp280
680 | g12
681 | I00
682 | S'T\xe3\xa5\x9b\xc4t\x8e@\x93\x18\x04V\x0e\xb9\x8a@\xf4\xfd\xd4xi\xf7\x93@\xf6(\\\x8f\xc2a\x91@'
683 | p281
684 | tp282
685 | bsS'indoor_177.png'
686 | p283
687 | g2
688 | (g3
689 | (I0
690 | tp284
691 | g5
692 | tp285
693 | Rp286
694 | (I1
695 | (L4L
696 | tp287
697 | g12
698 | I00
699 | S'\x00\x00\x00\x00\x00\x94\x82@\x00\x00\x00\x00\x00\xa8\x7f@\x00\x00\x00\x00\x00\xb4\x85@\x00\x00\x00\x00\x00\xf4\x83@'
700 | p288
701 | tp289
702 | bsS'indoor_165.png'
703 | p290
704 | g2
705 | (g3
706 | (I0
707 | tp291
708 | g5
709 | tp292
710 | Rp293
711 | (I1
712 | (L4L
713 | tp294
714 | g12
715 | I00
716 | S'\xa2E\xb6\xf3\xfd\xd8}@b\x10X9\xb4\x96\x7f@+\x87\x16\xd9\xceR\x86@\x89A`\xe5\xd0\xd8\x87@'
717 | p295
718 | tp296
719 | bsS'indoor_042.png'
720 | p297
721 | g2
722 | (g3
723 | (I0
724 | tp298
725 | g5
726 | tp299
727 | Rp300
728 | (I1
729 | (L4L
730 | tp301
731 | g12
732 | I00
733 | S'?5^\xbaI\x9a\x90@\xf4\xfd\xd4x\xe9*`@\xfc\xa9\xf1\xd2Mi\x94@m\xe7\xfb\xa9\xf1\xb4t@'
734 | p302
735 | tp303
736 | bsS'indoor_233.png'
737 | p304
738 | g2
739 | (g3
740 | (I0
741 | tp305
742 | g5
743 | tp306
744 | Rp307
745 | (I1
746 | (L4L
747 | tp308
748 | g12
749 | I00
750 | S'\xcd\xcc\xcc\xcc\xcc\x14n@!\xb0rh\x91\xddb@;\xdfO\x8d\x97\xe2}@\x14\xaeG\xe1z\xfat@'
751 | p309
752 | tp310
753 | bsS'indoor_026.png'
754 | p311
755 | g2
756 | (g3
757 | (I0
758 | tp312
759 | g5
760 | tp313
761 | Rp314
762 | (I1
763 | (L4L
764 | tp315
765 | g12
766 | I00
767 | S'\x00\x00\x00\x00\x00\xa4\x86@\x00\x00\x00\x00\x00\x90c@\x00\x00\x00\x00\x00\xe4\x8f@\x00\x00\x00\x00\x00\xc8|@'
768 | p316
769 | tp317
770 | bsS'indoor_016.png'
771 | p318
772 | g2
773 | (g3
774 | (I0
775 | tp319
776 | g5
777 | tp320
778 | Rp321
779 | (I1
780 | (L4L
781 | tp322
782 | g12
783 | I00
784 | S'\xe3\xa5\x9b\xc4 \x12|@\xf8S\xe3\xa5\x9b^\x7f@Zd;\xdfO@\x89@o\x12\x83\xc0\xca\x8c\x8c@'
785 | p323
786 | tp324
787 | bsS'indoor_137.png'
788 | p325
789 | g2
790 | (g3
791 | (I0
792 | tp326
793 | g5
794 | tp327
795 | Rp328
796 | (I1
797 | (L4L
798 | tp329
799 | g12
800 | I00
801 | S'\xbaI\x0c\x02k\xff\xa2@\xf4\xfd\xd4x\xe9\xba\x8a@\x87\x16\xd9\xce\xf77\xa6@\xdd$\x06\x81\x15\x83\x95@'
802 | p330
803 | tp331
804 | bsS'indoor_136.png'
805 | p332
806 | g2
807 | (g3
808 | (I0
809 | tp333
810 | g5
811 | tp334
812 | Rp335
813 | (I1
814 | (L4L
815 | tp336
816 | g12
817 | I00
818 | S"'1\x08\xac\x9c\x85\xa9@\xe9&1\x08\xacn\x86@\xecQ\xb8\x1e\xc58\xad@L7\x89A`[\x94@"
819 | p337
820 | tp338
821 | bsS'indoor_232.png'
822 | p339
823 | g2
824 | (g3
825 | (I0
826 | tp340
827 | g5
828 | tp341
829 | Rp342
830 | (I1
831 | (L4L
832 | tp343
833 | g12
834 | I00
835 | S'\xb0rh\x91\xed\xe1\x80@\xdfO\x8d\x97n\xd6o@\xa8\xc6K7\x89\x10\x88@#\xdb\xf9~jH~@'
836 | p344
837 | tp345
838 | bsS'indoor_241.png'
839 | p346
840 | g2
841 | (g3
842 | (I0
843 | tp347
844 | g5
845 | tp348
846 | Rp349
847 | (I1
848 | (L4L
849 | tp350
850 | g12
851 | I00
852 | S'\xe7\xfb\xa9\xf1\xd2\x0fu@o\x12\x83\xc0\xca\xc9r@\xecQ\xb8\x1e\x85\x8a\x81@\x00\x00\x00\x00\x007\x80@'
853 | p351
854 | tp352
855 | bsS'indoor_235.png'
856 | p353
857 | g2
858 | (g3
859 | (I0
860 | tp354
861 | g5
862 | tp355
863 | Rp356
864 | (I1
865 | (L4L
866 | tp357
867 | g12
868 | I00
869 | S'L7\x89A`\xa9x@%\x06\x81\x95C\x15q@{\x14\xaeG\xe1t\x88@\x89A`\xe5\xd0\xaa\x84@'
870 | p358
871 | tp359
872 | bsS'indoor_285.png'
873 | p360
874 | g2
875 | (g3
876 | (I0
877 | tp361
878 | g5
879 | tp362
880 | Rp363
881 | (I1
882 | (L4L
883 | tp364
884 | g12
885 | I00
886 | S'\x00\x00\x00\x00\x00P`@\x00\x00\x00\x00\x00\x80>@\x00\x00\x00\x00\x00Pi@\x00\x00\x00\x00\x00\xa0f@'
887 | p365
888 | tp366
889 | bsS'indoor_180.png'
890 | p367
891 | g2
892 | (g3
893 | (I0
894 | tp368
895 | g5
896 | tp369
897 | Rp370
898 | (I1
899 | (L4L
900 | tp371
901 | g12
902 | I00
903 | S'\x81\x95C\x8b,\x90\xa7@j\xbct\x93\x18\x19\x96@\x8f\xc2\xf5(\x1c$\xa9@w\xbe\x9f\x1a\xaf;\x9a@'
904 | p372
905 | tp373
906 | bsS'indoor_202.png'
907 | p374
908 | g2
909 | (g3
910 | (I0
911 | tp375
912 | g5
913 | tp376
914 | Rp377
915 | (I1
916 | (L4L
917 | tp378
918 | g12
919 | I00
920 | S'\x81\x95C\x8blL\x8b@\xc7K7\x89A\xae\x90@o\x12\x83\xc0\xca\xc3\x92@\xd3Mb\x10X]\x96@'
921 | p379
922 | tp380
923 | bsS'indoor_183.png'
924 | p381
925 | g2
926 | (g3
927 | (I0
928 | tp382
929 | g5
930 | tp383
931 | Rp384
932 | (I1
933 | (L4L
934 | tp385
935 | g12
936 | I00
937 | S';\xdfO\x8d\xd7\xda\xa3@X9\xb4\xc8vs\x8d@\xc9v\xbe\x9fZ9\xa6@5^\xbaI\x8c.\x94@'
938 | p386
939 | tp387
940 | bsS'indoor_157.png'
941 | p388
942 | g2
943 | (g3
944 | (I0
945 | tp389
946 | g5
947 | tp390
948 | Rp391
949 | (I1
950 | (L4L
951 | tp392
952 | g12
953 | I00
954 | S'\x19\x04V\x0e-*d@V\x0e-\xb2\x9dA\x83@;\xdfO\x8d\x97\xb2r@\xe3\xa5\x9b\xc4 \xb5\x87@'
955 | p393
956 | tp394
957 | bsS'indoor_238.png'
958 | p395
959 | g2
960 | (g3
961 | (I0
962 | tp396
963 | g5
964 | tp397
965 | Rp398
966 | (I1
967 | (L4L
968 | tp399
969 | g12
970 | I00
971 | S'\xf4\xfd\xd4x\xe9\xdac@\xe9&1\x08\xac\\E@9\xb4\xc8v\xbe\x18\x88@\x85\xebQ\xb8\x1e\x0e\x8c@'
972 | p400
973 | tp401
974 | bsS'indoor_169.png'
975 | p402
976 | g2
977 | (g3
978 | (I0
979 | tp403
980 | g5
981 | tp404
982 | Rp405
983 | (I1
984 | (L4L
985 | tp406
986 | g12
987 | I00
988 | S'\xaa\xf1\xd2Mb\x9cg@\xf6(\\\x8f\xc2\x91u@?5^\xbaI\xc2~@\x8d\x97n\x12\x83\xb2\x85@'
989 | p407
990 | tp408
991 | bsS'indoor_031.png'
992 | p409
993 | g2
994 | (g3
995 | (I0
996 | tp410
997 | g5
998 | tp411
999 | Rp412
1000 | (I1
1001 | (L4L
1002 | tp413
1003 | g12
1004 | I00
1005 | S'J\x0c\x02+\x87ny@\xe1z\x14\xaeGy^@\xbe\x9f\x1a/\xdd\xeb\x88@\xa2E\xb6\xf3\xfd\xa9\x81@'
1006 | p414
1007 | tp415
1008 | bsS'indoor_195.png'
1009 | p416
1010 | g2
1011 | (g3
1012 | (I0
1013 | tp417
1014 | g5
1015 | tp418
1016 | Rp419
1017 | (I1
1018 | (L4L
1019 | tp420
1020 | g12
1021 | I00
1022 | S'\x7fj\xbct\xd3\x89\xaa@\xe7\xfb\xa9\xf1\xd2\xc6\x8e@\xcb\xa1E\xb6\xf3\xbb\xab@\xc3\xf5(\\\x8fp\x92@'
1023 | p421
1024 | tp422
1025 | bsS'indoor_078.png'
1026 | p423
1027 | g2
1028 | (g3
1029 | (I0
1030 | tp424
1031 | g5
1032 | tp425
1033 | Rp426
1034 | (I1
1035 | (L4L
1036 | tp427
1037 | g12
1038 | I00
1039 | S'\x00\x00\x00\x00\x00\x80<@\x00\x00\x00\x00\x00\x90`@\x00\x00\x00\x00\x00\x90k@\x00\x00\x00\x00\x00\xd0u@'
1040 | p428
1041 | tp429
1042 | bsS'indoor_079.png'
1043 | p430
1044 | g2
1045 | (g3
1046 | (I0
1047 | tp431
1048 | g5
1049 | tp432
1050 | Rp433
1051 | (I1
1052 | (L4L
1053 | tp434
1054 | g12
1055 | I00
1056 | S'\x00\x00\x00\x00\x00\x90o@\x00\x00\x00\x00\x00 W@\x00\x00\x00\x00\x00(~@\x00\x00\x00\x00\x00\x10v@'
1057 | p435
1058 | tp436
1059 | bsS'indoor_050.png'
1060 | p437
1061 | g2
1062 | (g3
1063 | (I0
1064 | tp438
1065 | g5
1066 | tp439
1067 | Rp440
1068 | (I1
1069 | (L4L
1070 | tp441
1071 | g12
1072 | I00
1073 | S'\xcf\xf7S\xe3\xa5\xd4\x83@\xcb\xa1E\xb6\xf3\xff\x88@\x8f\xc2\xf5(\xdc\x1a\x93@\xc3\xf5(\\\x0f\x8d\x96@'
1074 | p442
1075 | tp443
1076 | bsS'indoor_027.png'
1077 | p444
1078 | g2
1079 | (g3
1080 | (I0
1081 | tp445
1082 | g5
1083 | tp446
1084 | Rp447
1085 | (I1
1086 | (L4L
1087 | tp448
1088 | g12
1089 | I00
1090 | S'\x00\x00\x00\x00\x00d\x80@\x00\x00\x00\x00\x00\x90k@\x00\x00\x00\x00\x00d\x89@\x00\x00\x00\x00\x00\xc8\x7f@'
1091 | p449
1092 | tp450
1093 | bsS'indoor_120.png'
1094 | p451
1095 | g2
1096 | (g3
1097 | (I0
1098 | tp452
1099 | g5
1100 | tp453
1101 | Rp454
1102 | (I1
1103 | (L4L
1104 | tp455
1105 | g12
1106 | I00
1107 | S'\x85\xebQ\xb8\x1e,\x88@\x08\xac\x1cZdsi@\xc1\xca\xa1E\xb6\x0b\x8e@R\xb8\x1e\x85\xeb\x1f{@'
1108 | p456
1109 | tp457
1110 | bsS'indoor_024.png'
1111 | p458
1112 | g2
1113 | (g3
1114 | (I0
1115 | tp459
1116 | g5
1117 | tp460
1118 | Rp461
1119 | (I1
1120 | (L4L
1121 | tp462
1122 | g12
1123 | I00
1124 | S'{\x14\xaeG\xe1\xeaS@\xe5\xd0"\xdb\xf9\xcai@\xe3\xa5\x9b\xc4 \x12|@\xa2E\xb6\xf3\xfd\xa9\x81@'
1125 | p463
1126 | tp464
1127 | bsS'indoor_134.png'
1128 | p465
1129 | g2
1130 | (g3
1131 | (I0
1132 | tp466
1133 | g5
1134 | tp467
1135 | Rp468
1136 | (I1
1137 | (L4L
1138 | tp469
1139 | g12
1140 | I00
1141 | S'\x00\x00\x00\x00\x00h~@\x00\x00\x00\x00\x00(q@\x00\x00\x00\x00\x00\x94\x83@\x00\x00\x00\x00\x00\xa8z@'
1142 | p470
1143 | tp471
1144 | bsS'indoor_237.png'
1145 | p472
1146 | g2
1147 | (g3
1148 | (I0
1149 | tp473
1150 | g5
1151 | tp474
1152 | Rp475
1153 | (I1
1154 | (L4L
1155 | tp476
1156 | g12
1157 | I00
1158 | S'd;\xdfO\x8d\x1fr@\xecQ\xb8\x1e\x85{j@\xbct\x93\x18\x04*z@%\x06\x81\x95C\xdbu@'
1159 | p477
1160 | tp478
1161 | bsS'indoor_218.png'
1162 | p479
1163 | g2
1164 | (g3
1165 | (I0
1166 | tp480
1167 | g5
1168 | tp481
1169 | Rp482
1170 | (I1
1171 | (L4L
1172 | tp483
1173 | g12
1174 | I00
1175 | S'\x00\x00\x00\x00\x00\xe8q@\x00\x00\x00\x00\x00Pb@\x00\x00\x00\x00\x00hz@\x00\x00\x00\x00\x00(r@'
1176 | p484
1177 | tp485
1178 | bsS'indoor_129.png'
1179 | p486
1180 | g2
1181 | (g3
1182 | (I0
1183 | tp487
1184 | g5
1185 | tp488
1186 | Rp489
1187 | (I1
1188 | (L4L
1189 | tp490
1190 | g12
1191 | I00
1192 | S'\xaa\xf1\xd2Mb\xaav@-\xb2\x9d\xef\xa7\xect@=\n\xd7\xa3\xf0(\x93@\x1dZd;_\x98\x93@'
1193 | p491
1194 | tp492
1195 | bsS'indoor_038.png'
1196 | p493
1197 | g2
1198 | (g3
1199 | (I0
1200 | tp494
1201 | g5
1202 | tp495
1203 | Rp496
1204 | (I1
1205 | (L4L
1206 | tp497
1207 | g12
1208 | I00
1209 | S'\x00\x00\x00\x00\x00Pj@\x00\x00\x00\x00\x00\xd0a@\x00\x00\x00\x00\x00\xe8t@\x00\x00\x00\x00\x00(p@'
1210 | p498
1211 | tp499
1212 | bsS'indoor_108.png'
1213 | p500
1214 | g2
1215 | (g3
1216 | (I0
1217 | tp501
1218 | g5
1219 | tp502
1220 | Rp503
1221 | (I1
1222 | (L4L
1223 | tp504
1224 | g12
1225 | I00
1226 | S'\x91\xed|?u\x18\xa3@=\n\xd7\xa3p\xfe\x81@\xaeG\xe1z\xd4O\xa6@h\x91\xed|?\xe1\x8c@'
1227 | p505
1228 | tp506
1229 | bsS'indoor_216.png'
1230 | p507
1231 | g2
1232 | (g3
1233 | (I0
1234 | tp508
1235 | g5
1236 | tp509
1237 | Rp510
1238 | (I1
1239 | (L4L
1240 | tp511
1241 | g12
1242 | I00
1243 | S'\\\x8f\xc2\xf5\xa8\xa0\x9a@T\xe3\xa5\x9b\xc4A\x81@B`\xe5\xd0\xa2\xd1\xa0@\x87\x16\xd9\xce\xf7#\x8e@'
1244 | p512
1245 | tp513
1246 | bsS'indoor_071.png'
1247 | p514
1248 | g2
1249 | (g3
1250 | (I0
1251 | tp515
1252 | g5
1253 | tp516
1254 | Rp517
1255 | (I1
1256 | (L4L
1257 | tp518
1258 | g12
1259 | I00
1260 | S'?5^\xbaI\xec@@\xdfO\x8d\x97n*\\@\xfa~j\xbct\xffm@+\x87\x16\xd9\xce\x8bs@'
1261 | p519
1262 | tp520
1263 | bsS'indoor_045.png'
1264 | p521
1265 | g2
1266 | (g3
1267 | (I0
1268 | tp522
1269 | g5
1270 | tp523
1271 | Rp524
1272 | (I1
1273 | (L4L
1274 | tp525
1275 | g12
1276 | I00
1277 | S'\x00\x00\x00\x00\x00@G@\x00\x00\x00\x00\x00@O@\x00\x00\x00\x00\x00Pd@\x00\x00\x00\x00\x00\xd0g@'
1278 | p526
1279 | tp527
1280 | bsS'indoor_093.png'
1281 | p528
1282 | g2
1283 | (g3
1284 | (I0
1285 | tp529
1286 | g5
1287 | tp530
1288 | Rp531
1289 | (I1
1290 | (L4L
1291 | tp532
1292 | g12
1293 | I00
1294 | S'\xe1z\x14\xaeG\x99r@\x83\xc0\xca\xa1E~a@\x89A`\xe5\xd0\xaa\x84@\xb4\xc8v\xbe\x9f\xa9\x80@'
1295 | p533
1296 | tp534
1297 | bsS'indoor_227.png'
1298 | p535
1299 | g2
1300 | (g3
1301 | (I0
1302 | tp536
1303 | g5
1304 | tp537
1305 | Rp538
1306 | (I1
1307 | (L4L
1308 | tp539
1309 | g12
1310 | I00
1311 | S'Nb\x10X9\x9d\x8e@\xa0\x1a/\xdd$d\x91@\xe9&1\x08,I\x93@\xd5x\xe9&1l\x94@'
1312 | p540
1313 | tp541
1314 | bsS'indoor_176.png'
1315 | p542
1316 | g2
1317 | (g3
1318 | (I0
1319 | tp543
1320 | g5
1321 | tp544
1322 | Rp545
1323 | (I1
1324 | (L4L
1325 | tp546
1326 | g12
1327 | I00
1328 | S'\x00\x00\x00\x00\x00\x84\x8c@\x00\x00\x00\x00\x00Hr@\x00\x00\x00\x00\x00D\x8f@\x00\x00\x00\x00\x00Hx@'
1329 | p547
1330 | tp548
1331 | bsS'indoor_096.png'
1332 | p549
1333 | g2
1334 | (g3
1335 | (I0
1336 | tp550
1337 | g5
1338 | tp551
1339 | Rp552
1340 | (I1
1341 | (L4L
1342 | tp553
1343 | g12
1344 | I00
1345 | S'\xee|?5^"Y@\xee|?5^"Y@\xcd\xcc\xcc\xcc\xcc\xecs@\xfe\xd4x\xe9&\xc9s@'
1346 | p554
1347 | tp555
1348 | bsS'indoor_097.png'
1349 | p556
1350 | g2
1351 | (g3
1352 | (I0
1353 | tp557
1354 | g5
1355 | tp558
1356 | Rp559
1357 | (I1
1358 | (L4L
1359 | tp560
1360 | g12
1361 | I00
1362 | S'd;\xdfO\x8d\xdfh@o\x12\x83\xc0\xca\ta@\xa8\xc6K7\x89]z@\xf6(\\\x8f\xc2\xa1v@'
1363 | p561
1364 | tp562
1365 | bsS'indoor_037.png'
1366 | p563
1367 | g2
1368 | (g3
1369 | (I0
1370 | tp564
1371 | g5
1372 | tp565
1373 | Rp566
1374 | (I1
1375 | (L4L
1376 | tp567
1377 | g12
1378 | I00
1379 | S'\x00\x00\x00\x00\x00$\x87@\x00\x00\x00\x00\x00\x90i@\x00\x00\x00\x00\x00\xd2\x90@\x00\x00\x00\x00\x00\xc8}@'
1380 | p568
1381 | tp569
1382 | bsS'indoor_013.png'
1383 | p570
1384 | g2
1385 | (g3
1386 | (I0
1387 | tp571
1388 | g5
1389 | tp572
1390 | Rp573
1391 | (I1
1392 | (L4L
1393 | tp574
1394 | g12
1395 | I00
1396 | S'\x00\x00\x00\x00\x00b\x9f@\x00\x00\x00\x00\x00\xa2\x91@\x00\x00\x00\x00\x00\xf1\xa3@\x00\x00\x00\x00\x00\xe2\x99@'
1397 | p575
1398 | tp576
1399 | bsS'indoor_147.png'
1400 | p577
1401 | g2
1402 | (g3
1403 | (I0
1404 | tp578
1405 | g5
1406 | tp579
1407 | Rp580
1408 | (I1
1409 | (L4L
1410 | tp581
1411 | g12
1412 | I00
1413 | S'B`\xe5\xd0\xe2\xe9\xa0@\xbe\x9f\x1a/\xddQ\x87@w\xbe\x9f\x1a/\n\xa4@J\x0c\x02+\x07\x1a\x92@'
1414 | p582
1415 | tp583
1416 | bsS'indoor_005.png'
1417 | p584
1418 | g2
1419 | (g3
1420 | (I0
1421 | tp585
1422 | g5
1423 | tp586
1424 | Rp587
1425 | (I1
1426 | (L4L
1427 | tp588
1428 | g12
1429 | I00
1430 | S'\xfc\xa9\xf1\xd2Mvf@\x81\x95C\x8bl?X@Nb\x10X9\x9c}@\xbct\x93\x18\x04*z@'
1431 | p589
1432 | tp590
1433 | bsS'indoor_021.png'
1434 | p591
1435 | g2
1436 | (g3
1437 | (I0
1438 | tp592
1439 | g5
1440 | tp593
1441 | Rp594
1442 | (I1
1443 | (L4L
1444 | tp595
1445 | g12
1446 | I00
1447 | S'Nb\x10X9\x9c}@\x19\x04V\x0e-*d@\xd5x\xe9&1\xdb\x88@\n\xd7\xa3p=\x1a\x81@'
1448 | p596
1449 | tp597
1450 | bsS'indoor_020.png'
1451 | p598
1452 | g2
1453 | (g3
1454 | (I0
1455 | tp599
1456 | g5
1457 | tp600
1458 | Rp601
1459 | (I1
1460 | (L4L
1461 | tp602
1462 | g12
1463 | I00
1464 | S'\x00\x00\x00\x00\x00@L@\x00\x00\x00\x00\x00\x10k@\x00\x00\x00\x00\x00D\x81@\x00\x00\x00\x00\x00D\x86@'
1465 | p603
1466 | tp604
1467 | bsS'indoor_282.png'
1468 | p605
1469 | g2
1470 | (g3
1471 | (I0
1472 | tp606
1473 | g5
1474 | tp607
1475 | Rp608
1476 | (I1
1477 | (L4L
1478 | tp609
1479 | g12
1480 | I00
1481 | S'\xdd$\x06\x81\x95M\x84@Nb\x10X9\xe0a@\xe1z\x14\xaeG\xd9\x8f@R\xb8\x1e\x85\xebc}@'
1482 | p610
1483 | tp611
1484 | bsS'indoor_295.png'
1485 | p612
1486 | g2
1487 | (g3
1488 | (I0
1489 | tp613
1490 | g5
1491 | tp614
1492 | Rp615
1493 | (I1
1494 | (L4L
1495 | tp616
1496 | g12
1497 | I00
1498 | S'\x00\x00\x00\x00\x00\xa8w@\x00\x00\x00\x00\x00Pf@\x00\x00\x00\x00\x00(\x7f@\x00\x00\x00\x00\x00(t@'
1499 | p617
1500 | tp618
1501 | bsS'indoor_228.png'
1502 | p619
1503 | g2
1504 | (g3
1505 | (I0
1506 | tp620
1507 | g5
1508 | tp621
1509 | Rp622
1510 | (I1
1511 | (L4L
1512 | tp623
1513 | g12
1514 | I00
1515 | S'\x00\x00\x00\x00\x00\x84\x80@\x00\x00\x00\x00\x00\x90f@\x00\x00\x00\x00\x00d\x83@\x00\x00\x00\x00\x00\xc8p@'
1516 | p624
1517 | tp625
1518 | bsS'indoor_039.png'
1519 | p626
1520 | g2
1521 | (g3
1522 | (I0
1523 | tp627
1524 | g5
1525 | tp628
1526 | Rp629
1527 | (I1
1528 | (L4L
1529 | tp630
1530 | g12
1531 | I00
1532 | S'\xa0\x1a/\xdd$~l@;\xdfO\x8d\x97\x1e[@H\xe1z\x14\xae\x95x@\xf6(\\\x8f\xc2gq@'
1533 | p631
1534 | tp632
1535 | bsS'indoor_198.png'
1536 | p633
1537 | g2
1538 | (g3
1539 | (I0
1540 | tp634
1541 | g5
1542 | tp635
1543 | Rp636
1544 | (I1
1545 | (L4L
1546 | tp637
1547 | g12
1548 | I00
1549 | S'\x00\x00\x00\x00\x00h\x7f@\x00\x00\x00\x00\x00Pl@\x00\x00\x00\x00\x00\xd4\x84@\x00\x00\x00\x00\x00\xe8w@'
1550 | p638
1551 | tp639
1552 | bsS'indoor_049.png'
1553 | p640
1554 | g2
1555 | (g3
1556 | (I0
1557 | tp641
1558 | g5
1559 | tp642
1560 | Rp643
1561 | (I1
1562 | (L4L
1563 | tp644
1564 | g12
1565 | I00
1566 | S'Nb\x10X9Pe@\x8bl\xe7\xfb\xa9\xd1K@j\xbct\x93\x18\xfcr@\xc3\xf5(\\\x8f\x0ek@'
1567 | p645
1568 | tp646
1569 | bsS'indoor_065.png'
1570 | p647
1571 | g2
1572 | (g3
1573 | (I0
1574 | tp648
1575 | g5
1576 | tp649
1577 | Rp650
1578 | (I1
1579 | (L4L
1580 | tp651
1581 | g12
1582 | I00
1583 | S'\x00\x00\x00\x00\x00\x90a@\x00\x00\x00\x00\x00\x90f@\x00\x00\x00\x00\x00\xc8z@\x00\x00\x00\x00\x00H|@'
1584 | p652
1585 | tp653
1586 | bsS'indoor_073.png'
1587 | p654
1588 | g2
1589 | (g3
1590 | (I0
1591 | tp655
1592 | g5
1593 | tp656
1594 | Rp657
1595 | (I1
1596 | (L4L
1597 | tp658
1598 | g12
1599 | I00
1600 | S'\xee|?5^\xa6c@b\x10X9\xb4\x18n@\xe5\xd0"\xdb\xf9\xccz@\xe1z\x14\xaeG\'\x7f@'
1601 | p659
1602 | tp660
1603 | bsS'indoor_257.png'
1604 | p661
1605 | g2
1606 | (g3
1607 | (I0
1608 | tp662
1609 | g5
1610 | tp663
1611 | Rp664
1612 | (I1
1613 | (L4L
1614 | tp665
1615 | g12
1616 | I00
1617 | S'j\xbct\x93\x18\x04c@\x81\x95C\x8bl?X@\\\x8f\xc2\xf5(v|@\\\x8f\xc2\xf5(v|@'
1618 | p666
1619 | tp667
1620 | bsS'indoor_224.png'
1621 | p668
1622 | g2
1623 | (g3
1624 | (I0
1625 | tp669
1626 | g5
1627 | tp670
1628 | Rp671
1629 | (I1
1630 | (L4L
1631 | tp672
1632 | g12
1633 | I00
1634 | S'\x00\x00\x00\x00\x00\x14\x80@\x00\x00\x00\x00\x00Pc@\x00\x00\x00\x00\x00\xf4\x82@\x00\x00\x00\x00\x00hp@'
1635 | p673
1636 | tp674
1637 | bsS'indoor_091.png'
1638 | p675
1639 | g2
1640 | (g3
1641 | (I0
1642 | tp676
1643 | g5
1644 | tp677
1645 | Rp678
1646 | (I1
1647 | (L4L
1648 | tp679
1649 | g12
1650 | I00
1651 | S'\xee|?5^\x8eg@\x9c\xc4 \xb0rh[@\x17\xd9\xce\xf7S\xa1u@\x17\xd9\xce\xf7S\xa1u@'
1652 | p680
1653 | tp681
1654 | bsS'indoor_148.png'
1655 | p682
1656 | g2
1657 | (g3
1658 | (I0
1659 | tp683
1660 | g5
1661 | tp684
1662 | Rp685
1663 | (I1
1664 | (L4L
1665 | tp686
1666 | g12
1667 | I00
1668 | S'j\xbct\x93\x98u\x96@\x96C\x8bl\xe7Y\x8a@b\x10X9\xb4G\x9d@\x7fj\xbct\x13"\x95@'
1669 | p687
1670 | tp688
1671 | bsS'indoor_149.png'
1672 | p689
1673 | g2
1674 | (g3
1675 | (I0
1676 | tp690
1677 | g5
1678 | tp691
1679 | Rp692
1680 | (I1
1681 | (L4L
1682 | tp693
1683 | g12
1684 | I00
1685 | S'\x93\x18\x04V\x0e\xc5j@\x19\x04V\x0e-\t\x82@y\xe9&1\x08\x00v@\xc5 \xb0rh\x0e\x86@'
1686 | p694
1687 | tp695
1688 | bsS'indoor_160.png'
1689 | p696
1690 | g2
1691 | (g3
1692 | (I0
1693 | tp697
1694 | g5
1695 | tp698
1696 | Rp699
1697 | (I1
1698 | (L4L
1699 | tp700
1700 | g12
1701 | I00
1702 | S'+\x87\x16\xd9\xceJ\x8d@o\x12\x83\xc0\xca\xffr@\x17\xd9\xce\xf7S\x88\x91@\xa0\x1a/\xdd$\x8e}@'
1703 | p701
1704 | tp702
1705 | bsS'indoor_095.png'
1706 | p703
1707 | g2
1708 | (g3
1709 | (I0
1710 | tp704
1711 | g5
1712 | tp705
1713 | Rp706
1714 | (I1
1715 | (L4L
1716 | tp707
1717 | g12
1718 | I00
1719 | S'\x00\x00\x00\x00\x00\x88}@\x00\x00\x00\x00\x00\x88{@\x00\x00\x00\x00\x00D\x8f@\x00\x00\x00\x00\x00\xc4\x8e@'
1720 | p708
1721 | tp709
1722 | bsS'indoor_012.png'
1723 | p710
1724 | g2
1725 | (g3
1726 | (I0
1727 | tp711
1728 | g5
1729 | tp712
1730 | Rp713
1731 | (I1
1732 | (L4L
1733 | tp714
1734 | g12
1735 | I00
1736 | S'\x1f\x85\xebQ\xb8\xfet@\x81\x95C\x8bl?X@\x14\xaeG\xe1z\x1f\x85@\xa2E\xb6\xf3\xfd\x96y@'
1737 | p715
1738 | tp716
1739 | bsS'indoor_236.png'
1740 | p717
1741 | g2
1742 | (g3
1743 | (I0
1744 | tp718
1745 | g5
1746 | tp719
1747 | Rp720
1748 | (I1
1749 | (L4L
1750 | tp721
1751 | g12
1752 | I00
1753 | S'\xc7K7\x89A\xbc`@\xc7K7\x89APR@\xfc\xa9\xf1\xd2M\xbcs@h\x91\xed|?Sp@'
1754 | p722
1755 | tp723
1756 | bsS'indoor_270.png'
1757 | p724
1758 | g2
1759 | (g3
1760 | (I0
1761 | tp725
1762 | g5
1763 | tp726
1764 | Rp727
1765 | (I1
1766 | (L4L
1767 | tp728
1768 | g12
1769 | I00
1770 | S'\x00\x00\x00\x00\x00\xd0f@\x00\x00\x00\x00\x00@M@\x00\x00\x00\x00\x00(t@\x00\x00\x00\x00\x00\xd0i@'
1771 | p729
1772 | tp730
1773 | bsS'indoor_011.png'
1774 | p731
1775 | g2
1776 | (g3
1777 | (I0
1778 | tp732
1779 | g5
1780 | tp733
1781 | Rp734
1782 | (I1
1783 | (L4L
1784 | tp735
1785 | g12
1786 | I00
1787 | S'^\xbaI\x0c\x02\xc3l@\xdb\xf9~j\xbc$h@\x8bl\xe7\xfb\xa9Az@\xf2\xd2Mb\x10\x9ew@'
1788 | p736
1789 | tp737
1790 | bsS'indoor_264.png'
1791 | p738
1792 | g2
1793 | (g3
1794 | (I0
1795 | tp739
1796 | g5
1797 | tp740
1798 | Rp741
1799 | (I1
1800 | (L4L
1801 | tp742
1802 | g12
1803 | I00
1804 | S'\xe9&1\x08\xacrv@+\x87\x16\xd9\xce\x93u@\xaeG\xe1z\x14\x0f\x83@\xaeG\xe1z\x14\x0f\x83@'
1805 | p743
1806 | tp744
1807 | bsS'indoor_171.png'
1808 | p745
1809 | g2
1810 | (g3
1811 | (I0
1812 | tp746
1813 | g5
1814 | tp747
1815 | Rp748
1816 | (I1
1817 | (L4L
1818 | tp749
1819 | g12
1820 | I00
1821 | S'\x85\xebQ\xb8\x9e\x0c\x9b@\xe9&1\x08\xac\x00h@\xa2E\xb6\xf3}\xf7\x9e@\xa8\xc6K7\x89]z@'
1822 | p750
1823 | tp751
1824 | bsS'indoor_299.png'
1825 | p752
1826 | g2
1827 | (g3
1828 | (I0
1829 | tp753
1830 | g5
1831 | tp754
1832 | Rp755
1833 | (I1
1834 | (L4L
1835 | tp756
1836 | g12
1837 | I00
1838 | S'\x85\xebQ\xb8\x1e\xe3{@\xc3\xf5(\\\x8f\x0ek@j\xbct\x93\x18"\x87@}?5^\xba\xd0\x80@'
1839 | p757
1840 | tp758
1841 | bsS'indoor_252.png'
1842 | p759
1843 | g2
1844 | (g3
1845 | (I0
1846 | tp760
1847 | g5
1848 | tp761
1849 | Rp762
1850 | (I1
1851 | (L4L
1852 | tp763
1853 | g12
1854 | I00
1855 | S'\x00\x00\x00\x00\x00 U@\x00\x00\x00\x00\x00 P@\x00\x00\x00\x00\x00\x10g@\x00\x00\x00\x00\x00\x90d@'
1856 | p764
1857 | tp765
1858 | bsS'indoor_118.png'
1859 | p766
1860 | g2
1861 | (g3
1862 | (I0
1863 | tp767
1864 | g5
1865 | tp768
1866 | Rp769
1867 | (I1
1868 | (L4L
1869 | tp770
1870 | g12
1871 | I00
1872 | S'q=\n\xd7\xa3V\x80@\n\xd7\xa3p}3\xae@\xc1\xca\xa1E\xb6\x92\x8f@\xf0\xa7\xc6Kw\xd7\xb0@'
1873 | p771
1874 | tp772
1875 | bsS'indoor_144.png'
1876 | p773
1877 | g2
1878 | (g3
1879 | (I0
1880 | tp774
1881 | g5
1882 | tp775
1883 | Rp776
1884 | (I1
1885 | (L4L
1886 | tp777
1887 | g12
1888 | I00
1889 | S'`\xe5\xd0"\xdb*\x90@\xe9&1\x08\xac1\x87@-\xb2\x9d\xef\'\xc2\x93@\x02+\x87\x16\xd9v\x8f@'
1890 | p778
1891 | tp779
1892 | bsS'indoor_103.png'
1893 | p780
1894 | g2
1895 | (g3
1896 | (I0
1897 | tp781
1898 | g5
1899 | tp782
1900 | Rp783
1901 | (I1
1902 | (L4L
1903 | tp784
1904 | g12
1905 | I00
1906 | S'\x00\x00\x00\x00\x00\xf4\x8e@\x00\x00\x00\x00\x00hr@\x00\x00\x00\x00\x00Z\x91@\x00\x00\x00\x00\x00(z@'
1907 | p785
1908 | tp786
1909 | bsS'indoor_141.png'
1910 | p787
1911 | g2
1912 | (g3
1913 | (I0
1914 | tp788
1915 | g5
1916 | tp789
1917 | Rp790
1918 | (I1
1919 | (L4L
1920 | tp791
1921 | g12
1922 | I00
1923 | S'\xb8\x1e\x85\xebQ\xc4c@1\x08\xac\x1cZ\xc0\x86@h\x91\xed|?O\x80@\xf6(\\\x8f\xc2\xde\x90@'
1924 | p792
1925 | tp793
1926 | bsS'indoor_186.png'
1927 | p794
1928 | g2
1929 | (g3
1930 | (I0
1931 | tp795
1932 | g5
1933 | tp796
1934 | Rp797
1935 | (I1
1936 | (L4L
1937 | tp798
1938 | g12
1939 | I00
1940 | S'\x7fj\xbct\x93\xd8\x86@;\xdfO\x8d\x97\xbf\x8f@\x02+\x87\x16Y\xbc\x90@\xa4p=\nW\xe6\x94@'
1941 | p799
1942 | tp800
1943 | bsS'indoor_259.png'
1944 | p801
1945 | g2
1946 | (g3
1947 | (I0
1948 | tp802
1949 | g5
1950 | tp803
1951 | Rp804
1952 | (I1
1953 | (L4L
1954 | tp805
1955 | g12
1956 | I00
1957 | S'+\x87\x16\xd9\xce\x93u@fffff\xbei@\xee|?5^\xd7\x82@\xe3\xa5\x9b\xc4 \xfa|@'
1958 | p806
1959 | tp807
1960 | bsS'indoor_030.png'
1961 | p808
1962 | g2
1963 | (g3
1964 | (I0
1965 | tp809
1966 | g5
1967 | tp810
1968 | Rp811
1969 | (I1
1970 | (L4L
1971 | tp812
1972 | g12
1973 | I00
1974 | S'o\x12\x83\xc0\xca&\x83@Zd;\xdfO\x1dt@\xcb\xa1E\xb6\xf3a\x8d@\xbe\x9f\x1a/\xdd\xb2\x87@'
1975 | p813
1976 | tp814
1977 | bsS'indoor_080.png'
1978 | p815
1979 | g2
1980 | (g3
1981 | (I0
1982 | tp816
1983 | g5
1984 | tp817
1985 | Rp818
1986 | (I1
1987 | (L4L
1988 | tp819
1989 | g12
1990 | I00
1991 | S'\xe7\xfb\xa9\xf1\xd2%T@j\xbct\x93\x18de@\xecQ\xb8\x1e\x85Et@h\x91\xed|?\x0fy@'
1992 | p820
1993 | tp821
1994 | bsS'indoor_159.png'
1995 | p822
1996 | g2
1997 | (g3
1998 | (I0
1999 | tp823
2000 | g5
2001 | tp824
2002 | Rp825
2003 | (I1
2004 | (L4L
2005 | tp826
2006 | g12
2007 | I00
2008 | S'\x00\x00\x00\x00\x00\n\x98@\x00\x00\x00\x00\x00\xe8}@\x00\x00\x00\x00\x00\xda\x99@\x00\x00\x00\x00\x004\x82@'
2009 | p827
2010 | tp828
2011 | bsS'indoor_226.png'
2012 | p829
2013 | g2
2014 | (g3
2015 | (I0
2016 | tp830
2017 | g5
2018 | tp831
2019 | Rp832
2020 | (I1
2021 | (L4L
2022 | tp833
2023 | g12
2024 | I00
2025 | S'\xbaI\x0c\x02\xab&\x92@\x87\x16\xd9\xce\xf7B\x88@\xc7K7\x89A\xca\x94@R\xb8\x1e\x85\xeb_\x8d@'
2026 | p834
2027 | tp835
2028 | bsS'indoor_085.png'
2029 | p836
2030 | g2
2031 | (g3
2032 | (I0
2033 | tp837
2034 | g5
2035 | tp838
2036 | Rp839
2037 | (I1
2038 | (L4L
2039 | tp840
2040 | g12
2041 | I00
2042 | S'\x00\x00\x00\x00\x00(q@\x00\x00\x00\x00\x00\xa0]@\x00\x00\x00\x00\x00hx@\x00\x00\x00\x00\x00Po@'
2043 | p841
2044 | tp842
2045 | bsS'indoor_107.png'
2046 | p843
2047 | g2
2048 | (g3
2049 | (I0
2050 | tp844
2051 | g5
2052 | tp845
2053 | Rp846
2054 | (I1
2055 | (L4L
2056 | tp847
2057 | g12
2058 | I00
2059 | S'\x00\x00\x00\x00\x00\x10h@\x00\x00\x00\x00\x00\xc4\x89@\x00\x00\x00\x00\x00\x88{@\x00\x00\x00\x00\x00\x02\x91@'
2060 | p848
2061 | tp849
2062 | bsS'indoor_123.png'
2063 | p850
2064 | g2
2065 | (g3
2066 | (I0
2067 | tp851
2068 | g5
2069 | tp852
2070 | Rp853
2071 | (I1
2072 | (L4L
2073 | tp854
2074 | g12
2075 | I00
2076 | S'\x00\x00\x00\x00\x00d\x83@\x00\x00\x00\x00\x00\xa4\x82@\x00\x00\x00\x00\x00\xe4\x8c@\x00\x00\x00\x00\x00\xa4\x8b@'
2077 | p855
2078 | tp856
2079 | bsS'indoor_135.png'
2080 | p857
2081 | g2
2082 | (g3
2083 | (I0
2084 | tp858
2085 | g5
2086 | tp859
2087 | Rp860
2088 | (I1
2089 | (L4L
2090 | tp861
2091 | g12
2092 | I00
2093 | S'\x00\x00\x00\x00\x00 P@\x00\x00\x00\x00\x00\x08r@\x00\x00\x00\x00\x00\x90d@\x00\x00\x00\x00\x00\x08x@'
2094 | p862
2095 | tp863
2096 | bsS'indoor_247.png'
2097 | p864
2098 | g2
2099 | (g3
2100 | (I0
2101 | tp865
2102 | g5
2103 | tp866
2104 | Rp867
2105 | (I1
2106 | (L4L
2107 | tp868
2108 | g12
2109 | I00
2110 | S'\xa8\xc6K7\x89Z\x88@\xb0rh\x91\xedFt@\x8f\xc2\xf5(\\\xcf\x8d@\xe5\xd0"\xdb\xf9\xc0}@'
2111 | p869
2112 | tp870
2113 | bsS'indoor_111.png'
2114 | p871
2115 | g2
2116 | (g3
2117 | (I0
2118 | tp872
2119 | g5
2120 | tp873
2121 | Rp874
2122 | (I1
2123 | (L4L
2124 | tp875
2125 | g12
2126 | I00
2127 | S'q=\n\xd7\xa3(\x8c@w\xbe\x9f\x1a/\t}@\x0e-\xb2\x9d\xef\x16\x90@Zd;\xdfO@\x82@'
2128 | p876
2129 | tp877
2130 | bsS'indoor_110.png'
2131 | p878
2132 | g2
2133 | (g3
2134 | (I0
2135 | tp879
2136 | g5
2137 | tp880
2138 | Rp881
2139 | (I1
2140 | (L4L
2141 | tp882
2142 | g12
2143 | I00
2144 | S'\x00\x00\x00\x00\x00\x91\xab@\x00\x00\x00\x00\x00\xa2\x9b@\x00\x00\x00\x00\x00\xb1\xaf@\x00\x00\x00\x00\x001\xa3@'
2145 | p883
2146 | tp884
2147 | bsS'indoor_138.png'
2148 | p885
2149 | g2
2150 | (g3
2151 | (I0
2152 | tp886
2153 | g5
2154 | tp887
2155 | Rp888
2156 | (I1
2157 | (L4L
2158 | tp889
2159 | g12
2160 | I00
2161 | S'\xf8S\xe3\xa5\x1b%\x99@\x08\xac\x1cZd,\x88@\x10X9\xb4H\xe4\x9f@m\xe7\xfb\xa9\xf1\xeb\x93@'
2162 | p890
2163 | tp891
2164 | bsS'indoor_281.png'
2165 | p892
2166 | g2
2167 | (g3
2168 | (I0
2169 | tp893
2170 | g5
2171 | tp894
2172 | Rp895
2173 | (I1
2174 | (L4L
2175 | tp896
2176 | g12
2177 | I00
2178 | S'fffff\xbei@o\x12\x83\xc0\xca\ta@d;\xdfO\x8di}@\xa6\x9b\xc4 \xb0~y@'
2179 | p897
2180 | tp898
2181 | bsS'indoor_089.png'
2182 | p899
2183 | g2
2184 | (g3
2185 | (I0
2186 | tp900
2187 | g5
2188 | tp901
2189 | Rp902
2190 | (I1
2191 | (L4L
2192 | tp903
2193 | g12
2194 | I00
2195 | S'\x00\x00\x00\x00\x00\xd0h@\x00\x00\x00\x00\x00\xa0X@\x00\x00\x00\x00\x00\xe8r@\x00\x00\x00\x00\x00\xd0i@'
2196 | p904
2197 | tp905
2198 | bsS'indoor_062.png'
2199 | p906
2200 | g2
2201 | (g3
2202 | (I0
2203 | tp907
2204 | g5
2205 | tp908
2206 | Rp909
2207 | (I1
2208 | (L4L
2209 | tp910
2210 | g12
2211 | I00
2212 | S'\x00\x00\x00\x00\x00\xa8s@\x00\x00\x00\x00\x00P`@\x00\x00\x00\x00\x00\xe8z@\x00\x00\x00\x00\x00\xd0n@'
2213 | p911
2214 | tp912
2215 | bsS'indoor_213.png'
2216 | p913
2217 | g2
2218 | (g3
2219 | (I0
2220 | tp914
2221 | g5
2222 | tp915
2223 | Rp916
2224 | (I1
2225 | (L4L
2226 | tp917
2227 | g12
2228 | I00
2229 | S'\x00\x00\x00\x00\x00\x90f@\x00\x00\x00\x00\x00Hs@\x00\x00\x00\x00\x00\xc8r@\x00\x00\x00\x00\x00\x08z@'
2230 | p918
2231 | tp919
2232 | bsS'indoor_280.png'
2233 | p920
2234 | g2
2235 | (g3
2236 | (I0
2237 | tp921
2238 | g5
2239 | tp922
2240 | Rp923
2241 | (I1
2242 | (L4L
2243 | tp924
2244 | g12
2245 | I00
2246 | S'\x00\x00\x00\x00\x00@M@\x00\x00\x00\x00\x00\xd0a@\x00\x00\x00\x00\x00\xd0j@\x00\x00\x00\x00\x00\xe8q@'
2247 | p925
2248 | tp926
2249 | bsS'indoor_185.png'
2250 | p927
2251 | g2
2252 | (g3
2253 | (I0
2254 | tp928
2255 | g5
2256 | tp929
2257 | Rp930
2258 | (I1
2259 | (L4L
2260 | tp931
2261 | g12
2262 | I00
2263 | S'\xaeG\xe1z\x14\xd6s@o\x12\x83\xc0J]\x91@\xcf\xf7S\xe3\xa5\x19\x81@Zd;\xdfO\xef\x95@'
2264 | p932
2265 | tp933
2266 | bsS'indoor_058.png'
2267 | p934
2268 | g2
2269 | (g3
2270 | (I0
2271 | tp935
2272 | g5
2273 | tp936
2274 | Rp937
2275 | (I1
2276 | (L4L
2277 | tp938
2278 | g12
2279 | I00
2280 | S'\x81\x95C\x8bl7W@\xc7K7\x89A@8@\n\xd7\xa3p=Ts@\x81\x95C\x8bl\x1fj@'
2281 | p939
2282 | tp940
2283 | bsS'indoor_143.png'
2284 | p941
2285 | g2
2286 | (g3
2287 | (I0
2288 | tp942
2289 | g5
2290 | tp943
2291 | Rp944
2292 | (I1
2293 | (L4L
2294 | tp945
2295 | g12
2296 | I00
2297 | S'\x00\x00\x00\x00\x00r\x92@\x00\x00\x00\x00\x00\x04\x84@\x00\x00\x00\x00\x00\xf2\x93@\x00\x00\x00\x00\x00D\x87@'
2298 | p946
2299 | tp947
2300 | bsS'indoor_197.png'
2301 | p948
2302 | g2
2303 | (g3
2304 | (I0
2305 | tp949
2306 | g5
2307 | tp950
2308 | Rp951
2309 | (I1
2310 | (L4L
2311 | tp952
2312 | g12
2313 | I00
2314 | S';\xdfO\x8d\x17\xa0\x90@\x04V\x0e-\xb29}@q=\n\xd7#V\x94@;\xdfO\x8d\x97\x0b\x85@'
2315 | p953
2316 | tp954
2317 | bsS'indoor_057.png'
2318 | p955
2319 | g2
2320 | (g3
2321 | (I0
2322 | tp956
2323 | g5
2324 | tp957
2325 | Rp958
2326 | (I1
2327 | (L4L
2328 | tp959
2329 | g12
2330 | I00
2331 | S'X9\xb4\xc8v~s@\x04V\x0e-\xb2\xd5[@y\xe9&1\x08\xa2\x84@j\xbct\x93\x18\x01\x81@'
2332 | p960
2333 | tp961
2334 | bsS'indoor_082.png'
2335 | p962
2336 | g2
2337 | (g3
2338 | (I0
2339 | tp963
2340 | g5
2341 | tp964
2342 | Rp965
2343 | (I1
2344 | (L4L
2345 | tp966
2346 | g12
2347 | I00
2348 | S'V\x0e-\xb2\x9dEs@T\xe3\xa5\x9b\xc4\x80n@)\\\x8f\xc2\xf5\xd5\x84@\xb0rh\x91\xedB\x84@'
2349 | p967
2350 | tp968
2351 | bsS'indoor_254.png'
2352 | p969
2353 | g2
2354 | (g3
2355 | (I0
2356 | tp970
2357 | g5
2358 | tp971
2359 | Rp972
2360 | (I1
2361 | (L4L
2362 | tp973
2363 | g12
2364 | I00
2365 | S'\x00\x00\x00\x00\x00(v@\x00\x00\x00\x00\x00\xa0P@\x00\x00\x00\x00\x00\xe8{@\x00\x00\x00\x00\x00\xd0f@'
2366 | p974
2367 | tp975
2368 | bsS'indoor_255.png'
2369 | p976
2370 | g2
2371 | (g3
2372 | (I0
2373 | tp977
2374 | g5
2375 | tp978
2376 | Rp979
2377 | (I1
2378 | (L4L
2379 | tp980
2380 | g12
2381 | I00
2382 | S'\x00\x00\x00\x00\x00\x80>@\x00\x00\x00\x00\x00\x00-@\x00\x00\x00\x00\x00P`@\x00\x00\x00\x00\x00@]@'
2383 | p981
2384 | tp982
2385 | bsS'indoor_173.png'
2386 | p983
2387 | g2
2388 | (g3
2389 | (I0
2390 | tp984
2391 | g5
2392 | tp985
2393 | Rp986
2394 | (I1
2395 | (L4L
2396 | tp987
2397 | g12
2398 | I00
2399 | S'\x00\x00\x00\x00\x00\x04\x8b@\x00\x00\x00\x00\x00d\x80@\x00\x00\x00\x00\x00D\x8e@\x00\x00\x00\x00\x00$\x84@'
2400 | p988
2401 | tp989
2402 | bsS'indoor_086.png'
2403 | p990
2404 | g2
2405 | (g3
2406 | (I0
2407 | tp991
2408 | g5
2409 | tp992
2410 | Rp993
2411 | (I1
2412 | (L4L
2413 | tp994
2414 | g12
2415 | I00
2416 | S'\x14\xaeG\xe1z\xe4o@\xaa\xf1\xd2Mb`X@\x81\x95C\x8bl\xefz@\xe1z\x14\xaeG\x99r@'
2417 | p995
2418 | tp996
2419 | bsS'indoor_122.png'
2420 | p997
2421 | g2
2422 | (g3
2423 | (I0
2424 | tp998
2425 | g5
2426 | tp999
2427 | Rp1000
2428 | (I1
2429 | (L4L
2430 | tp1001
2431 | g12
2432 | I00
2433 | S'\xfe\xd4x\xe9&r\x8c@B`\xe5\xd0"\x8b\x83@\x17\xd9\xce\xf7\xd3\x87\x92@\x85\xebQ\xb8\x1e\xdf\x8b@'
2434 | p1002
2435 | tp1003
2436 | bsS'indoor_263.png'
2437 | p1004
2438 | g2
2439 | (g3
2440 | (I0
2441 | tp1005
2442 | g5
2443 | tp1006
2444 | Rp1007
2445 | (I1
2446 | (L4L
2447 | tp1008
2448 | g12
2449 | I00
2450 | S'\x00\x00\x00\x00\x00\x88v@\x00\x00\x00\x00\x00@L@\x00\x00\x00\x00\x00\x08|@\x00\x00\x00\x00\x00\x90d@'
2451 | p1009
2452 | tp1010
2453 | bsS'indoor_121.png'
2454 | p1011
2455 | g2
2456 | (g3
2457 | (I0
2458 | tp1012
2459 | g5
2460 | tp1013
2461 | Rp1014
2462 | (I1
2463 | (L4L
2464 | tp1015
2465 | g12
2466 | I00
2467 | S'Zd;\xdfOa\x9c@\xd3Mb\x10X\xa9e@\xc3\xf5(\\\x8f\t\xa0@\xd9\xce\xf7S\xe3\x9by@'
2468 | p1016
2469 | tp1017
2470 | bsS'indoor_112.png'
2471 | p1018
2472 | g2
2473 | (g3
2474 | (I0
2475 | tp1019
2476 | g5
2477 | tp1020
2478 | Rp1021
2479 | (I1
2480 | (L4L
2481 | tp1022
2482 | g12
2483 | I00
2484 | S'7\x89A`e\xa3\x92@\xc3\xf5(\\\x8f0\x7f@J\x0c\x02+\x87\xef\x94@o\x12\x83\xc0\xca\x0b\x84@'
2485 | p1023
2486 | tp1024
2487 | bsS'indoor_288.png'
2488 | p1025
2489 | g2
2490 | (g3
2491 | (I0
2492 | tp1026
2493 | g5
2494 | tp1027
2495 | Rp1028
2496 | (I1
2497 | (L4L
2498 | tp1029
2499 | g12
2500 | I00
2501 | S'\xe3\xa5\x9b\xc4 A\x90@sh\x91\xed|\x83o@\xb0rh\x91\xed\x91\x93@)\\\x8f\xc2\xf5\xc6}@'
2502 | p1030
2503 | tp1031
2504 | bsS'indoor_283.png'
2505 | p1032
2506 | g2
2507 | (g3
2508 | (I0
2509 | tp1033
2510 | g5
2511 | tp1034
2512 | Rp1035
2513 | (I1
2514 | (L4L
2515 | tp1036
2516 | g12
2517 | I00
2518 | S'\x00\x00\x00\x00\x00Pj@\x00\x00\x00\x00\x00\xa0Z@\x00\x00\x00\x00\x00\xa8u@\x00\x00\x00\x00\x00Pn@'
2519 | p1037
2520 | tp1038
2521 | bsS'indoor_248.png'
2522 | p1039
2523 | g2
2524 | (g3
2525 | (I0
2526 | tp1040
2527 | g5
2528 | tp1041
2529 | Rp1042
2530 | (I1
2531 | (L4L
2532 | tp1043
2533 | g12
2534 | I00
2535 | S'\x00\x00\x00\x00\x00\xe8|@\x00\x00\x00\x00\x00\xf4\x82@\x00\x00\x00\x00\x004\x82@\x00\x00\x00\x00\x00T\x86@'
2536 | p1044
2537 | tp1045
2538 | bsS'indoor_214.png'
2539 | p1046
2540 | g2
2541 | (g3
2542 | (I0
2543 | tp1047
2544 | g5
2545 | tp1048
2546 | Rp1049
2547 | (I1
2548 | (L4L
2549 | tp1050
2550 | g12
2551 | I00
2552 | S'm\xe7\xfb\xa9\xf1Bf@\xf2\xd2Mb\x10hR@fffff<{@fffff<{@'
2553 | p1051
2554 | tp1052
2555 | bsS'indoor_088.png'
2556 | p1053
2557 | g2
2558 | (g3
2559 | (I0
2560 | tp1054
2561 | g5
2562 | tp1055
2563 | Rp1056
2564 | (I1
2565 | (L4L
2566 | tp1057
2567 | g12
2568 | I00
2569 | S'\x00\x00\x00\x00\x00(w@\x00\x00\x00\x00\x00\xa0Z@\x00\x00\x00\x00\x00\xe8~@\x00\x00\x00\x00\x00\xd0m@'
2570 | p1058
2571 | tp1059
2572 | bsS'indoor_076.png'
2573 | p1060
2574 | g2
2575 | (g3
2576 | (I0
2577 | tp1061
2578 | g5
2579 | tp1062
2580 | Rp1063
2581 | (I1
2582 | (L4L
2583 | tp1064
2584 | g12
2585 | I00
2586 | S'\x91\xed|?5\x87\x80@T\xe3\xa5\x9b\xc4\x80n@\x9e\xef\xa7\xc6K\x94\x8a@o\x12\x83\xc0\xca\xf6\x81@'
2587 | p1065
2588 | tp1066
2589 | bsS'indoor_217.png'
2590 | p1067
2591 | g2
2592 | (g3
2593 | (I0
2594 | tp1068
2595 | g5
2596 | tp1069
2597 | Rp1070
2598 | (I1
2599 | (L4L
2600 | tp1071
2601 | g12
2602 | I00
2603 | S'\x00\x00\x00\x00\x00\xa0]@\x00\x00\x00\x00\x00Pa@\x00\x00\x00\x00\x00\xe8p@\x00\x00\x00\x00\x00\xa8r@'
2604 | p1072
2605 | tp1073
2606 | bsS'indoor_156.png'
2607 | p1074
2608 | g2
2609 | (g3
2610 | (I0
2611 | tp1075
2612 | g5
2613 | tp1076
2614 | Rp1077
2615 | (I1
2616 | (L4L
2617 | tp1078
2618 | g12
2619 | I00
2620 | S'\xe9&1\x08\xac\x1c&@^\xbaI\x0c\x02\xf9\x8b@\xb8\x1e\x85\xebQ\xc8j@\xc9v\xbe\x9f\x1a^\x91@'
2621 | p1079
2622 | tp1080
2623 | bsS'indoor_199.png'
2624 | p1081
2625 | g2
2626 | (g3
2627 | (I0
2628 | tp1082
2629 | g5
2630 | tp1083
2631 | Rp1084
2632 | (I1
2633 | (L4L
2634 | tp1085
2635 | g12
2636 | I00
2637 | S'\x00\x00\x00\x00\x00\xca\x97@\x00\x00\x00\x00\x00\xa0X@\x00\x00\x00\x00\x00\x1a\x9a@\x00\x00\x00\x00\x00\xd0m@'
2638 | p1086
2639 | tp1087
2640 | bsS'indoor_181.png'
2641 | p1088
2642 | g2
2643 | (g3
2644 | (I0
2645 | tp1089
2646 | g5
2647 | tp1090
2648 | Rp1091
2649 | (I1
2650 | (L4L
2651 | tp1092
2652 | g12
2653 | I00
2654 | S'\xe5\xd0"\xdb\xf9J\x7f@\xd7\xa3p=\n\xde\x82@\xdd$\x06\x81\x95\xb5\x85@\xbaI\x0c\x02+\xd3\x8a@'
2655 | p1093
2656 | tp1094
2657 | bsS'indoor_100.png'
2658 | p1095
2659 | g2
2660 | (g3
2661 | (I0
2662 | tp1096
2663 | g5
2664 | tp1097
2665 | Rp1098
2666 | (I1
2667 | (L4L
2668 | tp1099
2669 | g12
2670 | I00
2671 | S'\x93\x18\x04V\x8e\xce\x93@\x87\x16\xd9\xce\xf7\x84\x8e@\xe9&1\x08,2\x9b@j\xbct\x93\x98u\x96@'
2672 | p1100
2673 | tp1101
2674 | bsS'indoor_047.png'
2675 | p1102
2676 | g2
2677 | (g3
2678 | (I0
2679 | tp1103
2680 | g5
2681 | tp1104
2682 | Rp1105
2683 | (I1
2684 | (L4L
2685 | tp1106
2686 | g12
2687 | I00
2688 | S'\xf6(\\\x8f\xc2\x99e@X9\xb4\xc8vn`@\xd9\xce\xf7S\xe3\xb3s@\xd3Mb\x10X\xd7r@'
2689 | p1107
2690 | tp1108
2691 | bsS'indoor_158.png'
2692 | p1109
2693 | g2
2694 | (g3
2695 | (I0
2696 | tp1110
2697 | g5
2698 | tp1111
2699 | Rp1112
2700 | (I1
2701 | (L4L
2702 | tp1113
2703 | g12
2704 | I00
2705 | S'\x00\x00\x00\x00\x00\xc8y@\x00\x00\x00\x00\x00\x10k@\x00\x00\x00\x00\x00\xc8\x7f@\x00\x00\x00\x00\x00\x08s@'
2706 | p1114
2707 | tp1115
2708 | bsS'indoor_191.png'
2709 | p1116
2710 | g2
2711 | (g3
2712 | (I0
2713 | tp1117
2714 | g5
2715 | tp1118
2716 | Rp1119
2717 | (I1
2718 | (L4L
2719 | tp1120
2720 | g12
2721 | I00
2722 | S'\x08\xac\x1cZ$2\xa4@\x00\x00\x00\x00\x00T\x83@q=\n\xd7\xa3<\xa5@/\xdd$\x06\x81\xc7\x87@'
2723 | p1121
2724 | tp1122
2725 | bsS'indoor_051.png'
2726 | p1123
2727 | g2
2728 | (g3
2729 | (I0
2730 | tp1124
2731 | g5
2732 | tp1125
2733 | Rp1126
2734 | (I1
2735 | (L4L
2736 | tp1127
2737 | g12
2738 | I00
2739 | S'\xb8\x1e\x85\xebQ\xe0W@\\\x8f\xc2\xf5(\n\x7f@9\xb4\xc8v\xbe\x18\x88@\xa6\x9b\xc4 \xb0\xa2\x93@'
2740 | p1128
2741 | tp1129
2742 | bsS'indoor_245.png'
2743 | p1130
2744 | g2
2745 | (g3
2746 | (I0
2747 | tp1131
2748 | g5
2749 | tp1132
2750 | Rp1133
2751 | (I1
2752 | (L4L
2753 | tp1134
2754 | g12
2755 | I00
2756 | S'\x00\x00\x00\x00\x00hp@\x00\x00\x00\x00\x00\xa0[@\x00\x00\x00\x00\x00hw@\x00\x00\x00\x00\x00\xd0m@'
2757 | p1135
2758 | tp1136
2759 | bsS'indoor_130.png'
2760 | p1137
2761 | g2
2762 | (g3
2763 | (I0
2764 | tp1138
2765 | g5
2766 | tp1139
2767 | Rp1140
2768 | (I1
2769 | (L4L
2770 | tp1141
2771 | g12
2772 | I00
2773 | S'L7\x89A`\xb1h@\x81\x95C\x8bl\xf7j@\xd9\xce\xf7S\xe3\xd9x@\x96C\x8bl\xe7]z@'
2774 | p1142
2775 | tp1143
2776 | bsS'indoor_023.png'
2777 | p1144
2778 | g2
2779 | (g3
2780 | (I0
2781 | tp1145
2782 | g5
2783 | tp1146
2784 | Rp1147
2785 | (I1
2786 | (L4L
2787 | tp1148
2788 | g12
2789 | I00
2790 | S'\xe3\xa5\x9b\xc4 |k@\xee|?5^\xaaP@\xa6\x9b\xc4 \xb0\x8a|@-\xb2\x9d\xef\xa7fs@'
2791 | p1149
2792 | tp1150
2793 | bsS'indoor_124.png'
2794 | p1151
2795 | g2
2796 | (g3
2797 | (I0
2798 | tp1152
2799 | g5
2800 | tp1153
2801 | Rp1154
2802 | (I1
2803 | (L4L
2804 | tp1155
2805 | g12
2806 | I00
2807 | S'\x00\x00\x00\x00\x00\x90g@\x00\x00\x00\x00\x00\x90j@\x00\x00\x00\x00\x00\xc8}@\x00\x00\x00\x00\x00\xe4\x80@'
2808 | p1156
2809 | tp1157
2810 | bsS'indoor_125.png'
2811 | p1158
2812 | g2
2813 | (g3
2814 | (I0
2815 | tp1159
2816 | g5
2817 | tp1160
2818 | Rp1161
2819 | (I1
2820 | (L4L
2821 | tp1162
2822 | g12
2823 | I00
2824 | S'\x00\x00\x00\x00\x00Ht@\x00\x00\x00\x00\x00\x90k@\x00\x00\x00\x00\x00d\x82@\x00\x00\x00\x00\x00\xc8~@'
2825 | p1163
2826 | tp1164
2827 | bsS'indoor_268.png'
2828 | p1165
2829 | g2
2830 | (g3
2831 | (I0
2832 | tp1166
2833 | g5
2834 | tp1167
2835 | Rp1168
2836 | (I1
2837 | (L4L
2838 | tp1169
2839 | g12
2840 | I00
2841 | S'\x1f\x85\xebQ\xb8\xd4p@\xd9\xce\xf7S\xe3\xe5g@Nb\x10X9ry@\x93\x18\x04V\x0e\x93v@'
2842 | p1170
2843 | tp1171
2844 | bsS'indoor_290.png'
2845 | p1172
2846 | g2
2847 | (g3
2848 | (I0
2849 | tp1173
2850 | g5
2851 | tp1174
2852 | Rp1175
2853 | (I1
2854 | (L4L
2855 | tp1176
2856 | g12
2857 | I00
2858 | S'\x00\x00\x00\x00\x00\x14\x84@\x00\x00\x00\x00\x00\xa0X@\x00\x00\x00\x00\x00\xb4\x87@\x00\x00\x00\x00\x00\xd0j@'
2859 | p1177
2860 | tp1178
2861 | bsS'indoor_178.png'
2862 | p1179
2863 | g2
2864 | (g3
2865 | (I0
2866 | tp1180
2867 | g5
2868 | tp1181
2869 | Rp1182
2870 | (I1
2871 | (L4L
2872 | tp1183
2873 | g12
2874 | I00
2875 | S'\x00\x00\x00\x00\x00\xea\x9a@\x00\x00\x00\x00\x00\xe8~@\x00\x00\x00\x00\x00z\x9d@\x00\x00\x00\x00\x004\x84@'
2876 | p1184
2877 | tp1185
2878 | bsS'indoor_215.png'
2879 | p1186
2880 | g2
2881 | (g3
2882 | (I0
2883 | tp1187
2884 | g5
2885 | tp1188
2886 | Rp1189
2887 | (I1
2888 | (L4L
2889 | tp1190
2890 | g12
2891 | I00
2892 | S'H\xe1z\x14\xae\xc7l@\xb0rh\x91\xed4P@\x93\x18\x04V\x0e\xb9\x8a@V\x0e-\xb2\x9dA\x83@'
2893 | p1191
2894 | tp1192
2895 | bsS'indoor_067.png'
2896 | p1193
2897 | g2
2898 | (g3
2899 | (I0
2900 | tp1194
2901 | g5
2902 | tp1195
2903 | Rp1196
2904 | (I1
2905 | (L4L
2906 | tp1197
2907 | g12
2908 | I00
2909 | S'\xf4\xfd\xd4x\xe9\xdac@\xd1"\xdb\xf9~~f@\xee|?5^\xb8}@%\x06\x81\x95Ca~@'
2910 | p1198
2911 | tp1199
2912 | bsS'indoor_168.png'
2913 | p1200
2914 | g2
2915 | (g3
2916 | (I0
2917 | tp1201
2918 | g5
2919 | tp1202
2920 | Rp1203
2921 | (I1
2922 | (L4L
2923 | tp1204
2924 | g12
2925 | I00
2926 | S'\x00\x00\x00\x00\x00\x10l@\x00\x00\x00\x00\x00 Z@\x00\x00\x00\x00\x00\x08~@\x00\x00\x00\x00\x00\x88s@'
2927 | p1205
2928 | tp1206
2929 | bsS'indoor_154.png'
2930 | p1207
2931 | g2
2932 | (g3
2933 | (I0
2934 | tp1208
2935 | g5
2936 | tp1209
2937 | Rp1210
2938 | (I1
2939 | (L4L
2940 | tp1211
2941 | g12
2942 | I00
2943 | S'\xa2E\xb6\xf3\xfd\x95\x9e@\xe9&1\x08\xac\xf4\x87@H\xe1z\x14\xee\xde\xa0@\xc3\xf5(\\\x8f\xeb\x8e@'
2944 | p1212
2945 | tp1213
2946 | bsS'indoor_044.png'
2947 | p1214
2948 | g2
2949 | (g3
2950 | (I0
2951 | tp1215
2952 | g5
2953 | tp1216
2954 | Rp1217
2955 | (I1
2956 | (L4L
2957 | tp1218
2958 | g12
2959 | I00
2960 | S'Nb\x10X9Pe@\xa2E\xb6\xf3\xfdT@@}?5^\xba\xd0\x80@\xf4\xfd\xd4x\xe9px@'
2961 | p1219
2962 | tp1220
2963 | bsS'indoor_041.png'
2964 | p1221
2965 | g2
2966 | (g3
2967 | (I0
2968 | tp1222
2969 | g5
2970 | tp1223
2971 | Rp1224
2972 | (I1
2973 | (L4L
2974 | tp1225
2975 | g12
2976 | I00
2977 | S'\x96C\x8bl\xe7Y\x8a@\xe1z\x14\xaeG\xd7q@5^\xbaI\x0c=\x93@\x02+\x87\x16\xd9\x8f\x86@'
2978 | p1226
2979 | tp1227
2980 | bsS'indoor_040.png'
2981 | p1228
2982 | g2
2983 | (g3
2984 | (I0
2985 | tp1229
2986 | g5
2987 | tp1230
2988 | Rp1231
2989 | (I1
2990 | (L4L
2991 | tp1232
2992 | g12
2993 | I00
2994 | S'\x00\x00\x00\x00\x00\xe8x@\x00\x00\x00\x00\x00\xa0Z@\x00\x00\x00\x00\x00\xf4\x80@\x00\x00\x00\x00\x00Pk@'
2995 | p1233
2996 | tp1234
2997 | bsS'indoor_223.png'
2998 | p1235
2999 | g2
3000 | (g3
3001 | (I0
3002 | tp1236
3003 | g5
3004 | tp1237
3005 | Rp1238
3006 | (I1
3007 | (L4L
3008 | tp1239
3009 | g12
3010 | I00
3011 | S'o\x12\x83\xc0\xca\x8c\x8c@\x14\xaeG\xe1z\xf6\x84@\xb6\xf3\xfd\xd4x6\x94@\xc1\xca\xa1E6\x14\x91@'
3012 | p1240
3013 | tp1241
3014 | bsS'indoor_131.png'
3015 | p1242
3016 | g2
3017 | (g3
3018 | (I0
3019 | tp1243
3020 | g5
3021 | tp1244
3022 | Rp1245
3023 | (I1
3024 | (L4L
3025 | tp1246
3026 | g12
3027 | I00
3028 | S'\x9e\xef\xa7\xc6K[s@?5^\xbaI\xccP@\xe7\xfb\xa9\xf1\xd2\x0b\x85@\xfa~j\xbct5}@'
3029 | p1247
3030 | tp1248
3031 | bsS'indoor_010.png'
3032 | p1249
3033 | g2
3034 | (g3
3035 | (I0
3036 | tp1250
3037 | g5
3038 | tp1251
3039 | Rp1252
3040 | (I1
3041 | (L4L
3042 | tp1253
3043 | g12
3044 | I00
3045 | S'\xd1"\xdb\xf9~\xe0y@D\x8bl\xe7\xfb\x92\x89@\xf6(\\\x8f\xc2a\x91@\\\x8f\xc2\xf5(F\x98@'
3046 | p1254
3047 | tp1255
3048 | bsS'indoor_132.png'
3049 | p1256
3050 | g2
3051 | (g3
3052 | (I0
3053 | tp1257
3054 | g5
3055 | tp1258
3056 | Rp1259
3057 | (I1
3058 | (L4L
3059 | tp1260
3060 | g12
3061 | I00
3062 | S'L7\x89A`[\x94@\xecQ\xb8\x1e\x85A\x84@\xa4p=\n\xd7h\x9c@\x8f\xc2\xf5(\\O\x91@'
3063 | p1261
3064 | tp1262
3065 | bsS'indoor_004.png'
3066 | p1263
3067 | g2
3068 | (g3
3069 | (I0
3070 | tp1264
3071 | g5
3072 | tp1265
3073 | Rp1266
3074 | (I1
3075 | (L4L
3076 | tp1267
3077 | g12
3078 | I00
3079 | S'\xaeG\xe1z\x14\xd6s@\xee|?5^\xa6c@\x10X9\xb4\xc8:\x80@\xa8\xc6K7\x89]z@'
3080 | p1268
3081 | tp1269
3082 | bsS'indoor_139.png'
3083 | p1270
3084 | g2
3085 | (g3
3086 | (I0
3087 | tp1271
3088 | g5
3089 | tp1272
3090 | Rp1273
3091 | (I1
3092 | (L4L
3093 | tp1274
3094 | g12
3095 | I00
3096 | S'\x02+\x87\x16\xd92\xa3@\xcd\xcc\xcc\xcc\xcc\xe9\x9c@\x08\xac\x1cZ\xa4\x84\xa4@Nb\x10X\xb9\xcc\x9f@'
3097 | p1275
3098 | tp1276
3099 | bsS'indoor_296.png'
3100 | p1277
3101 | g2
3102 | (g3
3103 | (I0
3104 | tp1278
3105 | g5
3106 | tp1279
3107 | Rp1280
3108 | (I1
3109 | (L4L
3110 | tp1281
3111 | g12
3112 | I00
3113 | S'sh\x91\xed|\x83o@\xd1"\xdb\xf9~2_@m\xe7\xfb\xa9\xf1\x04}@\xe7\xfb\xa9\xf1\xd2\x0fu@'
3114 | p1282
3115 | tp1283
3116 | bsS'indoor_297.png'
3117 | p1284
3118 | g2
3119 | (g3
3120 | (I0
3121 | tp1285
3122 | g5
3123 | tp1286
3124 | Rp1287
3125 | (I1
3126 | (L4L
3127 | tp1288
3128 | g12
3129 | I00
3130 | S'B`\xe5\xd0"\x8fs@\xecQ\xb8\x1e\x85\x8bZ@q=\n\xd7\xa3,|@+\x87\x16\xd9\xce\x13o@'
3131 | p1289
3132 | tp1290
3133 | bsS'indoor_102.png'
3134 | p1291
3135 | g2
3136 | (g3
3137 | (I0
3138 | tp1292
3139 | g5
3140 | tp1293
3141 | Rp1294
3142 | (I1
3143 | (L4L
3144 | tp1295
3145 | g12
3146 | I00
3147 | S'\x00\x00\x00\x00\x00\x08p@\x00\x00\x00\x00\x00\x88t@\x00\x00\x00\x00\x00\xc8v@\x00\x00\x00\x00\x00\x08{@'
3148 | p1296
3149 | tp1297
3150 | bsS'indoor_242.png'
3151 | p1298
3152 | g2
3153 | (g3
3154 | (I0
3155 | tp1299
3156 | g5
3157 | tp1300
3158 | Rp1301
3159 | (I1
3160 | (L4L
3161 | tp1302
3162 | g12
3163 | I00
3164 | S'\xe7\xfb\xa9\xf1\xd2\x8dr@%\x06\x81\x95C7n@\xbct\x93\x18\x04T~@+\x87\x16\xd9\xce\xe1z@'
3165 | p1303
3166 | tp1304
3167 | bsS'indoor_203.png'
3168 | p1305
3169 | g2
3170 | (g3
3171 | (I0
3172 | tp1306
3173 | g5
3174 | tp1307
3175 | Rp1308
3176 | (I1
3177 | (L4L
3178 | tp1309
3179 | g12
3180 | I00
3181 | S'\x06\x81\x95CK\x87\xaa@\x1f\x85\xebQ\xb8\xcc\x91@\xfc\xa9\xf1\xd2M\xd0\xac@\xcb\xa1E\xb6s\xd3\x95@'
3182 | p1310
3183 | tp1311
3184 | bsS'indoor_219.png'
3185 | p1312
3186 | g2
3187 | (g3
3188 | (I0
3189 | tp1313
3190 | g5
3191 | tp1314
3192 | Rp1315
3193 | (I1
3194 | (L4L
3195 | tp1316
3196 | g12
3197 | I00
3198 | S'\x00\x00\x00\x00\x00\x90g@\x00\x00\x00\x00\x00 T@\x00\x00\x00\x00\x00\x88p@\x00\x00\x00\x00\x00\x90e@'
3199 | p1317
3200 | tp1318
3201 | bsS'indoor_146.png'
3202 | p1319
3203 | g2
3204 | (g3
3205 | (I0
3206 | tp1320
3207 | g5
3208 | tp1321
3209 | Rp1322
3210 | (I1
3211 | (L4L
3212 | tp1323
3213 | g12
3214 | I00
3215 | S'L7\x89A`\xa3u@\x96C\x8bl\xe7\x10\x83@D\x8bl\xe7\xfb\xeb\x80@\xfc\xa9\xf1\xd2M\x82\x88@'
3216 | p1324
3217 | tp1325
3218 | bsS'indoor_200.png'
3219 | p1326
3220 | g2
3221 | (g3
3222 | (I0
3223 | tp1327
3224 | g5
3225 | tp1328
3226 | Rp1329
3227 | (I1
3228 | (L4L
3229 | tp1330
3230 | g12
3231 | I00
3232 | S'\x00\x00\x00\x00\x00\x90j@\x00\x00\x00\x00\x00 P@\x00\x00\x00\x00\x00\xc8s@\x00\x00\x00\x00\x00\x90d@'
3233 | p1331
3234 | tp1332
3235 | bsS'indoor_184.png'
3236 | p1333
3237 | g2
3238 | (g3
3239 | (I0
3240 | tp1334
3241 | g5
3242 | tp1335
3243 | Rp1336
3244 | (I1
3245 | (L4L
3246 | tp1337
3247 | g12
3248 | I00
3249 | S'w\xbe\x9f\x1a\xafx\x99@d;\xdfO\x8d\xdf\x8b@\x91\xed|?\xb5\x90\x9f@\x8bl\xe7\xfb\xa9\xe6\x94@'
3250 | p1338
3251 | tp1339
3252 | bsS'indoor_048.png'
3253 | p1340
3254 | g2
3255 | (g3
3256 | (I0
3257 | tp1341
3258 | g5
3259 | tp1342
3260 | Rp1343
3261 | (I1
3262 | (L4L
3263 | tp1344
3264 | g12
3265 | I00
3266 | S')\\\x8f\xc2\xf5Fx@\xf0\xa7\xc6K7qk@\x91\xed|?5\x16\x81@\x8d\x97n\x12\x83\xf2w@'
3267 | p1345
3268 | tp1346
3269 | bsS'indoor_109.png'
3270 | p1347
3271 | g2
3272 | (g3
3273 | (I0
3274 | tp1348
3275 | g5
3276 | tp1349
3277 | Rp1350
3278 | (I1
3279 | (L4L
3280 | tp1351
3281 | g12
3282 | I00
3283 | S'\x00\x00\x00\x00\x00\x82\x90@\x00\x00\x00\x00\x00\x02\x9d@\x00\x00\x00\x00\x00\x02\x98@\x00\x00\x00\x00\x00\x01\xa2@'
3284 | p1352
3285 | tp1353
3286 | bsS'indoor_056.png'
3287 | p1354
3288 | g2
3289 | (g3
3290 | (I0
3291 | tp1355
3292 | g5
3293 | tp1356
3294 | Rp1357
3295 | (I1
3296 | (L4L
3297 | tp1358
3298 | g12
3299 | I00
3300 | S'\x00\x00\x00\x00\x00P`@\x00\x00\x00\x00\x00\x80>@\x00\x00\x00\x00\x00\xd0o@\x00\x00\x00\x00\x00\xd0d@'
3301 | p1359
3302 | tp1360
3303 | bsS'indoor_032.png'
3304 | p1361
3305 | g2
3306 | (g3
3307 | (I0
3308 | tp1362
3309 | g5
3310 | tp1363
3311 | Rp1364
3312 | (I1
3313 | (L4L
3314 | tp1365
3315 | g12
3316 | I00
3317 | S'\xaeG\xe1z\x14L\x82@m\xe7\xfb\xa9\xf16c@\x87\x16\xd9\xce\xf7B\x89@+\x87\x16\xd9\xce\x19w@'
3318 | p1366
3319 | tp1367
3320 | bsS'indoor_046.png'
3321 | p1368
3322 | g2
3323 | (g3
3324 | (I0
3325 | tp1369
3326 | g5
3327 | tp1370
3328 | Rp1371
3329 | (I1
3330 | (L4L
3331 | tp1372
3332 | g12
3333 | I00
3334 | S'\x00\x00\x00\x00\x00\xa4\x81@\x00\x00\x00\x00\x00\x90i@\x00\x00\x00\x00\x00\xe4\x8a@\x00\x00\x00\x00\x00H\x7f@'
3335 | p1373
3336 | tp1374
3337 | bsS'indoor_087.png'
3338 | p1375
3339 | g2
3340 | (g3
3341 | (I0
3342 | tp1376
3343 | g5
3344 | tp1377
3345 | Rp1378
3346 | (I1
3347 | (L4L
3348 | tp1379
3349 | g12
3350 | I00
3351 | S'\x00\x00\x00\x00\x00\xd0f@\x00\x00\x00\x00\x00\xa0\\@\x00\x00\x00\x00\x00(s@\x00\x00\x00\x00\x00\xd0m@'
3352 | p1380
3353 | tp1381
3354 | bsS'indoor_161.png'
3355 | p1382
3356 | g2
3357 | (g3
3358 | (I0
3359 | tp1383
3360 | g5
3361 | tp1384
3362 | Rp1385
3363 | (I1
3364 | (L4L
3365 | tp1386
3366 | g12
3367 | I00
3368 | S'\'1\x08\xac\x1c\x96z@`\xe5\xd0"\xdb\xefx@\xe3\xa5\x9b\xc4 ;\x83@d;\xdfO\x8d\x13\x82@'
3369 | p1387
3370 | tp1388
3371 | bsS'indoor_260.png'
3372 | p1389
3373 | g2
3374 | (g3
3375 | (I0
3376 | tp1390
3377 | g5
3378 | tp1391
3379 | Rp1392
3380 | (I1
3381 | (L4L
3382 | tp1393
3383 | g12
3384 | I00
3385 | S'\xb4\xc8v\xbe\x9ffo@^\xbaI\x0c\x02\xdbY@33333\xedy@d;\xdfO\x8dYq@'
3386 | p1394
3387 | tp1395
3388 | bsS'indoor_113.png'
3389 | p1396
3390 | g2
3391 | (g3
3392 | (I0
3393 | tp1397
3394 | g5
3395 | tp1398
3396 | Rp1399
3397 | (I1
3398 | (L4L
3399 | tp1400
3400 | g12
3401 | I00
3402 | S'\x00\x00\x00\x00\x00\x9a\x9c@\x00\x00\x00\x00\x00(~@\x00\x00\x00\x00\x00\xba\x9e@\x00\x00\x00\x00\x00\xd4\x82@'
3403 | p1401
3404 | tp1402
3405 | bsS'indoor_274.png'
3406 | p1403
3407 | g2
3408 | (g3
3409 | (I0
3410 | tp1404
3411 | g5
3412 | tp1405
3413 | Rp1406
3414 | (I1
3415 | (L4L
3416 | tp1407
3417 | g12
3418 | I00
3419 | S'\x00\x00\x00\x00\x00 T@\x00\x00\x00\x00\x00 X@\x00\x00\x00\x00\x00\x10d@\x00\x00\x00\x00\x00\x90g@'
3420 | p1408
3421 | tp1409
3422 | bsS'indoor_275.png'
3423 | p1410
3424 | g2
3425 | (g3
3426 | (I0
3427 | tp1411
3428 | g5
3429 | tp1412
3430 | Rp1413
3431 | (I1
3432 | (L4L
3433 | tp1414
3434 | g12
3435 | I00
3436 | S'\x00\x00\x00\x00\x00\x08p@\x00\x00\x00\x00\x00 V@\x00\x00\x00\x00\x00Hu@\x00\x00\x00\x00\x00\x10f@'
3437 | p1415
3438 | tp1416
3439 | bsS'indoor_179.png'
3440 | p1417
3441 | g2
3442 | (g3
3443 | (I0
3444 | tp1418
3445 | g5
3446 | tp1419
3447 | Rp1420
3448 | (I1
3449 | (L4L
3450 | tp1421
3451 | g12
3452 | I00
3453 | S'\x00\x00\x00\x00\x00Z\x96@\x00\x00\x00\x00\x00\xa8\x7f@\x00\x00\x00\x00\x00:\x98@\x00\x00\x00\x00\x00\x14\x83@'
3454 | p1422
3455 | tp1423
3456 | bsS'indoor_231.png'
3457 | p1424
3458 | g2
3459 | (g3
3460 | (I0
3461 | tp1425
3462 | g5
3463 | tp1426
3464 | Rp1427
3465 | (I1
3466 | (L4L
3467 | tp1428
3468 | g12
3469 | I00
3470 | S'\x00\x00\x00\x00\x00\x04\x82@\x00\x00\x00\x00\x00 Q@\x00\x00\x00\x00\x00\x84\x85@\x00\x00\x00\x00\x00\x10f@'
3471 | p1429
3472 | tp1430
3473 | bsS'indoor_287.png'
3474 | p1431
3475 | g2
3476 | (g3
3477 | (I0
3478 | tp1432
3479 | g5
3480 | tp1433
3481 | Rp1434
3482 | (I1
3483 | (L4L
3484 | tp1435
3485 | g12
3486 | I00
3487 | S';\xdfO\x8d\x97\xb2r@sh\x91\xed|\xf9p@7\x89A`\xe5\xaf\x83@\xbe\x9f\x1a/\xdd\x1c\x83@'
3488 | p1436
3489 | tp1437
3490 | bsS'indoor_291.png'
3491 | p1438
3492 | g2
3493 | (g3
3494 | (I0
3495 | tp1439
3496 | g5
3497 | tp1440
3498 | Rp1441
3499 | (I1
3500 | (L4L
3501 | tp1442
3502 | g12
3503 | I00
3504 | S'Nb\x10X9\xf3\x82@\xe9&1\x08\xac\xf8w@\x10X9\xb4\xc88\x90@\xc7K7\x89A\x0b\x89@'
3505 | p1443
3506 | tp1444
3507 | bsS'indoor_249.png'
3508 | p1445
3509 | g2
3510 | (g3
3511 | (I0
3512 | tp1446
3513 | g5
3514 | tp1447
3515 | Rp1448
3516 | (I1
3517 | (L4L
3518 | tp1449
3519 | g12
3520 | I00
3521 | S'\x00\x00\x00\x00\x00*\x92@\x00\x00\x00\x00\x00\xa8t@\x00\x00\x00\x00\x00z\x93@\x00\x00\x00\x00\x00\xa8{@'
3522 | p1450
3523 | tp1451
3524 | bsS'indoor_170.png'
3525 | p1452
3526 | g2
3527 | (g3
3528 | (I0
3529 | tp1453
3530 | g5
3531 | tp1454
3532 | Rp1455
3533 | (I1
3534 | (L4L
3535 | tp1456
3536 | g12
3537 | I00
3538 | S'-\xb2\x9d\xef\xa7\xd8s@\x10X9\xb4\xc8$v@7\x89A`\xe5\xaf\x83@\xb0rh\x91\xedB\x84@'
3539 | p1457
3540 | tp1458
3541 | bsS'indoor_182.png'
3542 | p1459
3543 | g2
3544 | (g3
3545 | (I0
3546 | tp1460
3547 | g5
3548 | tp1461
3549 | Rp1462
3550 | (I1
3551 | (L4L
3552 | tp1463
3553 | g12
3554 | I00
3555 | S'\xd5x\xe9&\xb1\xc1\x9b@\xe5\xd0"\xdb\xf9\xc8\x8a@R\xb8\x1e\x85k\x05\x9f@\xdfO\x8d\x97\xee\xdf\x90@'
3556 | p1464
3557 | tp1465
3558 | bsS'indoor_210.png'
3559 | p1466
3560 | g2
3561 | (g3
3562 | (I0
3563 | tp1467
3564 | g5
3565 | tp1468
3566 | Rp1469
3567 | (I1
3568 | (L4L
3569 | tp1470
3570 | g12
3571 | I00
3572 | S'\x00\x00\x00\x00\x00\xc8z@\x00\x00\x00\x00\x00d\x80@\x00\x00\x00\x00\x00$\x81@\x00\x00\x00\x00\x00\xa4\x83@'
3573 | p1471
3574 | tp1472
3575 | bsS'indoor_212.png'
3576 | p1473
3577 | g2
3578 | (g3
3579 | (I0
3580 | tp1474
3581 | g5
3582 | tp1475
3583 | Rp1476
3584 | (I1
3585 | (L4L
3586 | tp1477
3587 | g12
3588 | I00
3589 | S'\x00\x00\x00\x00\x00\xf4\x8a@\x00\x00\x00\x00\x00\xe8~@\x00\x00\x00\x00\x004\x8f@\x00\x00\x00\x00\x00T\x83@'
3590 | p1478
3591 | tp1479
3592 | bsS'indoor_072.png'
3593 | p1480
3594 | g2
3595 | (g3
3596 | (I0
3597 | tp1481
3598 | g5
3599 | tp1482
3600 | Rp1483
3601 | (I1
3602 | (L4L
3603 | tp1484
3604 | g12
3605 | I00
3606 | S'\x00\x00\x00\x00\x00 X@\x00\x00\x00\x00\x00@H@\x00\x00\x00\x00\x00\xc4\x81@\x00\x00\x00\x00\x00\x84\x80@'
3607 | p1485
3608 | tp1486
3609 | bsS'indoor_204.png'
3610 | p1487
3611 | g2
3612 | (g3
3613 | (I0
3614 | tp1488
3615 | g5
3616 | tp1489
3617 | Rp1490
3618 | (I1
3619 | (L4L
3620 | tp1491
3621 | g12
3622 | I00
3623 | S'\xcb\xa1E\xb6\xf3\x15\x95@\xfe\xd4x\xe9&\x11\x8a@^\xbaI\x0c\x82\xaf\x98@\xe3\xa5\x9b\xc4\xa0q\x90@'
3624 | p1492
3625 | tp1493
3626 | bsS'indoor_174.png'
3627 | p1494
3628 | g2
3629 | (g3
3630 | (I0
3631 | tp1495
3632 | g5
3633 | tp1496
3634 | Rp1497
3635 | (I1
3636 | (L4L
3637 | tp1498
3638 | g12
3639 | I00
3640 | S'\x00\x00\x00\x00\x002\x94@\x00\x00\x00\x00\x00\x08s@\x00\x00\x00\x00\x00\xc2\x95@\x00\x00\x00\x00\x00Hz@'
3641 | p1499
3642 | tp1500
3643 | bsS'indoor_090.png'
3644 | p1501
3645 | g2
3646 | (g3
3647 | (I0
3648 | tp1502
3649 | g5
3650 | tp1503
3651 | Rp1504
3652 | (I1
3653 | (L4L
3654 | tp1505
3655 | g12
3656 | I00
3657 | S'\x00\x00\x00\x00\x00\xc8z@\x00\x00\x00\x00\x00\x90o@\x00\x00\x00\x00\x00$\x87@\x00\x00\x00\x00\x00\xe4\x81@'
3658 | p1506
3659 | tp1507
3660 | bsS'indoor_034.png'
3661 | p1508
3662 | g2
3663 | (g3
3664 | (I0
3665 | tp1509
3666 | g5
3667 | tp1510
3668 | Rp1511
3669 | (I1
3670 | (L4L
3671 | tp1512
3672 | g12
3673 | I00
3674 | S'\xe7\xfb\xa9\xf1\xd2\x89\x82@sh\x91\xed|\xf9p@{\x14\xaeG\xe1\x03\x8c@\xd3Mb\x10X\xd3\x82@'
3675 | p1513
3676 | tp1514
3677 | bsS'indoor_035.png'
3678 | p1515
3679 | g2
3680 | (g3
3681 | (I0
3682 | tp1516
3683 | g5
3684 | tp1517
3685 | Rp1518
3686 | (I1
3687 | (L4L
3688 | tp1519
3689 | g12
3690 | I00
3691 | S'\x00\x00\x00\x00\x00Pe@\x00\x00\x00\x00\x00\xa0Z@\x00\x00\x00\x00\x00(t@\x00\x00\x00\x00\x00Pn@'
3692 | p1520
3693 | tp1521
3694 | bsS'indoor_256.png'
3695 | p1522
3696 | g2
3697 | (g3
3698 | (I0
3699 | tp1523
3700 | g5
3701 | tp1524
3702 | Rp1525
3703 | (I1
3704 | (L4L
3705 | tp1526
3706 | g12
3707 | I00
3708 | S'\x00\x00\x00\x00\x00@N@\x00\x00\x00\x00\x00@H@\x00\x00\x00\x00\x00\x90d@\x00\x00\x00\x00\x00\x10c@'
3709 | p1527
3710 | tp1528
3711 | bsS'indoor_261.png'
3712 | p1529
3713 | g2
3714 | (g3
3715 | (I0
3716 | tp1530
3717 | g5
3718 | tp1531
3719 | Rp1532
3720 | (I1
3721 | (L4L
3722 | tp1533
3723 | g12
3724 | I00
3725 | S'#\xdb\xf9~j\x0cM@h\x91\xed|?\x1da@T\xe3\xa5\x9b\xc4\xe4p@\x8bl\xe7\xfb\xa9\xb3u@'
3726 | p1534
3727 | tp1535
3728 | bsS'indoor_003.png'
3729 | p1536
3730 | g2
3731 | (g3
3732 | (I0
3733 | tp1537
3734 | g5
3735 | tp1538
3736 | Rp1539
3737 | (I1
3738 | (L4L
3739 | tp1540
3740 | g12
3741 | I00
3742 | S'+\x87\x16\xd9\xce\x19w@\xb0rh\x91\xed"p@H\xe1z\x14\xaez\x89@L7\x89A` \x85@'
3743 | p1541
3744 | tp1542
3745 | bsS'indoor_262.png'
3746 | p1543
3747 | g2
3748 | (g3
3749 | (I0
3750 | tp1544
3751 | g5
3752 | tp1545
3753 | Rp1546
3754 | (I1
3755 | (L4L
3756 | tp1547
3757 | g12
3758 | I00
3759 | S'\x00\x00\x00\x00\x00 R@\x00\x00\x00\x00\x00@B@\x00\x00\x00\x00\x00\x10e@\x00\x00\x00\x00\x00\x10c@'
3760 | p1548
3761 | tp1549
3762 | bsS'indoor_277.png'
3763 | p1550
3764 | g2
3765 | (g3
3766 | (I0
3767 | tp1551
3768 | g5
3769 | tp1552
3770 | Rp1553
3771 | (I1
3772 | (L4L
3773 | tp1554
3774 | g12
3775 | I00
3776 | S'\xc9v\xbe\x9f\x1a\x92\x8a@{\x14\xaeG\xe1\xdap@\x19\x04V\x0e\xad\xe4\x92@\xe7\xfb\xa9\xf1\xd2\xf3\x85@'
3777 | p1555
3778 | tp1556
3779 | bsS'indoor_269.png'
3780 | p1557
3781 | g2
3782 | (g3
3783 | (I0
3784 | tp1558
3785 | g5
3786 | tp1559
3787 | Rp1560
3788 | (I1
3789 | (L4L
3790 | tp1561
3791 | g12
3792 | I00
3793 | S'\xa0\x1a/\xdd$\x12o@X9\xb4\xc8v~s@B`\xe5\xd0"\xf9\x83@-\xb2\x9d\xef\xa7=\x8a@'
3794 | p1562
3795 | tp1563
3796 | bsS'indoor_243.png'
3797 | p1564
3798 | g2
3799 | (g3
3800 | (I0
3801 | tp1565
3802 | g5
3803 | tp1566
3804 | Rp1567
3805 | (I1
3806 | (L4L
3807 | tp1568
3808 | g12
3809 | I00
3810 | S'\x00\x00\x00\x00\x00\x90h@\x00\x00\x00\x00\x00\x10`@\x00\x00\x00\x00\x00\xc8s@\x00\x00\x00\x00\x00\x10o@'
3811 | p1569
3812 | tp1570
3813 | bsS'indoor_128.png'
3814 | p1571
3815 | g2
3816 | (g3
3817 | (I0
3818 | tp1572
3819 | g5
3820 | tp1573
3821 | Rp1574
3822 | (I1
3823 | (L4L
3824 | tp1575
3825 | g12
3826 | I00
3827 | S'\x04V\x0e-\xb2\x1dN@T\xe3\xa5\x9b\xc4\x80n@\x02+\x87\x16\xd9Jw@Zd;\xdfO@\x82@'
3828 | p1576
3829 | tp1577
3830 | bsS'indoor_028.png'
3831 | p1578
3832 | g2
3833 | (g3
3834 | (I0
3835 | tp1579
3836 | g5
3837 | tp1580
3838 | Rp1581
3839 | (I1
3840 | (L4L
3841 | tp1582
3842 | g12
3843 | I00
3844 | S"\x98n\x12\x83\xc0\x03\x80@'1\x08\xac\x1c2Y@\x00\x00\x00\x00\x00;\x8b@\x1b/\xdd$\x06\xbb|@"
3845 | p1583
3846 | tp1584
3847 | bsS'indoor_074.png'
3848 | p1585
3849 | g2
3850 | (g3
3851 | (I0
3852 | tp1586
3853 | g5
3854 | tp1587
3855 | Rp1588
3856 | (I1
3857 | (L4L
3858 | tp1589
3859 | g12
3860 | I00
3861 | S'\x04V\x0e-\xb2I\x8d@fffff\xbei@\xaeG\xe1z\x94\xab\x92@\xa2E\xb6\xf3\xfd\xd8}@'
3862 | p1590
3863 | tp1591
3864 | bsS'indoor_151.png'
3865 | p1592
3866 | g2
3867 | (g3
3868 | (I0
3869 | tp1593
3870 | g5
3871 | tp1594
3872 | Rp1595
3873 | (I1
3874 | (L4L
3875 | tp1596
3876 | g12
3877 | I00
3878 | S'\x00\x00\x00\x00\x00\x14\x84@\x00\x00\x00\x00\x00(\x7f@\x00\x00\x00\x00\x00t\x87@\x00\x00\x00\x00\x004\x84@'
3879 | p1597
3880 | tp1598
3881 | bsS'indoor_077.png'
3882 | p1599
3883 | g2
3884 | (g3
3885 | (I0
3886 | tp1600
3887 | g5
3888 | tp1601
3889 | Rp1602
3890 | (I1
3891 | (L4L
3892 | tp1603
3893 | g12
3894 | I00
3895 | S'sh\x91\xed|\xf9p@;\xdfO\x8d\x97\xb2r@\xf6(\\\x8f\xc2c\x81@\xe7\xfb\xa9\xf1\xd2\x89\x82@'
3896 | p1604
3897 | tp1605
3898 | bsS'indoor_289.png'
3899 | p1606
3900 | g2
3901 | (g3
3902 | (I0
3903 | tp1607
3904 | g5
3905 | tp1608
3906 | Rp1609
3907 | (I1
3908 | (L4L
3909 | tp1610
3910 | g12
3911 | I00
3912 | S'j\xbct\x93\x18\xe2v@\xdfO\x8d\x97n\xda\\@m\xe7\xfb\xa9\xf1\xed\x83@\xaa\xf1\xd2Mb$u@'
3913 | p1611
3914 | tp1612
3915 | bsS'indoor_166.png'
3916 | p1613
3917 | g2
3918 | (g3
3919 | (I0
3920 | tp1614
3921 | g5
3922 | tp1615
3923 | Rp1616
3924 | (I1
3925 | (L4L
3926 | tp1617
3927 | g12
3928 | I00
3929 | S'/\xdd$\x06\x81\xbfr@\xe3\xa5\x9b\xc4 \x88n@m\xe7\xfb\xa9\xf1\xb0\x84@\n\xd7\xa3p=\xff\x85@'
3930 | p1618
3931 | tp1619
3932 | bsS'indoor_196.png'
3933 | p1620
3934 | g2
3935 | (g3
3936 | (I0
3937 | tp1621
3938 | g5
3939 | tp1622
3940 | Rp1623
3941 | (I1
3942 | (L4L
3943 | tp1624
3944 | g12
3945 | I00
3946 | S'\x00\x00\x00\x00\x00\x94\x8f@\x00\x00\x00\x00\x00Pl@\x00\x00\x00\x00\x00\xea\x91@\x00\x00\x00\x00\x00\xa8v@'
3947 | p1625
3948 | tp1626
3949 | bsS'indoor_069.png'
3950 | p1627
3951 | g2
3952 | (g3
3953 | (I0
3954 | tp1628
3955 | g5
3956 | tp1629
3957 | Rp1630
3958 | (I1
3959 | (L4L
3960 | tp1631
3961 | g12
3962 | I00
3963 | S'Nb\x10X9Pe@;\xdfO\x8d\x97\xb2r@\x04V\x0e-\xb2=\x80@L7\x89A`f\x83@'
3964 | p1632
3965 | tp1633
3966 | bsS'indoor_033.png'
3967 | p1634
3968 | g2
3969 | (g3
3970 | (I0
3971 | tp1635
3972 | g5
3973 | tp1636
3974 | Rp1637
3975 | (I1
3976 | (L4L
3977 | tp1638
3978 | g12
3979 | I00
3980 | S'Nb\x10X9\xe0a@T\xe3\xa5\x9b\xc4\x1ck@\xc1\xca\xa1E\xb6\xb5~@o\x12\x83\xc0\xca\xfb\x82@'
3981 | p1639
3982 | tp1640
3983 | bsS'indoor_193.png'
3984 | p1641
3985 | g2
3986 | (g3
3987 | (I0
3988 | tp1642
3989 | g5
3990 | tp1643
3991 | Rp1644
3992 | (I1
3993 | (L4L
3994 | tp1645
3995 | g12
3996 | I00
3997 | S'\xe3\xa5\x9b\xc4\xa0\xa8\x96@\xf6(\\\x8f\xc2\t\x9b@\x9e\xef\xa7\xc6\xcb\x87\x99@\x83\xc0\xca\xa1Eh\x9d@'
3998 | p1646
3999 | tp1647
4000 | bsS'indoor_192.png'
4001 | p1648
4002 | g2
4003 | (g3
4004 | (I0
4005 | tp1649
4006 | g5
4007 | tp1650
4008 | Rp1651
4009 | (I1
4010 | (L4L
4011 | tp1652
4012 | g12
4013 | I00
4014 | S'\x00\x00\x00\x00\x00\xea\x9d@\x00\x00\x00\x00\x00\xba\x93@\x00\x00\x00\x00\x00\xaa\x9f@\x00\x00\x00\x00\x00\xfa\x95@'
4015 | p1653
4016 | tp1654
4017 | bsS'indoor_172.png'
4018 | p1655
4019 | g2
4020 | (g3
4021 | (I0
4022 | tp1656
4023 | g5
4024 | tp1657
4025 | Rp1658
4026 | (I1
4027 | (L4L
4028 | tp1659
4029 | g12
4030 | I00
4031 | S'\x19\x04V\x0e\xady\x93@\xd3Mb\x10X\xa9e@\x14\xaeG\xe1\xfa\xfa\x96@\xbe\x9f\x1a/\xdd\xb6w@'
4032 | p1660
4033 | tp1661
4034 | bsS'indoor_116.png'
4035 | p1662
4036 | g2
4037 | (g3
4038 | (I0
4039 | tp1663
4040 | g5
4041 | tp1664
4042 | Rp1665
4043 | (I1
4044 | (L4L
4045 | tp1666
4046 | g12
4047 | I00
4048 | S'\x00\x00\x00\x00\x00\xf1\xa4@\x00\x00\x00\x00\x00\x88\x7f@\x00\x00\x00\x00\x00\x91\xa9@\x00\x00\x00\x00\x00\xc4\x8f@'
4049 | p1667
4050 | tp1668
4051 | bsS'indoor_278.png'
4052 | p1669
4053 | g2
4054 | (g3
4055 | (I0
4056 | tp1670
4057 | g5
4058 | tp1671
4059 | Rp1672
4060 | (I1
4061 | (L4L
4062 | tp1673
4063 | g12
4064 | I00
4065 | S'\x81\x95C\x8bl\xf7j@\xe1z\x14\xaeG\xa1b@\xd9\xce\xf7S\xe3\x9by@\xbe\x9f\x1a/\xdd\xb6w@'
4066 | p1674
4067 | tp1675
4068 | bsS'indoor_126.png'
4069 | p1676
4070 | g2
4071 | (g3
4072 | (I0
4073 | tp1677
4074 | g5
4075 | tp1678
4076 | Rp1679
4077 | (I1
4078 | (L4L
4079 | tp1680
4080 | g12
4081 | I00
4082 | S'sh\x91\xed|\xf9p@\xc3\xf5(\\\x8f\x0ek@Zd;\xdfO@\x82@}?5^\xba\xd0\x80@'
4083 | p1681
4084 | tp1682
4085 | bsS'indoor_230.png'
4086 | p1683
4087 | g2
4088 | (g3
4089 | (I0
4090 | tp1684
4091 | g5
4092 | tp1685
4093 | Rp1686
4094 | (I1
4095 | (L4L
4096 | tp1687
4097 | g12
4098 | I00
4099 | S'\x00\x00\x00\x00\x00\xc8t@\x00\x00\x00\x00\x00 Z@\x00\x00\x00\x00\x00\x08|@\x00\x00\x00\x00\x00\x10l@'
4100 | p1688
4101 | tp1689
4102 | bsS'indoor_267.png'
4103 | p1690
4104 | g2
4105 | (g3
4106 | (I0
4107 | tp1691
4108 | g5
4109 | tp1692
4110 | Rp1693
4111 | (I1
4112 | (L4L
4113 | tp1694
4114 | g12
4115 | I00
4116 | S'u\x93\x18\x04V\x9eW@X9\xb4\xc8v\xae]@o\x12\x83\xc0\xca\xc9r@+\x87\x16\xd9\xceMt@'
4117 | p1695
4118 | tp1696
4119 | bsS'indoor_266.png'
4120 | p1697
4121 | g2
4122 | (g3
4123 | (I0
4124 | tp1698
4125 | g5
4126 | tp1699
4127 | Rp1700
4128 | (I1
4129 | (L4L
4130 | tp1701
4131 | g12
4132 | I00
4133 | S'\x00\x00\x00\x00\x00\x00%@\x00\x00\x00\x00\x00@I@\x00\x00\x00\x00\x00\xa0[@\x00\x00\x00\x00\x00\x10f@'
4134 | p1702
4135 | tp1703
4136 | bsS'indoor_008.png'
4137 | p1704
4138 | g2
4139 | (g3
4140 | (I0
4141 | tp1705
4142 | g5
4143 | tp1706
4144 | Rp1707
4145 | (I1
4146 | (L4L
4147 | tp1708
4148 | g12
4149 | I00
4150 | S'X9\xb4\xc8v~s@\xb2\x9d\xef\xa7\xc6\x83q@\xdd$\x06\x81\x95M\x84@\n\xd7\xa3p=P\x83@'
4151 | p1709
4152 | tp1710
4153 | bsS'indoor_286.png'
4154 | p1711
4155 | g2
4156 | (g3
4157 | (I0
4158 | tp1712
4159 | g5
4160 | tp1713
4161 | Rp1714
4162 | (I1
4163 | (L4L
4164 | tp1715
4165 | g12
4166 | I00
4167 | S'\xee|?5^\xaaP@j\xbct\x93\x18de@m\xe7\xfb\xa9\xf1\xb4t@\xa6\x9b\xc4 \xb0~y@'
4168 | p1716
4169 | tp1717
4170 | bsS'indoor_206.png'
4171 | p1718
4172 | g2
4173 | (g3
4174 | (I0
4175 | tp1719
4176 | g5
4177 | tp1720
4178 | Rp1721
4179 | (I1
4180 | (L4L
4181 | tp1722
4182 | g12
4183 | I00
4184 | S"\x02+\x87\x16\x19\xde\xa9@\xf8S\xe3\xa5\x9b\x80\x89@'1\x08\xac\x1c2\xab@\xaa\xf1\xd2M\xe2D\x90@"
4185 | p1723
4186 | tp1724
4187 | bsS'indoor_075.png'
4188 | p1725
4189 | g2
4190 | (g3
4191 | (I0
4192 | tp1726
4193 | g5
4194 | tp1727
4195 | Rp1728
4196 | (I1
4197 | (L4L
4198 | tp1729
4199 | g12
4200 | I00
4201 | S"\x8f\xc2\xf5(\\'t@1\x08\xac\x1cZ\xc0m@\xb0rh\x91\xedJ\x85@o\x12\x83\xc0\xca\xfb\x82@"
4202 | p1730
4203 | tp1731
4204 | bsS'indoor_098.png'
4205 | p1732
4206 | g2
4207 | (g3
4208 | (I0
4209 | tp1733
4210 | g5
4211 | tp1734
4212 | Rp1735
4213 | (I1
4214 | (L4L
4215 | tp1736
4216 | g12
4217 | I00
4218 | S'\x9a\x99\x99\x99\x99\xd5e@\x9e\xef\xa7\xc6KGQ@\x89A`\xe5\xd0\x0c~@\xa4p=\n\xd7sw@'
4219 | p1737
4220 | tp1738
4221 | bsS'indoor_099.png'
4222 | p1739
4223 | g2
4224 | (g3
4225 | (I0
4226 | tp1740
4227 | g5
4228 | tp1741
4229 | Rp1742
4230 | (I1
4231 | (L4L
4232 | tp1743
4233 | g12
4234 | I00
4235 | S"Nb\x10X9\xe0a@\x08\xac\x1cZd'g@\x89A`\xe5\xd0\x0c~@j\xbct\x93\x18\x01\x81@"
4236 | p1744
4237 | tp1745
4238 | bsS'indoor_142.png'
4239 | p1746
4240 | g2
4241 | (g3
4242 | (I0
4243 | tp1747
4244 | g5
4245 | tp1748
4246 | Rp1749
4247 | (I1
4248 | (L4L
4249 | tp1750
4250 | g12
4251 | I00
4252 | S'ffff\xe6\xf6\x99@o\x12\x83\xc0J\xf4\x92@sh\x91\xed\xfc\xa5\x9f@\xd9\xce\xf7S\xe34\x99@'
4253 | p1751
4254 | tp1752
4255 | bsS'indoor_239.png'
4256 | p1753
4257 | g2
4258 | (g3
4259 | (I0
4260 | tp1754
4261 | g5
4262 | tp1755
4263 | Rp1756
4264 | (I1
4265 | (L4L
4266 | tp1757
4267 | g12
4268 | I00
4269 | S'Zd;\xdfO\x1dt@\xd1"\xdb\xf9~"o@F\xb6\xf3\xfd\xd4l\x85@\xa4p=\n\xd7\xcd\x85@'
4270 | p1758
4271 | tp1759
4272 | bsS'indoor_188.png'
4273 | p1760
4274 | g2
4275 | (g3
4276 | (I0
4277 | tp1761
4278 | g5
4279 | tp1762
4280 | Rp1763
4281 | (I1
4282 | (L4L
4283 | tp1764
4284 | g12
4285 | I00
4286 | S'T\xe3\xa5\x9bD\xd5\x95@9\xb4\xc8v\xbe\xe5}@d;\xdfO\r\xb7\x9a@\xb6\xf3\xfd\xd4xI\x89@'
4287 | p1765
4288 | tp1766
4289 | bsS'indoor_101.png'
4290 | p1767
4291 | g2
4292 | (g3
4293 | (I0
4294 | tp1768
4295 | g5
4296 | tp1769
4297 | Rp1770
4298 | (I1
4299 | (L4L
4300 | tp1771
4301 | g12
4302 | I00
4303 | S'\x00\x00\x00\x00\x00\xc4\x88@\x00\x00\x00\x00\x00\xc4\x85@\x00\x00\x00\x00\x00b\x94@\x00\x00\x00\x00\x00b\x93@'
4304 | p1772
4305 | tp1773
4306 | bsS'indoor_083.png'
4307 | p1774
4308 | g2
4309 | (g3
4310 | (I0
4311 | tp1775
4312 | g5
4313 | tp1776
4314 | Rp1777
4315 | (I1
4316 | (L4L
4317 | tp1778
4318 | g12
4319 | I00
4320 | S'\x00\x00\x00\x00\x00Hp@\x00\x00\x00\x00\x00\x90g@\x00\x00\x00\x00\x00$\x80@\x00\x00\x00\x00\x00H~@'
4321 | p1779
4322 | tp1780
4323 | bsS'indoor_194.png'
4324 | p1781
4325 | g2
4326 | (g3
4327 | (I0
4328 | tp1782
4329 | g5
4330 | tp1783
4331 | Rp1784
4332 | (I1
4333 | (L4L
4334 | tp1785
4335 | g12
4336 | I00
4337 | S"\xd3Mb\x10\x188\xa5@}?5^\xba\xf9\x96@'1\x08\xac\x1c\xb4\xa6@\xb0rh\x91m\xb2\x99@"
4338 | p1786
4339 | tp1787
4340 | bsS'indoor_104.png'
4341 | p1788
4342 | g2
4343 | (g3
4344 | (I0
4345 | tp1789
4346 | g5
4347 | tp1790
4348 | Rp1791
4349 | (I1
4350 | (L4L
4351 | tp1792
4352 | g12
4353 | I00
4354 | S'\xb8\x1e\x85\xebQ8\x98@\xe3\xa5\x9b\xc4 \xfa|@\x04V\x0e-2#\x9c@\xaa\xf1\xd2Mbi\x87@'
4355 | p1793
4356 | tp1794
4357 | bsS'indoor_105.png'
4358 | p1795
4359 | g2
4360 | (g3
4361 | (I0
4362 | tp1796
4363 | g5
4364 | tp1797
4365 | Rp1798
4366 | (I1
4367 | (L4L
4368 | tp1799
4369 | g12
4370 | I00
4371 | S"^\xbaI\x0c\x02X\x92@\x10X9\xb4\xc8:\x80@\x1b/\xdd$\x06'\x96@\x89A`\xe5\xd0\xd8\x87@"
4372 | p1800
4373 | tp1801
4374 | bsS'indoor_043.png'
4375 | p1802
4376 | g2
4377 | (g3
4378 | (I0
4379 | tp1803
4380 | g5
4381 | tp1804
4382 | Rp1805
4383 | (I1
4384 | (L4L
4385 | tp1806
4386 | g12
4387 | I00
4388 | S'\xecQ\xb8\x1e\x85Et@h\x91\xed|?\x85d@\xaeG\xe1z\x14\x89\x81@\xe7\xfb\xa9\xf1\xd2\x9fx@'
4389 | p1807
4390 | tp1808
4391 | bsS'indoor_190.png'
4392 | p1809
4393 | g2
4394 | (g3
4395 | (I0
4396 | tp1810
4397 | g5
4398 | tp1811
4399 | Rp1812
4400 | (I1
4401 | (L4L
4402 | tp1813
4403 | g12
4404 | I00
4405 | S'\xf2\xd2MbP(\xa0@b\x10X9\xb4R}@=\n\xd7\xa3\xb0O\xa2@u\x93\x18\x04V\xfd\x86@'
4406 | p1814
4407 | tp1815
4408 | bsS'indoor_117.png'
4409 | p1816
4410 | g2
4411 | (g3
4412 | (I0
4413 | tp1817
4414 | g5
4415 | tp1818
4416 | Rp1819
4417 | (I1
4418 | (L4L
4419 | tp1820
4420 | g12
4421 | I00
4422 | S'\x00\x00\x00\x00\x00"\x98@\x00\x00\x00\x00\x00q\xa5@\x00\x00\x00\x00\x00\xf1\xa0@\x00\x00\x00\x00\x00\xb1\xa9@'
4423 | p1821
4424 | tp1822
4425 | bsS'indoor_133.png'
4426 | p1823
4427 | g2
4428 | (g3
4429 | (I0
4430 | tp1824
4431 | g5
4432 | tp1825
4433 | Rp1826
4434 | (I1
4435 | (L4L
4436 | tp1827
4437 | g12
4438 | I00
4439 | S'\x00\x00\x00\x00\x00ht@\x00\x00\x00\x00\x00Pl@\x00\x00\x00\x00\x00\xe8|@\x00\x00\x00\x00\x00\xe8v@'
4440 | p1828
4441 | tp1829
4442 | bsS'indoor_114.png'
4443 | p1830
4444 | g2
4445 | (g3
4446 | (I0
4447 | tp1831
4448 | g5
4449 | tp1832
4450 | Rp1833
4451 | (I1
4452 | (L4L
4453 | tp1834
4454 | g12
4455 | I00
4456 | S'\xb0rh\x91\xed\xdd\x8b@T\xe3\xa5\x9b\xc4A\x81@\xf2\xd2Mb\x10`\x94@\xcb\xa1E\xb6\xf3\x00\x8d@'
4457 | p1835
4458 | tp1836
4459 | bsS'indoor_022.png'
4460 | p1837
4461 | g2
4462 | (g3
4463 | (I0
4464 | tp1838
4465 | g5
4466 | tp1839
4467 | Rp1840
4468 | (I1
4469 | (L4L
4470 | tp1841
4471 | g12
4472 | I00
4473 | S'\x00\x00\x00\x00\x00\xc8w@\x00\x00\x00\x00\x00\x90e@\x00\x00\x00\x00\x00$\x85@\x00\x00\x00\x00\x00\xc8}@'
4474 | p1842
4475 | tp1843
4476 | bsS'indoor_294.png'
4477 | p1844
4478 | g2
4479 | (g3
4480 | (I0
4481 | tp1845
4482 | g5
4483 | tp1846
4484 | Rp1847
4485 | (I1
4486 | (L4L
4487 | tp1848
4488 | g12
4489 | I00
4490 | S'\xd7\xa3p=\n7~@D\x8bl\xe7\xfb9`@\x04V\x0e-\xb2b\x84@\xdd$\x06\x81\x95Qt@'
4491 | p1849
4492 | tp1850
4493 | bsS'indoor_208.png'
4494 | p1851
4495 | g2
4496 | (g3
4497 | (I0
4498 | tp1852
4499 | g5
4500 | tp1853
4501 | Rp1854
4502 | (I1
4503 | (L4L
4504 | tp1855
4505 | g12
4506 | I00
4507 | S'\x00\x00\x00\x00\x00\xea\x9a@\x00\x00\x00\x00\x00hp@\x00\x00\x00\x00\x00\x9a\x9c@\x00\x00\x00\x00\x00hx@'
4508 | p1856
4509 | tp1857
4510 | bsS'indoor_279.png'
4511 | p1858
4512 | g2
4513 | (g3
4514 | (I0
4515 | tp1859
4516 | g5
4517 | tp1860
4518 | Rp1861
4519 | (I1
4520 | (L4L
4521 | tp1862
4522 | g12
4523 | I00
4524 | S"\xe3\xa5\x9b\xc4 |k@d;\xdfO\x8d\xdfh@'1\x08\xac\x1c\xeey@\xa4p=\n\xd7\xab{@"
4525 | p1863
4526 | tp1864
4527 | bsS'indoor_234.png'
4528 | p1865
4529 | g2
4530 | (g3
4531 | (I0
4532 | tp1866
4533 | g5
4534 | tp1867
4535 | Rp1868
4536 | (I1
4537 | (L4L
4538 | tp1869
4539 | g12
4540 | I00
4541 | S'\x00\x00\x00\x00\x00\xc8y@\x00\x00\x00\x00\x00 R@\x00\x00\x00\x00\x00\x08\x7f@\x00\x00\x00\x00\x00\x10f@'
4542 | p1870
4543 | tp1871
4544 | bsS'indoor_244.png'
4545 | p1872
4546 | g2
4547 | (g3
4548 | (I0
4549 | tp1873
4550 | g5
4551 | tp1874
4552 | Rp1875
4553 | (I1
4554 | (L4L
4555 | tp1876
4556 | g12
4557 | I00
4558 | S'\x00\x00\x00\x00\x00hu@\x00\x00\x00\x00\x00Ph@\x00\x00\x00\x00\x00h~@\x00\x00\x00\x00\x00(t@'
4559 | p1877
4560 | tp1878
4561 | bsS'indoor_063.png'
4562 | p1879
4563 | g2
4564 | (g3
4565 | (I0
4566 | tp1880
4567 | g5
4568 | tp1881
4569 | Rp1882
4570 | (I1
4571 | (L4L
4572 | tp1883
4573 | g12
4574 | I00
4575 | S'\xa6\x9b\xc4 \xb0Zm@Nb\x10X9Pe@\n\xd7\xa3p=\x1a\x81@h\x91\xed|?/~@'
4576 | p1884
4577 | tp1885
4578 | bsS'indoor_201.png'
4579 | p1886
4580 | g2
4581 | (g3
4582 | (I0
4583 | tp1887
4584 | g5
4585 | tp1888
4586 | Rp1889
4587 | (I1
4588 | (L4L
4589 | tp1890
4590 | g12
4591 | I00
4592 | S'\x00\x00\x00\x00\x00\x08}@\x00\x00\x00\x00\x00@N@\x00\x00\x00\x00\x00\xc4\x81@\x00\x00\x00\x00\x00\x10d@'
4593 | p1891
4594 | tp1892
4595 | bsS'indoor_060.png'
4596 | p1893
4597 | g2
4598 | (g3
4599 | (I0
4600 | tp1894
4601 | g5
4602 | tp1895
4603 | Rp1896
4604 | (I1
4605 | (L4L
4606 | tp1897
4607 | g12
4608 | I00
4609 | S'\x00\x00\x00\x00\x00\x88w@\x00\x00\x00\x00\x00\x88~@\x00\x00\x00\x00\x00\xc4\x89@\x00\x00\x00\x00\x00"\x90@'
4610 | p1898
4611 | tp1899
4612 | bsS'indoor_066.png'
4613 | p1900
4614 | g2
4615 | (g3
4616 | (I0
4617 | tp1901
4618 | g5
4619 | tp1902
4620 | Rp1903
4621 | (I1
4622 | (L4L
4623 | tp1904
4624 | g12
4625 | I00
4626 | S'`\xe5\xd0"\xdb\x93v@%\x06\x81\x95C[`@\xecQ\xb8\x1e\x85\x8a\x81@\xe7\xfb\xa9\xf1\xd2\x0fu@'
4627 | p1905
4628 | tp1906
4629 | bsS'indoor_175.png'
4630 | p1907
4631 | g2
4632 | (g3
4633 | (I0
4634 | tp1908
4635 | g5
4636 | tp1909
4637 | Rp1910
4638 | (I1
4639 | (L4L
4640 | tp1911
4641 | g12
4642 | I00
4643 | S'\x00\x00\x00\x00\x00\xc4\x87@\x00\x00\x00\x00\x00\xc8u@\x00\x00\x00\x00\x00\xa4\x8a@\x00\x00\x00\x00\x00\x08|@'
4644 | p1912
4645 | tp1913
4646 | bsS'indoor_054.png'
4647 | p1914
4648 | g2
4649 | (g3
4650 | (I0
4651 | tp1915
4652 | g5
4653 | tp1916
4654 | Rp1917
4655 | (I1
4656 | (L4L
4657 | tp1918
4658 | g12
4659 | I00
4660 | S'\xdb\xf9~j\xbc\x1cx@\x04V\x0e-\xb2\xd5[@\x83\xc0\xca\xa1EH\x86@\x1b/\xdd$\x06\xbb|@'
4661 | p1919
4662 | tp1920
4663 | bsS'indoor_068.png'
4664 | p1921
4665 | g2
4666 | (g3
4667 | (I0
4668 | tp1922
4669 | g5
4670 | tp1923
4671 | Rp1924
4672 | (I1
4673 | (L4L
4674 | tp1925
4675 | g12
4676 | I00
4677 | S'\xe7\xfb\xa9\xf1\xd2!g@\xac\x1cZd;\xf7r@%\x06\x81\x95C\x1b|@\xee|?5^\xd7\x82@'
4678 | p1926
4679 | tp1927
4680 | bsS'indoor_084.png'
4681 | p1928
4682 | g2
4683 | (g3
4684 | (I0
4685 | tp1929
4686 | g5
4687 | tp1930
4688 | Rp1931
4689 | (I1
4690 | (L4L
4691 | tp1932
4692 | g12
4693 | I00
4694 | S'\x12\x83\xc0\xca\xa1\xc5x@33333X\x80@\xbaI\x0c\x02+\xf1\x86@\xa0\x1a/\xdd$\x8a\x8d@'
4695 | p1933
4696 | tp1934
4697 | bsS'indoor_222.png'
4698 | p1935
4699 | g2
4700 | (g3
4701 | (I0
4702 | tp1936
4703 | g5
4704 | tp1937
4705 | Rp1938
4706 | (I1
4707 | (L4L
4708 | tp1939
4709 | g12
4710 | I00
4711 | S'\x00\x00\x00\x00\x00\x08z@\x00\x00\x00\x00\x00 Z@\x00\x00\x00\x00\x00\x84\x83@\x00\x00\x00\x00\x00\x88u@'
4712 | p1940
4713 | tp1941
4714 | bsS'indoor_246.png'
4715 | p1942
4716 | g2
4717 | (g3
4718 | (I0
4719 | tp1943
4720 | g5
4721 | tp1944
4722 | Rp1945
4723 | (I1
4724 | (L4L
4725 | tp1946
4726 | g12
4727 | I00
4728 | S'\x00\x00\x00\x00\x00\xe8\x7f@\x00\x00\x00\x00\x00\xa0Y@\x00\x00\x00\x00\x00\xd4\x82@\x00\x00\x00\x00\x00\xd0j@'
4729 | p1947
4730 | tp1948
4731 | bsS'indoor_276.png'
4732 | p1949
4733 | g2
4734 | (g3
4735 | (I0
4736 | tp1950
4737 | g5
4738 | tp1951
4739 | Rp1952
4740 | (I1
4741 | (L4L
4742 | tp1953
4743 | g12
4744 | I00
4745 | S'\xb2\x9d\xef\xa7\xc6#_@V\x0e-\xb2\x9dEs@\x85\xebQ\xb8\x1e\xe3{@)\\\x8f\xc2\xf5\xd5\x84@'
4746 | p1954
4747 | tp1955
4748 | bsS'indoor_014.png'
4749 | p1956
4750 | g2
4751 | (g3
4752 | (I0
4753 | tp1957
4754 | g5
4755 | tp1958
4756 | Rp1959
4757 | (I1
4758 | (L4L
4759 | tp1960
4760 | g12
4761 | I00
4762 | S'\xd1"\xdb\xf9~"o@\xfc\xa9\xf1\xd2M\x02c@\xe7\xfb\xa9\xf1\xd2\x0b\x85@o\x12\x83\xc0\xca&\x83@'
4763 | p1961
4764 | tp1962
4765 | bsS'indoor_015.png'
4766 | p1963
4767 | g2
4768 | (g3
4769 | (I0
4770 | tp1964
4771 | g5
4772 | tp1965
4773 | Rp1966
4774 | (I1
4775 | (L4L
4776 | tp1967
4777 | g12
4778 | I00
4779 | S'm\xe7\xfb\xa9\xf1Bf@h\x91\xed|?\x9dj@\xa4p=\n\xd7\xab{@%\x06\x81\x95C\x1b|@'
4780 | p1968
4781 | tp1969
4782 | bsS'indoor_207.png'
4783 | p1970
4784 | g2
4785 | (g3
4786 | (I0
4787 | tp1971
4788 | g5
4789 | tp1972
4790 | Rp1973
4791 | (I1
4792 | (L4L
4793 | tp1974
4794 | g12
4795 | I00
4796 | S'\x00\x00\x00\x00\x00$\x8f@\x00\x00\x00\x00\x00\xc8t@\x00\x00\x00\x00\x002\x91@\x00\x00\x00\x00\x00\xc8{@'
4797 | p1975
4798 | tp1976
4799 | bsS'indoor_029.png'
4800 | p1977
4801 | g2
4802 | (g3
4803 | (I0
4804 | tp1978
4805 | g5
4806 | tp1979
4807 | Rp1980
4808 | (I1
4809 | (L4L
4810 | tp1981
4811 | g12
4812 | I00
4813 | S'%\x06\x81\x95C\x15q@%\x06\x81\x95C\x15q@\xa4p=\n\xd7.\x86@`\xe5\xd0"\xdb\xf0\x86@'
4814 | p1982
4815 | tp1983
4816 | bsS'indoor_145.png'
4817 | p1984
4818 | g2
4819 | (g3
4820 | (I0
4821 | tp1985
4822 | g5
4823 | tp1986
4824 | Rp1987
4825 | (I1
4826 | (L4L
4827 | tp1988
4828 | g12
4829 | I00
4830 | S'\xf2\xd2Mb\x90/\x94@\x89A`\xe5\xd0I\x84@\xcf\xf7S\xe3\xa5\xde\x99@J\x0c\x02+\x07\x1a\x92@'
4831 | p1989
4832 | tp1990
4833 | bsS'indoor_229.png'
4834 | p1991
4835 | g2
4836 | (g3
4837 | (I0
4838 | tp1992
4839 | g5
4840 | tp1993
4841 | Rp1994
4842 | (I1
4843 | (L4L
4844 | tp1995
4845 | g12
4846 | I00
4847 | S'\x00\x00\x00\x00\x00\x10i@\x00\x00\x00\x00\x00 U@\x00\x00\x00\x00\x00\xc8t@\x00\x00\x00\x00\x00\x90f@'
4848 | p1996
4849 | tp1997
4850 | bsS'indoor_070.png'
4851 | p1998
4852 | g2
4853 | (g3
4854 | (I0
4855 | tp1999
4856 | g5
4857 | tp2000
4858 | Rp2001
4859 | (I1
4860 | (L4L
4861 | tp2002
4862 | g12
4863 | I00
4864 | S'\x00\x00\x00\x00\x00\xa4\x8b@\x00\x00\x00\x00\x00\xc8w@\x00\x00\x00\x00\x00\x12\x92@\x00\x00\x00\x00\x00d\x84@'
4865 | p2003
4866 | tp2004
4867 | bsS'indoor_155.png'
4868 | p2005
4869 | g2
4870 | (g3
4871 | (I0
4872 | tp2006
4873 | g5
4874 | tp2007
4875 | Rp2008
4876 | (I1
4877 | (L4L
4878 | tp2009
4879 | g12
4880 | I00
4881 | S'\xa2E\xb6\xf3\xfdf\x95@\xcf\xf7S\xe3\xa5\xd4\x83@}?5^:l\x99@\x85\xebQ\xb8\x1e\xdf\x8b@'
4882 | p2010
4883 | tp2011
4884 | bsS'indoor_064.png'
4885 | p2012
4886 | g2
4887 | (g3
4888 | (I0
4889 | tp2013
4890 | g5
4891 | tp2014
4892 | Rp2015
4893 | (I1
4894 | (L4L
4895 | tp2016
4896 | g12
4897 | I00
4898 | S'\x00\x00\x00\x00\x00\x10b@\x00\x00\x00\x00\x00@F@\x00\x00\x00\x00\x00Hp@\x00\x00\x00\x00\x00\x90b@'
4899 | p2017
4900 | tp2018
4901 | bsS'indoor_092.png'
4902 | p2019
4903 | g2
4904 | (g3
4905 | (I0
4906 | tp2020
4907 | g5
4908 | tp2021
4909 | Rp2022
4910 | (I1
4911 | (L4L
4912 | tp2023
4913 | g12
4914 | I00
4915 | S'\xe5\xd0"\xdb\xf9Ni@%\x06\x81\x95C\x95z@-\xb2\x9d\xef\xa7b\x83@\xe5\xd0"\xdb\xf9\xc8\x8a@'
4916 | p2024
4917 | tp2025
4918 | bsS'indoor_251.png'
4919 | p2026
4920 | g2
4921 | (g3
4922 | (I0
4923 | tp2027
4924 | g5
4925 | tp2028
4926 | Rp2029
4927 | (I1
4928 | (L4L
4929 | tp2030
4930 | g12
4931 | I00
4932 | S'\x00\x00\x00\x00\x00\xa8q@\x00\x00\x00\x00\x00@G@\x00\x00\x00\x00\x00(y@\x00\x00\x00\x00\x00Pg@'
4933 | p2031
4934 | tp2032
4935 | bsS'indoor_052.png'
4936 | p2033
4937 | g2
4938 | (g3
4939 | (I0
4940 | tp2034
4941 | g5
4942 | tp2035
4943 | Rp2036
4944 | (I1
4945 | (L4L
4946 | tp2037
4947 | g12
4948 | I00
4949 | S'\x9e\xef\xa7\xc6KGQ@{\x14\xaeG\xe1\xeaS@\xac\x1cZd;i{@R\xb8\x1e\x85\xebc}@'
4950 | p2038
4951 | tp2039
4952 | bsS'indoor_053.png'
4953 | p2040
4954 | g2
4955 | (g3
4956 | (I0
4957 | tp2041
4958 | g5
4959 | tp2042
4960 | Rp2043
4961 | (I1
4962 | (L4L
4963 | tp2044
4964 | g12
4965 | I00
4966 | S'+\x87\x16\xd9\xce\x8f\x85@fffff\xcal@\xee|?5^\xd5\x92@\xe9&1\x08\xacn\x86@'
4967 | p2045
4968 | tp2046
4969 | bsS'indoor_036.png'
4970 | p2047
4971 | g2
4972 | (g3
4973 | (I0
4974 | tp2048
4975 | g5
4976 | tp2049
4977 | Rp2050
4978 | (I1
4979 | (L4L
4980 | tp2051
4981 | g12
4982 | I00
4983 | S'X9\xb4\xc8v~s@{\x14\xaeG\xe1\xdap@L7\x89A`\x9f\x85@o\x12\x83\xc0\xca\xfb\x82@'
4984 | p2052
4985 | tp2053
4986 | bsS'indoor_001.png'
4987 | p2054
4988 | g2
4989 | (g3
4990 | (I0
4991 | tp2055
4992 | g5
4993 | tp2056
4994 | Rp2057
4995 | (I1
4996 | (L4L
4997 | tp2058
4998 | g12
4999 | I00
5000 | S'\x0e-\xb2\x9d\xef\xe1{@u\x93\x18\x04V\x96T@\xc3\xf5(\\\x8f1\x84@T\xe3\xa5\x9b\xc4\xa6q@'
5001 | p2059
5002 | tp2060
5003 | bsS'indoor_025.png'
5004 | p2061
5005 | g2
5006 | (g3
5007 | (I0
5008 | tp2062
5009 | g5
5010 | tp2063
5011 | Rp2064
5012 | (I1
5013 | (L4L
5014 | tp2065
5015 | g12
5016 | I00
5017 | S'-\xb2\x9d\xef\xa7b\x83@\xa8\xc6K7\x89\xd7x@\x7fj\xbct\x13\x87\x91@%\x06\x81\x95C\x17\x8c@'
5018 | p2066
5019 | tp2067
5020 | bsS'indoor_002.png'
5021 | p2068
5022 | g2
5023 | (g3
5024 | (I0
5025 | tp2069
5026 | g5
5027 | tp2070
5028 | Rp2071
5029 | (I1
5030 | (L4L
5031 | tp2072
5032 | g12
5033 | I00
5034 | S'\xdfO\x8d\x97n\xc2h@\xaa\xf1\xd2Mb\x9cg@\x04V\x0e-\xb2=\x80@h\x91\xed|?/~@'
5035 | p2073
5036 | tp2074
5037 | bsS'indoor_240.png'
5038 | p2075
5039 | g2
5040 | (g3
5041 | (I0
5042 | tp2076
5043 | g5
5044 | tp2077
5045 | Rp2078
5046 | (I1
5047 | (L4L
5048 | tp2079
5049 | g12
5050 | I00
5051 | S'\xd8\xa3p=\n\x97O@\xe3\xa5\x9b\xc4 \xa0H@P\x8d\x97n\x12\xc6\x80@\xa4p=\n\xd71}@'
5052 | p2080
5053 | tp2081
5054 | bsS'indoor_017.png'
5055 | p2082
5056 | g2
5057 | (g3
5058 | (I0
5059 | tp2083
5060 | g5
5061 | tp2084
5062 | Rp2085
5063 | (I1
5064 | (L4L
5065 | tp2086
5066 | g12
5067 | I00
5068 | S'\x00\x00\x00\x00\x00\x90c@\x00\x00\x00\x00\x00Hp@\x00\x00\x00\x00\x00H{@\x00\x00\x00\x00\x00d\x80@'
5069 | p2087
5070 | tp2088
5071 | bsS'indoor_009.png'
5072 | p2089
5073 | g2
5074 | (g3
5075 | (I0
5076 | tp2090
5077 | g5
5078 | tp2091
5079 | Rp2092
5080 | (I1
5081 | (L4L
5082 | tp2093
5083 | g12
5084 | I00
5085 | S'\xf6(\\\x8f\xc2\x07p@\x81\x95C\x8bl\x1fj@\xfa~j\xbct\x93{@V\x0e-\xb2\x9dIw@'
5086 | p2094
5087 | tp2095
5088 | bsS'indoor_298.png'
5089 | p2096
5090 | g2
5091 | (g3
5092 | (I0
5093 | tp2097
5094 | g5
5095 | tp2098
5096 | Rp2099
5097 | (I1
5098 | (L4L
5099 | tp2100
5100 | g12
5101 | I00
5102 | S'\x00\x00\x00\x00\x00\x08s@\x00\x00\x00\x00\x00 Z@\x00\x00\x00\x00\x00Hy@\x00\x00\x00\x00\x00\x90j@'
5103 | p2101
5104 | tp2102
5105 | bsS'indoor_284.png'
5106 | p2103
5107 | g2
5108 | (g3
5109 | (I0
5110 | tp2104
5111 | g5
5112 | tp2105
5113 | Rp2106
5114 | (I1
5115 | (L4L
5116 | tp2107
5117 | g12
5118 | I00
5119 | S'\x17\xd9\xce\xf7S\xa1u@\xaa\xf1\xd2Mb\xd0>@\xbe\x9f\x1a/\xdd\xb2\x87@\x81\x95C\x8bl\xefz@'
5120 | p2108
5121 | tp2109
5122 | bs.
--------------------------------------------------------------------------------
/data/boxesLFPWTest.pkl:
--------------------------------------------------------------------------------
1 | (dp0
2 | S'image_0094.png'
3 | p1
4 | cnumpy.core.multiarray
5 | _reconstruct
6 | p2
7 | (cnumpy
8 | ndarray
9 | p3
10 | (I0
11 | tp4
12 | S'b'
13 | p5
14 | tp6
15 | Rp7
16 | (I1
17 | (L4L
18 | tp8
19 | cnumpy
20 | dtype
21 | p9
22 | (S'f8'
23 | p10
24 | I0
25 | I1
26 | tp11
27 | Rp12
28 | (I3
29 | S'<'
30 | p13
31 | NNNI-1
32 | I-1
33 | I0
34 | tp14
35 | bI00
36 | S'\xd3!-5Z\x0b\\@q\xad\xd4\x19\xc0\x11a@\r|6w\x9e{v@$.\xf0\xf7\x9d;w@'
37 | p15
38 | tp16
39 | bsS'image_0208.png'
40 | p17
41 | g2
42 | (g3
43 | (I0
44 | tp18
45 | g5
46 | tp19
47 | Rp20
48 | (I1
49 | (L4L
50 | tp21
51 | g12
52 | I00
53 | S'\xed[RZd\xddS@\xe8\xcf\xc81\x03\xf9Y@\xb1\n\xe5\x8e\xa8?j@\x8c# p\xd6.p@'
54 | p22
55 | tp23
56 | bsS'image_0171.png'
57 | p24
58 | g2
59 | (g3
60 | (I0
61 | tp25
62 | g5
63 | tp26
64 | Rp27
65 | (I1
66 | (L4L
67 | tp28
68 | g12
69 | I00
70 | S't\xcc\x1e\r\\_p@\xd8\x1c1\xc4\x9b\xe6T@Dr\x8d*\x0etv@\xa4\xcb\xf6|X\x03f@'
71 | p29
72 | tp30
73 | bsS'image_0097.png'
74 | p31
75 | g2
76 | (g3
77 | (I0
78 | tp32
79 | g5
80 | tp33
81 | Rp34
82 | (I1
83 | (L4L
84 | tp35
85 | g12
86 | I00
87 | S"i\x9ak0\xaaT_@\xd8'\x7f\x0c\x90\x19c@\xae\xc4\x91\xa5^\x86r@^Kz\xe8\xeb\xads@"
88 | p36
89 | tp37
90 | bsS'image_0146.png'
91 | p38
92 | g2
93 | (g3
94 | (I0
95 | tp39
96 | g5
97 | tp40
98 | Rp41
99 | (I1
100 | (L4L
101 | tp42
102 | g12
103 | I00
104 | S"\x96c\xa1\xbc\xa9\x85^@\xc8j4\x87\xaf+g@6\xafX\xe1'\xadt@c\x87\xae\x89\x98\xfaw@"
105 | p43
106 | tp44
107 | bsS'image_0239.png'
108 | p45
109 | g2
110 | (g3
111 | (I0
112 | tp46
113 | g5
114 | tp47
115 | Rp48
116 | (I1
117 | (L4L
118 | tp49
119 | g12
120 | I00
121 | S'j\r\x01\x86\xf5\xe9f@\xd8\xc9\x17W\xcbK`@\xdc\xa0\x0cE\xaa\xc9v@d\xb80\xeawzu@'
122 | p50
123 | tp51
124 | bsS'image_0089.png'
125 | p52
126 | g2
127 | (g3
128 | (I0
129 | tp53
130 | g5
131 | tp54
132 | Rp55
133 | (I1
134 | (L4L
135 | tp56
136 | g12
137 | I00
138 | S'\x94f\xae\x83\xb5\x07i@?z\xde\xbdY\x19Z@\xb6\xcc(>%lw@pa\x88\x90\xa9\xe9p@'
139 | p57
140 | tp58
141 | bsS'image_0152.png'
142 | p59
143 | g2
144 | (g3
145 | (I0
146 | tp60
147 | g5
148 | tp61
149 | Rp62
150 | (I1
151 | (L4L
152 | tp63
153 | g12
154 | I00
155 | S"\xf4\xd5lT8\xd73@}'O\xbcy\xc0R@n\x97Z\xf8T\x8c_@&\xd13\xb5\x90\x83e@"
156 | p64
157 | tp65
158 | bsS'image_0136.png'
159 | p66
160 | g2
161 | (g3
162 | (I0
163 | tp67
164 | g5
165 | tp68
166 | Rp69
167 | (I1
168 | (L4L
169 | tp70
170 | g12
171 | I00
172 | S'\x8f\xc1\xd0U\xfa\xc2\x7f@\x897\xe91\xa9\xcd\x7f@\x9c\xcf\x8bjA\x0b\x91@\x1e\xb2\x85\xb3\x95\x88\x91@'
173 | p71
174 | tp72
175 | bsS'image_0198.png'
176 | p73
177 | g2
178 | (g3
179 | (I0
180 | tp74
181 | g5
182 | tp75
183 | Rp76
184 | (I1
185 | (L4L
186 | tp77
187 | g12
188 | I00
189 | S'$W2\x0em\x1ec@_ms\xa1\xb5;S@\x1f\x04\x05\xee\xa0\x8as@\xc6\x01\xb0\xa7q\xf3i@'
190 | p78
191 | tp79
192 | bsS'image_0106.png'
193 | p80
194 | g2
195 | (g3
196 | (I0
197 | tp81
198 | g5
199 | tp82
200 | Rp83
201 | (I1
202 | (L4L
203 | tp84
204 | g12
205 | I00
206 | S'\x9a\x18a4\xe9\x17B@\x0b]\xb6k\xd0\xa3i@\x88\xd0SE\x06\xcfp@\xb1\xb8\xe4\xa1\x1eby@'
207 | p85
208 | tp86
209 | bsS'image_0186.png'
210 | p87
211 | g2
212 | (g3
213 | (I0
214 | tp88
215 | g5
216 | tp89
217 | Rp90
218 | (I1
219 | (L4L
220 | tp91
221 | g12
222 | I00
223 | S'\x13]\xf9\x8b*\x16Y@\xc8\xdeF\x06\xf4\xc2e@\xceHkE\xcb\xa3p@\x1d{\xd94m\xcbu@'
224 | p92
225 | tp93
226 | bsS'image_0234.png'
227 | p94
228 | g2
229 | (g3
230 | (I0
231 | tp95
232 | g5
233 | tp96
234 | Rp97
235 | (I1
236 | (L4L
237 | tp98
238 | g12
239 | I00
240 | S'\xa1d\xc8\xa4]\xc3`@\x0c\x8f\x87\xe0\x90M\\@\xb7\x11\xf3\xd3H\xcdp@S\x86as\xfc\xfdn@'
241 | p99
242 | tp100
243 | bsS'image_0215.png'
244 | p101
245 | g2
246 | (g3
247 | (I0
248 | tp102
249 | g5
250 | tp103
251 | Rp104
252 | (I1
253 | (L4L
254 | tp105
255 | g12
256 | I00
257 | S'\x85\xce\xa0\xfb#e_@`\x88,\xce\xb6\x9d\\@z\xd4\x98QIut@,\xf7\xf0\xb9\xa6Ar@'
258 | p106
259 | tp107
260 | bsS'image_0158.png'
261 | p108
262 | g2
263 | (g3
264 | (I0
265 | tp109
266 | g5
267 | tp110
268 | Rp111
269 | (I1
270 | (L4L
271 | tp112
272 | g12
273 | I00
274 | S'E\xf9\xbe\x93\xb5\x1cV@\xfcTq\xc2T\x16V@\xee\xd8\x0e\xe3\x86\x1fk@\n\xcc\xde\xe4\xdaCj@'
275 | p113
276 | tp114
277 | bsS'image_0036.png'
278 | p115
279 | g2
280 | (g3
281 | (I0
282 | tp116
283 | g5
284 | tp117
285 | Rp118
286 | (I1
287 | (L4L
288 | tp119
289 | g12
290 | I00
291 | S"\x8b\xa7\xc6'\x98\xa3`@H\xf2\xb5\x1e\x0e\xfb^@\xea\x0556\xce/s@\xb6.\xff\xa9\xc5\x9cr@"
292 | p120
293 | tp121
294 | bsS'image_0095.png'
295 | p122
296 | g2
297 | (g3
298 | (I0
299 | tp123
300 | g5
301 | tp124
302 | Rp125
303 | (I1
304 | (L4L
305 | tp126
306 | g12
307 | I00
308 | S'\xf2\xd1\xcf\x87\xe0\xf2`@\xdf\xd8=\x96\xf5=[@\x83\x99\xfay!ur@D\x0cSX\x14\x1ft@'
309 | p127
310 | tp128
311 | bsS'image_0078.png'
312 | p129
313 | g2
314 | (g3
315 | (I0
316 | tp130
317 | g5
318 | tp131
319 | Rp132
320 | (I1
321 | (L4L
322 | tp133
323 | g12
324 | I00
325 | S'\x88\x8e\xcf\x0fw\xc6[@L\xbc\xc3g\xcd\xd6W@\x95\xdf\x8a\x1f-6l@u>@\x81\xba\x8fi@'
326 | p134
327 | tp135
328 | bsS'image_0079.png'
329 | p136
330 | g2
331 | (g3
332 | (I0
333 | tp137
334 | g5
335 | tp138
336 | Rp139
337 | (I1
338 | (L4L
339 | tp140
340 | g12
341 | I00
342 | S'X!\x8d`%WY@jL\xf6:\xf7Q_@\xaa\xb7\xdc\xa76\x9aq@\xe6lB1\x82\x9br@'
343 | p141
344 | tp142
345 | bsS'image_0162.png'
346 | p143
347 | g2
348 | (g3
349 | (I0
350 | tp144
351 | g5
352 | tp145
353 | Rp146
354 | (I1
355 | (L4L
356 | tp147
357 | g12
358 | I00
359 | S'*\x91\x9f\xe8=\xa3t@#\xfcA\x137\x83S@A\xfd\x1d@\x81\x00\x81@d\xd8\x17\xbfWhq@'
360 | p148
361 | tp149
362 | bsS'image_0121.png'
363 | p150
364 | g2
365 | (g3
366 | (I0
367 | tp151
368 | g5
369 | tp152
370 | Rp153
371 | (I1
372 | (L4L
373 | tp154
374 | g12
375 | I00
376 | S'\xed\xc8\xf5\xbe(\xdc`@\xd1\x9a\xdfc\xb0"q@\xed\x15AK\x7fuy@$\xe6\xd2\xa7\r\x15\x81@'
377 | p155
378 | tp156
379 | bsS'image_0063.png'
380 | p157
381 | g2
382 | (g3
383 | (I0
384 | tp158
385 | g5
386 | tp159
387 | Rp160
388 | (I1
389 | (L4L
390 | tp161
391 | g12
392 | I00
393 | S'{\xa1c\xad.lr@\xc4\xcd\x01\xafX\x08}@xt\x81\xaeo\xdc\x88@\x9c\x8aP\xaf\x84*\x8e@'
394 | p162
395 | tp163
396 | bsS'image_0228.png'
397 | p164
398 | g2
399 | (g3
400 | (I0
401 | tp165
402 | g5
403 | tp166
404 | Rp167
405 | (I1
406 | (L4L
407 | tp168
408 | g12
409 | I00
410 | S"%,\xec\x82??\\@\x97\x9b\xd3\xb1\x87\x0b`@\xee\xe9\x89>`\xc0n@42\x16'&]|\x18is@\xa2\x80\xfe\xb3u\xd9o@'
700 | p288
701 | tp289
702 | bsS'image_0183.png'
703 | p290
704 | g2
705 | (g3
706 | (I0
707 | tp291
708 | g5
709 | tp292
710 | Rp293
711 | (I1
712 | (L4L
713 | tp294
714 | g12
715 | I00
716 | S'1\xeb\xf9\x8aq?_@G\x18}\xff\x914j@\xd0\x1e\x88\xa1\x92*t@\xa8da\x06V\x00{@'
717 | p295
718 | tp296
719 | bsS'image_0088.png'
720 | p297
721 | g2
722 | (g3
723 | (I0
724 | tp298
725 | g5
726 | tp299
727 | Rp300
728 | (I1
729 | (L4L
730 | tp301
731 | g12
732 | I00
733 | S'(\xf6\xc2\x8anGY@\xbc\x0c\x97\x85\x95\x94Z@\x86\xa1\xc0\xefi\xd7h@\x0e\xf6/Z\x87+j@'
734 | p302
735 | tp303
736 | bsS'image_0029.png'
737 | p304
738 | g2
739 | (g3
740 | (I0
741 | tp305
742 | g5
743 | tp306
744 | Rp307
745 | (I1
746 | (L4L
747 | tp308
748 | g12
749 | I00
750 | S'\xd9Rv\x85\x1a\x1c\\@ \xe4)\x95\x0e\x05P@\x94\xd6D\xbd\xf2\xd1o@\xf0\rk\xb5x\xddk@'
751 | p309
752 | tp310
753 | bsS'image_0188.png'
754 | p311
755 | g2
756 | (g3
757 | (I0
758 | tp312
759 | g5
760 | tp313
761 | Rp314
762 | (I1
763 | (L4L
764 | tp315
765 | g12
766 | I00
767 | S'\xd3m=\x03n+q@\xce\xaen\xe1\x0e\x8ed@\xea#*\xb5,\x91{@~\r\xa4"\xc6\xact@'
768 | p316
769 | tp317
770 | bsS'image_0041.png'
771 | p318
772 | g2
773 | (g3
774 | (I0
775 | tp319
776 | g5
777 | tp320
778 | Rp321
779 | (I1
780 | (L4L
781 | tp322
782 | g12
783 | I00
784 | S'qF\n\x99\x82\x8d\\@\xeb\xa36M\xd3\xd2b@\x8er\xe6]\x0b\x15t@\xe62?^\x14[v@'
785 | p323
786 | tp324
787 | bsS'image_0189.png'
788 | p325
789 | g2
790 | (g3
791 | (I0
792 | tp326
793 | g5
794 | tp327
795 | Rp328
796 | (I1
797 | (L4L
798 | tp329
799 | g12
800 | I00
801 | S'\xa6\x0e\x12\x9a!\xbah@\xd1\xa8\x81[\x1d\x90\\@\x10\xf3\xb2\xdd\x82\x86u@zX\xbb\x9c\x92\xbbo@'
802 | p330
803 | tp331
804 | bsS'image_0018.png'
805 | p332
806 | g2
807 | (g3
808 | (I0
809 | tp333
810 | g5
811 | tp334
812 | Rp335
813 | (I1
814 | (L4L
815 | tp336
816 | g12
817 | I00
818 | S'%\xce5\x99\x99\xecX@R\xc2\x12\n+ek@\xbc\x03R\x0e8Aq@\\\xf1\r-\xa7\xb8x@'
819 | p337
820 | tp338
821 | bsS'image_0214.png'
822 | p339
823 | g2
824 | (g3
825 | (I0
826 | tp340
827 | g5
828 | tp341
829 | Rp342
830 | (I1
831 | (L4L
832 | tp343
833 | g12
834 | I00
835 | S'\x06\xeb\nX\xa3TM@F\xc2\xf4V\x8b\xd8[@\xd6`|\xa3T\x10p@\x1c\xadL\xf0\xd8\xb4r@'
836 | p344
837 | tp345
838 | bsS'image_0015.png'
839 | p346
840 | g2
841 | (g3
842 | (I0
843 | tp347
844 | g5
845 | tp348
846 | Rp349
847 | (I1
848 | (L4L
849 | tp350
850 | g12
851 | I00
852 | S'r\x0e\x1f@\x8a\xbad@\xab\x1c21l\xc6j@\xe1\xe8^\xe5G1y@\xeaw\xa4\xedky{@'
853 | p351
854 | tp352
855 | bsS'image_0007.png'
856 | p353
857 | g2
858 | (g3
859 | (I0
860 | tp354
861 | g5
862 | tp355
863 | Rp356
864 | (I1
865 | (L4L
866 | tp357
867 | g12
868 | I00
869 | S'\xbd\\\x0c$I:m@6$-\xe5\xa7\xbda@\\/TiK@{@0M#\xfc\xdf[t@'
870 | p358
871 | tp359
872 | bsS'image_0011.png'
873 | p360
874 | g2
875 | (g3
876 | (I0
877 | tp361
878 | g5
879 | tp362
880 | Rp363
881 | (I1
882 | (L4L
883 | tp364
884 | g12
885 | I00
886 | S'i\x1a\xa1\xdeJ\xf0a@4{\x93[QH_@\xae\xa3\xfdf}\x1cs@H\xf5\x91Nl\xf6q@'
887 | p365
888 | tp366
889 | bsS'image_0025.png'
890 | p367
891 | g2
892 | (g3
893 | (I0
894 | tp368
895 | g5
896 | tp369
897 | Rp370
898 | (I1
899 | (L4L
900 | tp371
901 | g12
902 | I00
903 | S'\xe7\xeb\x06\xed\x1e\xe1]@J\xad\x1b@p\xead@\x06E\xbeD\xb8wq@[)\xf2\xdf\xc7\xfas@'
904 | p372
905 | tp373
906 | bsS'image_0165.png'
907 | p374
908 | g2
909 | (g3
910 | (I0
911 | tp375
912 | g5
913 | tp376
914 | Rp377
915 | (I1
916 | (L4L
917 | tp378
918 | g12
919 | I00
920 | S'\x82.\xd3\x8f\x1c\xa8A@\xaf\xea\xa2\x9b\xc2\xf0]@(\xf1S)i\x16o@pM\x98\xa9a\xd2t@'
921 | p379
922 | tp380
923 | bsS'image_0026.png'
924 | p381
925 | g2
926 | (g3
927 | (I0
928 | tp382
929 | g5
930 | tp383
931 | Rp384
932 | (I1
933 | (L4L
934 | tp385
935 | g12
936 | I00
937 | S'\x08\xda}\x9d\x06\xf9W@\xfbE\xc3\xcb\xd2R`@\x9f&\xdd+\x17\xefk@\xf9\xa4fL\x87no@'
938 | p386
939 | tp387
940 | bsS'image_0159.png'
941 | p388
942 | g2
943 | (g3
944 | (I0
945 | tp389
946 | g5
947 | tp390
948 | Rp391
949 | (I1
950 | (L4L
951 | tp392
952 | g12
953 | I00
954 | S'T\xa9\xd7\xfb3\xaec@"\xf5\xc1\x06\x9d|Y@\xa0\n\xce\xf0\x99cs@\xfe\xf9\xee27\x1dq@'
955 | p393
956 | tp394
957 | bsS'image_0175.png'
958 | p395
959 | g2
960 | (g3
961 | (I0
962 | tp396
963 | g5
964 | tp397
965 | Rp398
966 | (I1
967 | (L4L
968 | tp399
969 | g12
970 | I00
971 | S'\xc3\xd5!\x8f"lo@\xac\xd0\xe6P\x95wU@\xa6\x9b\x93\'V\x94y@\x80=\xc4{_ep@'
972 | p400
973 | tp401
974 | bsS'image_0084.png'
975 | p402
976 | g2
977 | (g3
978 | (I0
979 | tp403
980 | g5
981 | tp404
982 | Rp405
983 | (I1
984 | (L4L
985 | tp406
986 | g12
987 | I00
988 | S'*\xe1]F\xc7\xacP@\xed\xc3=\x8e\xf9(`@\xd8\xe8cn\x0c\\j@\x08\x83ax\x9e;p@'
989 | p407
990 | tp408
991 | bsS'image_0072.png'
992 | p409
993 | g2
994 | (g3
995 | (I0
996 | tp410
997 | g5
998 | tp411
999 | Rp412
1000 | (I1
1001 | (L4L
1002 | tp413
1003 | g12
1004 | I00
1005 | S'\x0c\xa5\x9bi_\x84|@\xf4\xc4\xceo\x83ba@\xc1\x11\xee\xdfj\x8a\x85@\xef\x80\xa1\xfd\xf6\x8ex@'
1006 | p414
1007 | tp415
1008 | bsS'image_0193.png'
1009 | p416
1010 | g2
1011 | (g3
1012 | (I0
1013 | tp417
1014 | g5
1015 | tp418
1016 | Rp419
1017 | (I1
1018 | (L4L
1019 | tp420
1020 | g12
1021 | I00
1022 | S"}\x0e\xb5g\xe4\x98X@M\xb0\xab\xf4\x00\x90X@\xc2x%\xcc\x8d\x93l@\xda'\xaa\x85\xff\x97n@"
1023 | p421
1024 | tp422
1025 | bsS'image_0181.png'
1026 | p423
1027 | g2
1028 | (g3
1029 | (I0
1030 | tp424
1031 | g5
1032 | tp425
1033 | Rp426
1034 | (I1
1035 | (L4L
1036 | tp427
1037 | g12
1038 | I00
1039 | S'\x1a~\xcc{]HV@\xaah;\xe6\xf0?V@\xf3\xc0\x19B\xd1\xbbm@\xabK\xe2\x8c\x07\xc0n@'
1040 | p428
1041 | tp429
1042 | bsS'image_0185.png'
1043 | p430
1044 | g2
1045 | (g3
1046 | (I0
1047 | tp431
1048 | g5
1049 | tp432
1050 | Rp433
1051 | (I1
1052 | (L4L
1053 | tp434
1054 | g12
1055 | I00
1056 | S'X\x93A\x8f\xdc\xc6l@\xb9\xcc\xe3\x19A=[@U\xd1\x08\xbe$\xafv@\xae\xf5\xc1y\r6n@'
1057 | p435
1058 | tp436
1059 | bsS'image_0128.png'
1060 | p437
1061 | g2
1062 | (g3
1063 | (I0
1064 | tp438
1065 | g5
1066 | tp439
1067 | Rp440
1068 | (I1
1069 | (L4L
1070 | tp441
1071 | g12
1072 | I00
1073 | S'1E\x1d@\xd1\x14h@\xec\xa3\x7f\xf9\x90\xc8]@\xf9%\x98$*\x7f\x81@V\x92\x81\xe7\x0ff~@'
1074 | p442
1075 | tp443
1076 | bsS'image_0001.png'
1077 | p444
1078 | g2
1079 | (g3
1080 | (I0
1081 | tp445
1082 | g5
1083 | tp446
1084 | Rp447
1085 | (I1
1086 | (L4L
1087 | tp448
1088 | g12
1089 | I00
1090 | S'+\xc6\x14\xe4\xed\xe0b@\xfe\x85S\xe2\x99Bp@\x06\rd\x13\x16\x1ez@_\xeb\x88\x12\x13\x17\x80@'
1091 | p449
1092 | tp450
1093 | bsS'image_0210.png'
1094 | p451
1095 | g2
1096 | (g3
1097 | (I0
1098 | tp452
1099 | g5
1100 | tp453
1101 | Rp454
1102 | (I1
1103 | (L4L
1104 | tp455
1105 | g12
1106 | I00
1107 | S'\x98Pp\xc9[\xdcv@\xc7\xff\x0f,\xac\x03[@\x1f#\x05Rs|\x7f@\xe4\x8f\xef\xff5\xe5m@'
1108 | p456
1109 | tp457
1110 | bsS'image_0173.png'
1111 | p458
1112 | g2
1113 | (g3
1114 | (I0
1115 | tp459
1116 | g5
1117 | tp460
1118 | Rp461
1119 | (I1
1120 | (L4L
1121 | tp462
1122 | g12
1123 | I00
1124 | S'\xf8o\xf4\xe1WQp@\xd4\xe3\x1d\x81\xb1PU@`\xeb\r$D\x07w@\xbd\xe8\xc1D1\x14h@'
1125 | p463
1126 | tp464
1127 | bsS'image_0024.png'
1128 | p465
1129 | g2
1130 | (g3
1131 | (I0
1132 | tp466
1133 | g5
1134 | tp467
1135 | Rp468
1136 | (I1
1137 | (L4L
1138 | tp469
1139 | g12
1140 | I00
1141 | S'f\xd9H\xd7>\x0cZ@L\x04\x84\xd7D\x90[@\xff\xae\xb6\x9a\x85\x88l@sD\xd4\x9a\x88Jm@'
1142 | p470
1143 | tp471
1144 | bsS'image_0170.png'
1145 | p472
1146 | g2
1147 | (g3
1148 | (I0
1149 | tp473
1150 | g5
1151 | tp474
1152 | Rp475
1153 | (I1
1154 | (L4L
1155 | tp476
1156 | g12
1157 | I00
1158 | S'v\x14\x9d\x9c\xe7\x13I@67\x9e\xd0/\xb2[@\x0b\xbf\x01\x1dr\xe3d@\x89\x95)\x1e\x90wl@'
1159 | p477
1160 | tp478
1161 | bsS'image_0054.png'
1162 | p479
1163 | g2
1164 | (g3
1165 | (I0
1166 | tp480
1167 | g5
1168 | tp481
1169 | Rp482
1170 | (I1
1171 | (L4L
1172 | tp483
1173 | g12
1174 | I00
1175 | S'\xfe\xe8\x80\x8c\xcfLO@v\x84CSZ\xffX@t\x87\x12\xe1\xbb\\i@\xf5\xbe\x98S\x7f\xa9p@'
1176 | p484
1177 | tp485
1178 | bsS'image_0048.png'
1179 | p486
1180 | g2
1181 | (g3
1182 | (I0
1183 | tp487
1184 | g5
1185 | tp488
1186 | Rp489
1187 | (I1
1188 | (L4L
1189 | tp490
1190 | g12
1191 | I00
1192 | S'\xfa=\x12\x16\xef\xb42@\x1d\x85\x9f\xf6\x88\xc3Y@\xdc\xab\x1d\x89e\xab`@\xa8$p\\BBi@'
1193 | p491
1194 | tp492
1195 | bsS'image_0144.png'
1196 | p493
1197 | g2
1198 | (g3
1199 | (I0
1200 | tp494
1201 | g5
1202 | tp495
1203 | Rp496
1204 | (I1
1205 | (L4L
1206 | tp497
1207 | g12
1208 | I00
1209 | S'N\xbf\xcbg*\xe2c@Ne\x9bU\x8aWU@\x8bx\xae\xa8$`q@\xe9t?\xdd\xdf\x82g@'
1210 | p498
1211 | tp499
1212 | bsS'image_0074.png'
1213 | p500
1214 | g2
1215 | (g3
1216 | (I0
1217 | tp501
1218 | g5
1219 | tp502
1220 | Rp503
1221 | (I1
1222 | (L4L
1223 | tp504
1224 | g12
1225 | I00
1226 | S'X\x14bN\x01\x9e]@h\xeb{Q,\xfap@VT\xfa\xbd\xefZ{@\\-p\xe4\xbd\x98\x81@'
1227 | p505
1228 | tp506
1229 | bsS'image_0220.png'
1230 | p507
1231 | g2
1232 | (g3
1233 | (I0
1234 | tp508
1235 | g5
1236 | tp509
1237 | Rp510
1238 | (I1
1239 | (L4L
1240 | tp511
1241 | g12
1242 | I00
1243 | S'\xc8\xe0\r\n$%<@#\xa4I+\xccSg@\x9d\x16\xddq\xd3bi@\x1a \x06\x95\xa4=w@'
1244 | p512
1245 | tp513
1246 | bsS'image_0006.png'
1247 | p514
1248 | g2
1249 | (g3
1250 | (I0
1251 | tp515
1252 | g5
1253 | tp516
1254 | Rp517
1255 | (I1
1256 | (L4L
1257 | tp518
1258 | g12
1259 | I00
1260 | S"\xe8\xbb\x88'\x0e\xc6_@p\xff\x87B&\xfee@\x90\xdf\xfc\xf9\xe0aq@=Z[\xe3dAs@"
1261 | p519
1262 | tp520
1263 | bsS'image_0139.png'
1264 | p521
1265 | g2
1266 | (g3
1267 | (I0
1268 | tp522
1269 | g5
1270 | tp523
1271 | Rp524
1272 | (I1
1273 | (L4L
1274 | tp525
1275 | g12
1276 | I00
1277 | S'\x01+\xf2^d7h@\xc4\xe0\xcc&J\xacP@\x14:pU\xcd\tt@\x06\x7fV\xf1U\x9cf@'
1278 | p526
1279 | tp527
1280 | bsS'image_0172.png'
1281 | p528
1282 | g2
1283 | (g3
1284 | (I0
1285 | tp529
1286 | g5
1287 | tp530
1288 | Rp531
1289 | (I1
1290 | (L4L
1291 | tp532
1292 | g12
1293 | I00
1294 | S'J\x7f\xb7\\\x8a\xfdE@\xee\xeb\xf9/\xef\x9aU@r\xf9\xbfl\x03%d@\x96\x0f\x8fm\x18si@'
1295 | p533
1296 | tp534
1297 | bsS'image_0052.png'
1298 | p535
1299 | g2
1300 | (g3
1301 | (I0
1302 | tp536
1303 | g5
1304 | tp537
1305 | Rp538
1306 | (I1
1307 | (L4L
1308 | tp539
1309 | g12
1310 | I00
1311 | S"\x98\x91|6=W\x84@h\x8f\xf2\xe8'\x87w@|_i\xcdB4\x90@\x14u\xcfX\xdc\xd4\x87@"
1312 | p540
1313 | tp541
1314 | bsS'image_0053.png'
1315 | p542
1316 | g2
1317 | (g3
1318 | (I0
1319 | tp543
1320 | g5
1321 | tp544
1322 | Rp545
1323 | (I1
1324 | (L4L
1325 | tp546
1326 | g12
1327 | I00
1328 | S'&Q\x18\xbe\xda\xb9P@n\x98\xc0s<$[@\xd0\xd1\xafK\xa6vi@\x87d@u\x11\xf6l@'
1329 | p547
1330 | tp548
1331 | bsS'image_0160.png'
1332 | p549
1333 | g2
1334 | (g3
1335 | (I0
1336 | tp550
1337 | g5
1338 | tp551
1339 | Rp552
1340 | (I1
1341 | (L4L
1342 | tp553
1343 | g12
1344 | I00
1345 | S'\xb4\xfbMO\x8e\x1aJ@\x98\xc8\x14-a\xfca@\x95\x9f6an\xf5l@\x97\xcc\xc3?r\x16s@'
1346 | p554
1347 | tp555
1348 | bsS'image_0229.png'
1349 | p556
1350 | g2
1351 | (g3
1352 | (I0
1353 | tp557
1354 | g5
1355 | tp558
1356 | Rp559
1357 | (I1
1358 | (L4L
1359 | tp560
1360 | g12
1361 | I00
1362 | S'\x18,\x999p!`@l(\xc8\x97\x8a#Q@\x90\x03z\xe7\xb6\xe9s@wNJ]q\xdfp@'
1363 | p561
1364 | tp562
1365 | bsS'image_0061.png'
1366 | p563
1367 | g2
1368 | (g3
1369 | (I0
1370 | tp564
1371 | g5
1372 | tp565
1373 | Rp566
1374 | (I1
1375 | (L4L
1376 | tp567
1377 | g12
1378 | I00
1379 | S'\xc3\xee\xb2\x05\x0bPc@\xb3R\x91G\xf5\xe7R@\x0f\xc2@\x01e/q@\x82\xdb\x11a\x83@f@'
1380 | p568
1381 | tp569
1382 | bsS'image_0147.png'
1383 | p570
1384 | g2
1385 | (g3
1386 | (I0
1387 | tp571
1388 | g5
1389 | tp572
1390 | Rp573
1391 | (I1
1392 | (L4L
1393 | tp574
1394 | g12
1395 | I00
1396 | S'\x0b\x01\xe6\x0b\x8f\xb9\\@\x03\xd7\x1a\x87\xe5\xf0e@?D\x88A\x11Pv@\x7f/\x1cB \x1az@'
1397 | p575
1398 | tp576
1399 | bsS'image_0045.png'
1400 | p577
1401 | g2
1402 | (g3
1403 | (I0
1404 | tp578
1405 | g5
1406 | tp579
1407 | Rp580
1408 | (I1
1409 | (L4L
1410 | tp581
1411 | g12
1412 | I00
1413 | S'x\xdf\x80i\x13\x86h@\xf1\xbe\x01\xd3&\x0cY@D\x90?K\xf6,v@D\x90?K\xf6,p@'
1414 | p582
1415 | tp583
1416 | bsS'image_0237.png'
1417 | p584
1418 | g2
1419 | (g3
1420 | (I0
1421 | tp585
1422 | g5
1423 | tp586
1424 | Rp587
1425 | (I1
1426 | (L4L
1427 | tp588
1428 | g12
1429 | I00
1430 | S'\xc2\xbdq\x96p\xe9P@\xc2\xbdq\x96p\xe9\\@\x1f!\xc7\xb4Gkk@\x90\x90c\xda\xa3\xb5p@'
1431 | p589
1432 | tp590
1433 | bsS'image_0142.png'
1434 | p591
1435 | g2
1436 | (g3
1437 | (I0
1438 | tp592
1439 | g5
1440 | tp593
1441 | Rp594
1442 | (I1
1443 | (L4L
1444 | tp595
1445 | g12
1446 | I00
1447 | S'gL\xea+\x11]a@7C\xbd\xbb\xefOW@J\x90\xfa\xe43\x1fu@EOz\xf9Y\x15q@'
1448 | p596
1449 | tp597
1450 | bsS'image_0143.png'
1451 | p598
1452 | g2
1453 | (g3
1454 | (I0
1455 | tp599
1456 | g5
1457 | tp600
1458 | Rp601
1459 | (I1
1460 | (L4L
1461 | tp602
1462 | g12
1463 | I00
1464 | S's\x93\xa0F\xc1d[@\xa3\x1a\xca \xb3Xe@\xbft\x9e\xb2>!u@\xe37\xcet-^w@'
1465 | p603
1466 | tp604
1467 | bsS'image_0126.png'
1468 | p605
1469 | g2
1470 | (g3
1471 | (I0
1472 | tp606
1473 | g5
1474 | tp607
1475 | Rp608
1476 | (I1
1477 | (L4L
1478 | tp609
1479 | g12
1480 | I00
1481 | S'\xf2Ec5\x9c\x87[@\xf1I}\xcfL\xe7p@\x84.\xa7\xf2\x18\xd6w@\x08[A\x98Y\\\x81@'
1482 | p610
1483 | tp611
1484 | bsS'image_0107.png'
1485 | p612
1486 | g2
1487 | (g3
1488 | (I0
1489 | tp613
1490 | g5
1491 | tp614
1492 | Rp615
1493 | (I1
1494 | (L4L
1495 | tp616
1496 | g12
1497 | I00
1498 | S'\xce\x13&e\xb8\x9fY@0(\x0c{\xd6>[@\xb0<\x03\xd4\xceBn@\x0c\x9d\xf2\xc8<\xb1l@'
1499 | p617
1500 | tp618
1501 | bsS'image_0200.png'
1502 | p619
1503 | g2
1504 | (g3
1505 | (I0
1506 | tp620
1507 | g5
1508 | tp621
1509 | Rp622
1510 | (I1
1511 | (L4L
1512 | tp623
1513 | g12
1514 | I00
1515 | S'\x8eP.\xd9e\x0eg@\xe8\x803Q\x13)y@\x06p\xdd\x8d\xd2|\x85@X0\x86]\x15\x8e\x8b@'
1516 | p624
1517 | tp625
1518 | bsS'image_0014.png'
1519 | p626
1520 | g2
1521 | (g3
1522 | (I0
1523 | tp627
1524 | g5
1525 | tp628
1526 | Rp629
1527 | (I1
1528 | (L4L
1529 | tp630
1530 | g12
1531 | I00
1532 | S'\x0eG\xf1p\xf7\x8eu@2.cl\x07\xa4{@z\xf70M\x17S\x8a@\x0c\x1aGP\xa4\x96\x8c@'
1533 | p631
1534 | tp632
1535 | bsS'image_0230.png'
1536 | p633
1537 | g2
1538 | (g3
1539 | (I0
1540 | tp634
1541 | g5
1542 | tp635
1543 | Rp636
1544 | (I1
1545 | (L4L
1546 | tp637
1547 | g12
1548 | I00
1549 | S'\xf0$+\xb8\xb6\xa3R@-\xa3wQH:Z@I\x1d\x00\xa9\xa8\xe6g@5\x1fd\xddz\xedj@'
1550 | p638
1551 | tp639
1552 | bsS'image_0081.png'
1553 | p640
1554 | g2
1555 | (g3
1556 | (I0
1557 | tp641
1558 | g5
1559 | tp642
1560 | Rp643
1561 | (I1
1562 | (L4L
1563 | tp644
1564 | g12
1565 | I00
1566 | S'\x9f\x1e\x80yU\x13p@\xb7\xf2\xed\xb8\xfc\x9fW@b\xde>\x06^\xbdv@\x86.\x97C\xe1ei@'
1567 | p645
1568 | tp646
1569 | bsS'image_0023.png'
1570 | p647
1571 | g2
1572 | (g3
1573 | (I0
1574 | tp648
1575 | g5
1576 | tp649
1577 | Rp650
1578 | (I1
1579 | (L4L
1580 | tp651
1581 | g12
1582 | I00
1583 | S'(\\\xef\xe5g[a@\x97\x90\xea.\x01h]@\xfct6\x1a `q@\x8e\x050L\xc4pn@'
1584 | p652
1585 | tp653
1586 | bsS'image_0205.png'
1587 | p654
1588 | g2
1589 | (g3
1590 | (I0
1591 | tp655
1592 | g5
1593 | tp656
1594 | Rp657
1595 | (I1
1596 | (L4L
1597 | tp658
1598 | g12
1599 | I00
1600 | S'\xd0z\xf82\x11QR@C\xacY\xc2\xd5\x14U@\xc7\xf5\xef\xfalKh@\x16\xc8\xa2\x9f\x8f\x0fk@'
1601 | p659
1602 | tp660
1603 | bsS'image_0157.png'
1604 | p661
1605 | g2
1606 | (g3
1607 | (I0
1608 | tp662
1609 | g5
1610 | tp663
1611 | Rp664
1612 | (I1
1613 | (L4L
1614 | tp665
1615 | g12
1616 | I00
1617 | S'p\x18iB\xeami@RN\xab\x87\xcd\x98Z@\xcfX\xd2c\x8d0t@\x16\xdfgB;\x80k@'
1618 | p666
1619 | tp667
1620 | bsS'image_0145.png'
1621 | p668
1622 | g2
1623 | (g3
1624 | (I0
1625 | tp669
1626 | g5
1627 | tp670
1628 | Rp671
1629 | (I1
1630 | (L4L
1631 | tp672
1632 | g12
1633 | I00
1634 | S'\xf8\xf7y\xc7N\xf5l@^DsQ,\xefc@\x04\x04C\x9cX\xf5x@\xd1]F\xd7i\xf8t@'
1635 | p673
1636 | tp674
1637 | bsS'image_0042.png'
1638 | p675
1639 | g2
1640 | (g3
1641 | (I0
1642 | tp676
1643 | g5
1644 | tp677
1645 | Rp678
1646 | (I1
1647 | (L4L
1648 | tp679
1649 | g12
1650 | I00
1651 | S'\x10I\x9fe\xafn`@\x10I\x9fe\xafnd@x[0M\xa8\xb8q@x[0M\xa8\xb8s@'
1652 | p680
1653 | tp681
1654 | bsS'image_0184.png'
1655 | p682
1656 | g2
1657 | (g3
1658 | (I0
1659 | tp683
1660 | g5
1661 | tp684
1662 | Rp685
1663 | (I1
1664 | (L4L
1665 | tp686
1666 | g12
1667 | I00
1668 | S'Jz\xbdM\xc8Ba@\x94^\x94$r[`@\xebeO\xe6olq@\xb456-b"p@'
1669 | p687
1670 | tp688
1671 | bsS'image_0204.png'
1672 | p689
1673 | g2
1674 | (g3
1675 | (I0
1676 | tp690
1677 | g5
1678 | tp691
1679 | Rp692
1680 | (I1
1681 | (L4L
1682 | tp693
1683 | g12
1684 | I00
1685 | S'\xe4E4\xf9\xedyA@fPe\xed\xa0>`@\xe1\x80\x84D^~l@\xe8_\xce\xd9A/t@'
1686 | p694
1687 | tp695
1688 | bsS'image_0233.png'
1689 | p696
1690 | g2
1691 | (g3
1692 | (I0
1693 | tp697
1694 | g5
1695 | tp698
1696 | Rp699
1697 | (I1
1698 | (L4L
1699 | tp700
1700 | g12
1701 | I00
1702 | S's\xf6\xfb\xaf\x17Lu@47jH\xe1\x86R@[\xf1\xd0\xd7\xb2\xcb}@\x9b)\xfe`\x16\xb7h@'
1703 | p701
1704 | tp702
1705 | bsS'image_0221.png'
1706 | p703
1707 | g2
1708 | (g3
1709 | (I0
1710 | tp704
1711 | g5
1712 | tp705
1713 | Rp706
1714 | (I1
1715 | (L4L
1716 | tp707
1717 | g12
1718 | I00
1719 | S'0\xb6\xeai\x07.N@\xf0B\xb6E\xfa\x1ea@\xbc\xaf\xbc\x9b|\xabg@\x90"|\x83z\x9fp@'
1720 | p708
1721 | tp709
1722 | bsS'image_0117.png'
1723 | p710
1724 | g2
1725 | (g3
1726 | (I0
1727 | tp711
1728 | g5
1729 | tp712
1730 | Rp713
1731 | (I1
1732 | (L4L
1733 | tp714
1734 | g12
1735 | I00
1736 | S'\\\xa1\x93\xb2\xeeX`@\\\xa1\x93\xb2\xeeXd@R/\xb6\xa6\x88\xc3q@R/\xb6\xa6\x88\xc3s@'
1737 | p715
1738 | tp716
1739 | bsS'image_0116.png'
1740 | p717
1741 | g2
1742 | (g3
1743 | (I0
1744 | tp718
1745 | g5
1746 | tp719
1747 | Rp720
1748 | (I1
1749 | (L4L
1750 | tp721
1751 | g12
1752 | I00
1753 | S'\x94\xefr\xd0\xf9\xc0K@\x1f\xa8&\x0f$\xc3]@\xdf*\rw\xaf\xebp@\xdc\xc8{\x07\xfe\x8bs@'
1754 | p722
1755 | tp723
1756 | bsS'image_0177.png'
1757 | p724
1758 | g2
1759 | (g3
1760 | (I0
1761 | tp725
1762 | g5
1763 | tp726
1764 | Rp727
1765 | (I1
1766 | (L4L
1767 | tp728
1768 | g12
1769 | I00
1770 | S'8_\x8d@\x948h@\x8c\xcb{\x9aS\x87P@dP\xb9\xdf\xb5Sv@:\x1a\xc22V\x9ch@'
1771 | p729
1772 | tp730
1773 | bsS'image_0149.png'
1774 | p731
1775 | g2
1776 | (g3
1777 | (I0
1778 | tp732
1779 | g5
1780 | tp733
1781 | Rp734
1782 | (I1
1783 | (L4L
1784 | tp735
1785 | g12
1786 | I00
1787 | S'\xbf\x17Q_\xc5Hj@2\xd1B/8tc@V\xb9\x8aU$\xe6t@\xd7\xd0xlN\x1dq@'
1788 | p736
1789 | tp737
1790 | bsS'image_0058.png'
1791 | p738
1792 | g2
1793 | (g3
1794 | (I0
1795 | tp739
1796 | g5
1797 | tp740
1798 | Rp741
1799 | (I1
1800 | (L4L
1801 | tp742
1802 | g12
1803 | I00
1804 | S'\xd5\xea\xd3l\x98\xb1U@\xac\x01v\xd7\xb1.Y@\x14\xa2\xd6\xa8\\\x97i@\xdf\xd0\x8e\\\xfa\x11m@'
1805 | p743
1806 | tp744
1807 | bsS'image_0098.png'
1808 | p745
1809 | g2
1810 | (g3
1811 | (I0
1812 | tp746
1813 | g5
1814 | tp747
1815 | Rp748
1816 | (I1
1817 | (L4L
1818 | tp749
1819 | g12
1820 | I00
1821 | S'\xaf~\xb5V\xf1\x15a@ w\x1c\'\x14Vc@\xc0H)\xb7\xb2\x1ct@\xeezag\xb2"t@'
1822 | p750
1823 | tp751
1824 | bsS'image_0099.png'
1825 | p752
1826 | g2
1827 | (g3
1828 | (I0
1829 | tp753
1830 | g5
1831 | tp754
1832 | Rp755
1833 | (I1
1834 | (L4L
1835 | tp756
1836 | g12
1837 | I00
1838 | S'\xf8\xc5\x93<\x85\x88o@y\xd3N#ksc@\x82\x8e\x87hn\xe2|@\x1c$\x86\xf1\x9c\xedw@'
1839 | p757
1840 | tp758
1841 | bsS'image_0100.png'
1842 | p759
1843 | g2
1844 | (g3
1845 | (I0
1846 | tp760
1847 | g5
1848 | tp761
1849 | Rp762
1850 | (I1
1851 | (L4L
1852 | tp763
1853 | g12
1854 | I00
1855 | S'*\xb9 G\\\xb2X@K\xdf*[o\xb4^@\xb6\xd17\xeehCq@-H5)\xe4Br@'
1856 | p764
1857 | tp765
1858 | bsS'image_0114.png'
1859 | p766
1860 | g2
1861 | (g3
1862 | (I0
1863 | tp767
1864 | g5
1865 | tp768
1866 | Rp769
1867 | (I1
1868 | (L4L
1869 | tp770
1870 | g12
1871 | I00
1872 | S'_\xd8\xf3\x8e\xa8Sn@\xa0P\xe6y\xb1[g@\xbc\x1f\xd9i\xa9\xc8\x7f@\\\xca\x7f$\x9e,}@'
1873 | p771
1874 | tp772
1875 | bsS'image_0109.png'
1876 | p773
1877 | g2
1878 | (g3
1879 | (I0
1880 | tp774
1881 | g5
1882 | tp775
1883 | Rp776
1884 | (I1
1885 | (L4L
1886 | tp777
1887 | g12
1888 | I00
1889 | S'w\x9fAZ\tla@\x18\xf8P\xfc\xa5\xc4S@\xb6i\xf9\xd6e!r@\x82\x89c\x07=^j@'
1890 | p778
1891 | tp779
1892 | bsS'image_0225.png'
1893 | p780
1894 | g2
1895 | (g3
1896 | (I0
1897 | tp781
1898 | g5
1899 | tp782
1900 | Rp783
1901 | (I1
1902 | (L4L
1903 | tp784
1904 | g12
1905 | I00
1906 | S'0\xa56\xe2"7X@\xb9Ml\xc2$$[@\xc1\x08\xe7\x94\n-k@\xa1J\x9b\xa5\x9e\x04o@'
1907 | p785
1908 | tp786
1909 | bsS'image_0004.png'
1910 | p787
1911 | g2
1912 | (g3
1913 | (I0
1914 | tp788
1915 | g5
1916 | tp789
1917 | Rp790
1918 | (I1
1919 | (L4L
1920 | tp791
1921 | g12
1922 | I00
1923 | S'\x1br0\xcd`\xa0b@\xd4*\xab\x82\xc0\x93b@z\xf9_t\xf8\xa1u@V2\xde\xde\x13\xfav@'
1924 | p792
1925 | tp793
1926 | bsS'image_0032.png'
1927 | p794
1928 | g2
1929 | (g3
1930 | (I0
1931 | tp795
1932 | g5
1933 | tp796
1934 | Rp797
1935 | (I1
1936 | (L4L
1937 | tp798
1938 | g12
1939 | I00
1940 | S'\x08\x82\x90\xc6J9u@\xa4k\xf9\x04\xfe\xa2@@\xc0\xac\x83\xdf\xeaB\x84@~\xb6\xdeDcMs@'
1941 | p799
1942 | tp800
1943 | bsS'image_0091.png'
1944 | p801
1945 | g2
1946 | (g3
1947 | (I0
1948 | tp802
1949 | g5
1950 | tp803
1951 | Rp804
1952 | (I1
1953 | (L4L
1954 | tp805
1955 | g12
1956 | I00
1957 | S'g\xa6\xc23x\xbd]@\xbah\x82\x00V\xa9[@fV\x0f\xf3\xa1\x00r@\xd2e\xdf\x7f\xaa\x85p@'
1958 | p806
1959 | tp807
1960 | bsS'image_0056.png'
1961 | p808
1962 | g2
1963 | (g3
1964 | (I0
1965 | tp809
1966 | g5
1967 | tp810
1968 | Rp811
1969 | (I1
1970 | (L4L
1971 | tp812
1972 | g12
1973 | I00
1974 | S'\xbf\x98\x0e\xc9\xe2\xa9R@\x08\x18\x93q\x1b\xd3^@\r\x8d\x0b\xad~]i@\xde\xa0\xb2\x91\x13\x9an@'
1975 | p813
1976 | tp814
1977 | bsS'image_0022.png'
1978 | p815
1979 | g2
1980 | (g3
1981 | (I0
1982 | tp816
1983 | g5
1984 | tp817
1985 | Rp818
1986 | (I1
1987 | (L4L
1988 | tp819
1989 | g12
1990 | I00
1991 | S'\xd63?\xfdn\x98Z@\x8f\xea\x81\x8b\xcfDd@\xe5\xd4.\xfe\xb0\xf9n@\xe6\xca\xf1{\x01\x88r@'
1992 | p820
1993 | tp821
1994 | bsS'image_0073.png'
1995 | p822
1996 | g2
1997 | (g3
1998 | (I0
1999 | tp823
2000 | g5
2001 | tp824
2002 | Rp825
2003 | (I1
2004 | (L4L
2005 | tp826
2006 | g12
2007 | I00
2008 | S'\xee\xbdf\xf1\x85\xed]@\xb8\x9d\x8a\x89F\xd5_@\x84P\xa6\x83\x9e\xf4q@\x92X\x9d]\xaezs@'
2009 | p827
2010 | tp828
2011 | bsS'image_0156.png'
2012 | p829
2013 | g2
2014 | (g3
2015 | (I0
2016 | tp830
2017 | g5
2018 | tp831
2019 | Rp832
2020 | (I1
2021 | (L4L
2022 | tp833
2023 | g12
2024 | I00
2025 | S'\xf6*\x89\xd8\x890p@\xb4\xfa\xab[\x7fQV@b0y-\x12(w@2\x08\xb6W\xd0\x17i@'
2026 | p834
2027 | tp835
2028 | bsS'image_0076.png'
2029 | p836
2030 | g2
2031 | (g3
2032 | (I0
2033 | tp837
2034 | g5
2035 | tp838
2036 | Rp839
2037 | (I1
2038 | (L4L
2039 | tp840
2040 | g12
2041 | I00
2042 | S'\t\xdeG\xa1\xc1\xd5U@\x11\xa5%\xff\x89\xe4b@~\x08\xae\x97\x8fzp@x-m\x00\xbb\xfdt@'
2043 | p841
2044 | tp842
2045 | bsS'image_0077.png'
2046 | p843
2047 | g2
2048 | (g3
2049 | (I0
2050 | tp844
2051 | g5
2052 | tp845
2053 | Rp846
2054 | (I1
2055 | (L4L
2056 | tp847
2057 | g12
2058 | I00
2059 | S"\xb7}}\x7f*\x86c@'k\x9b\xde\x02\xf4Z@\xd04^\x88\xa1\xe2o@8;\xd2\x96\x9d\x90j@"
2060 | p848
2061 | tp849
2062 | bsS'image_0197.png'
2063 | p850
2064 | g2
2065 | (g3
2066 | (I0
2067 | tp851
2068 | g5
2069 | tp852
2070 | Rp853
2071 | (I1
2072 | (L4L
2073 | tp854
2074 | g12
2075 | I00
2076 | S'\x8f\x9e4,\xc5\x19W@\xbc\xf3q\xf5,\x1cb@m\xeb^\xd8\xa4;s@\x0en\xa1\xbd,;u@'
2077 | p855
2078 | tp856
2079 | bsS'image_0199.png'
2080 | p857
2081 | g2
2082 | (g3
2083 | (I0
2084 | tp858
2085 | g5
2086 | tp859
2087 | Rp860
2088 | (I1
2089 | (L4L
2090 | tp861
2091 | g12
2092 | I00
2093 | S'\x9a;"\xfe(\xedV@\xa4J\x1d\xa4a?i@\x93\xbfL\xc1\x1cTr@\xff\xd5\xd2S\x838y@'
2094 | p862
2095 | tp863
2096 | bsS'image_0012.png'
2097 | p864
2098 | g2
2099 | (g3
2100 | (I0
2101 | tp865
2102 | g5
2103 | tp866
2104 | Rp867
2105 | (I1
2106 | (L4L
2107 | tp868
2108 | g12
2109 | I00
2110 | S'\x8eBQ\xc1\xd6\x93b@\xb1h\xcb\xf6\x80\x13d@\x08yO\xa4\x95\xfe\xff\\Y\x95g@\xd6\xa9\xec]q\xa5m@'
2451 | p1009
2452 | tp1010
2453 | bsS'image_0060.png'
2454 | p1011
2455 | g2
2456 | (g3
2457 | (I0
2458 | tp1012
2459 | g5
2460 | tp1013
2461 | Rp1014
2462 | (I1
2463 | (L4L
2464 | tp1015
2465 | g12
2466 | I00
2467 | S'\x907z\xbe\x7f\xeaa@\x907z\xbe\x7f\xeaa@\x8a\x81\x7f\xb6\x1d\xabt@\x8a\x81\x7f\xb6\x1d\xabt@'
2468 | p1016
2469 | tp1017
2470 | bsS'image_0179.png'
2471 | p1018
2472 | g2
2473 | (g3
2474 | (I0
2475 | tp1019
2476 | g5
2477 | tp1020
2478 | Rp1021
2479 | (I1
2480 | (L4L
2481 | tp1022
2482 | g12
2483 | I00
2484 | S'\xfby\xcfW\x10dU@\xcd>\xc1\x02\x88n]@\x1c\x7f\xa9\xf3\xcd\xc4d@\x86a"\xc9\t\xcah@'
2485 | p1023
2486 | tp1024
2487 | bsS'image_0065.png'
2488 | p1025
2489 | g2
2490 | (g3
2491 | (I0
2492 | tp1026
2493 | g5
2494 | tp1027
2495 | Rp1028
2496 | (I1
2497 | (L4L
2498 | tp1029
2499 | g12
2500 | I00
2501 | S"]?e\x1cc'R@\x96\xf6OU\xe1 a@R`\xcdqN\xccn@\xb5\x04XU\x8f\xdfq@"
2502 | p1030
2503 | tp1031
2504 | bsS'image_0028.png'
2505 | p1032
2506 | g2
2507 | (g3
2508 | (I0
2509 | tp1033
2510 | g5
2511 | tp1034
2512 | Rp1035
2513 | (I1
2514 | (L4L
2515 | tp1036
2516 | g12
2517 | I00
2518 | S'\xe9\x91w\xdf!2Z@\xfbO%\xad\xda\xef[@\xd2\xc6;&\xfbMn@\xdc\xa5\x12\x8d\xd7,o@'
2519 | p1037
2520 | tp1038
2521 | bsS'image_0127.png'
2522 | p1039
2523 | g2
2524 | (g3
2525 | (I0
2526 | tp1040
2527 | g5
2528 | tp1041
2529 | Rp1042
2530 | (I1
2531 | (L4L
2532 | tp1043
2533 | g12
2534 | I00
2535 | S'{\x07tu\x1cBp@\xd0N\x90h_@r@1\xff\xd7\x19\xfd\xe1{@\xb8\x0c\xaa;\xe7*\x7f@'
2536 | p1044
2537 | tp1045
2538 | bsS'image_0103.png'
2539 | p1046
2540 | g2
2541 | (g3
2542 | (I0
2543 | tp1047
2544 | g5
2545 | tp1048
2546 | Rp1049
2547 | (I1
2548 | (L4L
2549 | tp1050
2550 | g12
2551 | I00
2552 | S'\x991\xf6\x94d\x7fU@\x10b&\xe4*\xafb@GQ\xcc\xa0"Kt@Ra\xbePD\x95w@'
2553 | p1051
2554 | tp1052
2555 | bsS'image_0224.png'
2556 | p1053
2557 | g2
2558 | (g3
2559 | (I0
2560 | tp1054
2561 | g5
2562 | tp1055
2563 | Rp1056
2564 | (I1
2565 | (L4L
2566 | tp1057
2567 | g12
2568 | I00
2569 | S'\xf8\xb5\xcf>E\xe6D@\xfc\xdag\x9f"sV@\x82\x12L\xb0n\xa6g@\x82\x12L\xb0n\xa6m@'
2570 | p1058
2571 | tp1059
2572 | bsS'image_0115.png'
2573 | p1060
2574 | g2
2575 | (g3
2576 | (I0
2577 | tp1061
2578 | g5
2579 | tp1062
2580 | Rp1063
2581 | (I1
2582 | (L4L
2583 | tp1064
2584 | g12
2585 | I00
2586 | S'\x1e>\x0f\nc\x17p@\xf4\x9d^\x12r4`@\xe2\xc1\xf0\xf5\x9c\xd8{@\x06\xb1\xd0\xf6\xc6\xd5r@'
2587 | p1065
2588 | tp1066
2589 | bsS'image_0118.png'
2590 | p1067
2591 | g2
2592 | (g3
2593 | (I0
2594 | tp1068
2595 | g5
2596 | tp1069
2597 | Rp1070
2598 | (I1
2599 | (L4L
2600 | tp1071
2601 | g12
2602 | I00
2603 | S'\n1\x17\xbb\xc0\xc1X@\n\xaec\x7fZ:d@\xb4\xb9\xe3\xa9\xce@q@:\xa7\xae\xcf\xf4Jt@'
2604 | p1072
2605 | tp1073
2606 | bsS'image_0005.png'
2607 | p1074
2608 | g2
2609 | (g3
2610 | (I0
2611 | tp1075
2612 | g5
2613 | tp1076
2614 | Rp1077
2615 | (I1
2616 | (L4L
2617 | tp1078
2618 | g12
2619 | I00
2620 | S'\x90\xfd\xef\xdeb\xc6a@\xac\xb5\x87\x9c\x0f\xd1a@\x97\xf9B\x85Wsp@A\xdb\x14eQ\xe1n@'
2621 | p1079
2622 | tp1080
2623 | bsS'image_0069.png'
2624 | p1081
2625 | g2
2626 | (g3
2627 | (I0
2628 | tp1082
2629 | g5
2630 | tp1083
2631 | Rp1084
2632 | (I1
2633 | (L4L
2634 | tp1085
2635 | g12
2636 | I00
2637 | S'\x9a\xd7p\xfd\xb8(i@\xc6\x12\x7fRA\x1ea@\xb6\xb2Qv\xb5\xf7v@L\xd0\xd8\xa0y\xf2r@'
2638 | p1086
2639 | tp1087
2640 | bsS'image_0082.png'
2641 | p1088
2642 | g2
2643 | (g3
2644 | (I0
2645 | tp1089
2646 | g5
2647 | tp1090
2648 | Rp1091
2649 | (I1
2650 | (L4L
2651 | tp1092
2652 | g12
2653 | I00
2654 | S'\x14g\xeaTR\x14p@\xc5\xadjj\x8c8Q@q\xeb,]\xeaVv@\x9c_\xbaEv!e@'
2655 | p1093
2656 | tp1094
2657 | bsS'image_0027.png'
2658 | p1095
2659 | g2
2660 | (g3
2661 | (I0
2662 | tp1096
2663 | g5
2664 | tp1097
2665 | Rp1098
2666 | (I1
2667 | (L4L
2668 | tp1099
2669 | g12
2670 | I00
2671 | S'\xbaM\nA\x0c\xf7c@\xf0XM\x8a?ig@<\x15\x0c\xffO\x8bu@\xd7\x9a\xad\xa3iDw@'
2672 | p1100
2673 | tp1101
2674 | bsS'image_0163.png'
2675 | p1102
2676 | g2
2677 | (g3
2678 | (I0
2679 | tp1103
2680 | g5
2681 | tp1104
2682 | Rp1105
2683 | (I1
2684 | (L4L
2685 | tp1106
2686 | g12
2687 | I00
2688 | S'\x02\xa0\x8e=Q\xccQ@\xe8\xcaD\x03\x9b\xc6_@\x86&P\xa7\xdchl@D2\xaf~t^p@'
2689 | p1107
2690 | tp1108
2691 | bsS'image_0238.png'
2692 | p1109
2693 | g2
2694 | (g3
2695 | (I0
2696 | tp1110
2697 | g5
2698 | tp1111
2699 | Rp1112
2700 | (I1
2701 | (L4L
2702 | tp1113
2703 | g12
2704 | I00
2705 | S'T\xcc\x1f\x1e\xef\xa0[@%$\xa3h\x19&b@\xafg\x95TMTo@\x82\x00H\x8c5jq@'
2706 | p1114
2707 | tp1115
2708 | bsS'image_0213.png'
2709 | p1116
2710 | g2
2711 | (g3
2712 | (I0
2713 | tp1117
2714 | g5
2715 | tp1118
2716 | Rp1119
2717 | (I1
2718 | (L4L
2719 | tp1120
2720 | g12
2721 | I00
2722 | S"\xe0\xd2\xf3\xf5\xa6\x8fH@8'=]\xf7Sb@\x99G\x91\x1f\xf1\xf1i@\x0c\xbd\xa8_\xff\x10s@"
2723 | p1121
2724 | tp1122
2725 | bsS'image_0153.png'
2726 | p1123
2727 | g2
2728 | (g3
2729 | (I0
2730 | tp1124
2731 | g5
2732 | tp1125
2733 | Rp1126
2734 | (I1
2735 | (L4L
2736 | tp1127
2737 | g12
2738 | I00
2739 | S'\xb0\x06)\x0c\x11\x80\x83Si@\x8e\xfd>\x80\x83Se@9\x81\xe0?>Fw@9\x81\xe0?>Fu@'
3080 | p1268
3081 | tp1269
3082 | bsS'image_0110.png'
3083 | p1270
3084 | g2
3085 | (g3
3086 | (I0
3087 | tp1271
3088 | g5
3089 | tp1272
3090 | Rp1273
3091 | (I1
3092 | (L4L
3093 | tp1274
3094 | g12
3095 | I00
3096 | S'\xbft\xf7\x16"\x1fd@\xe6\xbf\xc2c2\x1bd@1\x9br\xa1P.|@\x8c7_\xad\x8frz@'
3097 | p1275
3098 | tp1276
3099 | bsS'image_0104.png'
3100 | p1277
3101 | g2
3102 | (g3
3103 | (I0
3104 | tp1278
3105 | g5
3106 | tp1279
3107 | Rp1280
3108 | (I1
3109 | (L4L
3110 | tp1281
3111 | g12
3112 | I00
3113 | S"_O\xd8\xfclnp@\xb3\x9a\xe1\xd1\xa81`@'lV\x893\rx@\xb1\x01+5\x0e\xe9m@"
3114 | p1282
3115 | tp1283
3116 | bsS'image_0105.png'
3117 | p1284
3118 | g2
3119 | (g3
3120 | (I0
3121 | tp1285
3122 | g5
3123 | tp1286
3124 | Rp1287
3125 | (I1
3126 | (L4L
3127 | tp1288
3128 | g12
3129 | I00
3130 | S'\xd4&\x06H\xd4^`@X\xd3\x1e\xf6\x02^b@\x96\xec\xfc\xdb\x95\xc0r@T\x96\xf0\x84\xfe@t@'
3131 | p1289
3132 | tp1290
3133 | bsS'image_0002.png'
3134 | p1291
3135 | g2
3136 | (g3
3137 | (I0
3138 | tp1292
3139 | g5
3140 | tp1293
3141 | Rp1294
3142 | (I1
3143 | (L4L
3144 | tp1295
3145 | g12
3146 | I00
3147 | S'\xd7\xf1\xa1\x17\x10\xc7j@\xa1\xe6^\xce\xdcTg@\x9aYF\xa6\xb4\x07y@\xfe\xd3\xa4\x01\x9bNw@'
3148 | p1296
3149 | tp1297
3150 | bsS'image_0206.png'
3151 | p1298
3152 | g2
3153 | (g3
3154 | (I0
3155 | tp1299
3156 | g5
3157 | tp1300
3158 | Rp1301
3159 | (I1
3160 | (L4L
3161 | tp1302
3162 | g12
3163 | I00
3164 | S'\xb0\xdd\x01i`\x06f@n\x8a\xf5\xba\xf0\xb4G@\xdc\xd2\xb1\x8f\xbf@j\xa0\xea\x93Q\xd3\\@\x02w\r\xa5|\x99c@b\xf6\xa0<\x02\xa9l@"
3216 | p1324
3217 | tp1325
3218 | bsS'image_0148.png'
3219 | p1326
3220 | g2
3221 | (g3
3222 | (I0
3223 | tp1327
3224 | g5
3225 | tp1328
3226 | Rp1329
3227 | (I1
3228 | (L4L
3229 | tp1330
3230 | g12
3231 | I00
3232 | S'\x04\xdc<\x13p\xd1W@2D\xafj\xf8\xe2i@\xfe\x91a\xf6G\xf7o@\xe7]\xa8\xca\x83~v@'
3233 | p1331
3234 | tp1332
3235 | bsS'image_0174.png'
3236 | p1333
3237 | g2
3238 | (g3
3239 | (I0
3240 | tp1334
3241 | g5
3242 | tp1335
3243 | Rp1336
3244 | (I1
3245 | (L4L
3246 | tp1337
3247 | g12
3248 | I00
3249 | S'n\x8e\x10\x93\x93cq@\xb1\xd3ag\x0f\x07h@\x9a\xfcG:\x99H\x80@\xb5\x1b\xdbQ\x08Mx@'
3250 | p1338
3251 | tp1339
3252 | bsS'image_0182.png'
3253 | p1340
3254 | g2
3255 | (g3
3256 | (I0
3257 | tp1341
3258 | g5
3259 | tp1342
3260 | Rp1343
3261 | (I1
3262 | (L4L
3263 | tp1344
3264 | g12
3265 | I00
3266 | S'\x02s6\x1c\xd2:e@\x8cKG\xde\xd3\x1fr@\x7f\xc6\xe4\xf1\x96\xd2u@t\xb4\xb8!,P|@'
3267 | p1345
3268 | tp1346
3269 | bsS'image_0192.png'
3270 | p1347
3271 | g2
3272 | (g3
3273 | (I0
3274 | tp1348
3275 | g5
3276 | tp1349
3277 | Rp1350
3278 | (I1
3279 | (L4L
3280 | tp1351
3281 | g12
3282 | I00
3283 | S'\x84\xc5;\x8b\xc8Y_@\xde\x7f"zyIb@\x9ds\xb1\x1c\xa9yp@+\xc2\xf3\xb6\xf3\xc7q@'
3284 | p1352
3285 | tp1353
3286 | bsS'image_0196.png'
3287 | p1354
3288 | g2
3289 | (g3
3290 | (I0
3291 | tp1355
3292 | g5
3293 | tp1356
3294 | Rp1357
3295 | (I1
3296 | (L4L
3297 | tp1358
3298 | g12
3299 | I00
3300 | S'\xb8Sa\x0c8`V@<\xb0\xb6\xa2^\x0fg@\x89\xf3\xb5}"\xc1r@\x0e\x9aOY\xdb_w@'
3301 | p1359
3302 | tp1360
3303 | bsS'image_0111.png'
3304 | p1361
3305 | g2
3306 | (g3
3307 | (I0
3308 | tp1362
3309 | g5
3310 | tp1363
3311 | Rp1364
3312 | (I1
3313 | (L4L
3314 | tp1365
3315 | g12
3316 | I00
3317 | S"\x19y\xfc\x06\x85\xd0W@\xe3'\x8c?\xd0\x8cl@pPL\xc2G\x82t@3\x9d\xb2\xe6?\x1a|@"
3318 | p1366
3319 | tp1367
3320 | bsS'image_0112.png'
3321 | p1368
3322 | g2
3323 | (g3
3324 | (I0
3325 | tp1369
3326 | g5
3327 | tp1370
3328 | Rp1371
3329 | (I1
3330 | (L4L
3331 | tp1372
3332 | g12
3333 | I00
3334 | S'(MP\xbf}\xa0m@96<\xaaT\xb3S@\xf8\xde\xe3%Q\x80u@\xe4\x7f\x8b\xb0\xe8(k@'
3335 | p1373
3336 | tp1374
3337 | bsS'image_0226.png'
3338 | p1375
3339 | g2
3340 | (g3
3341 | (I0
3342 | tp1376
3343 | g5
3344 | tp1377
3345 | Rp1378
3346 | (I1
3347 | (L4L
3348 | tp1379
3349 | g12
3350 | I00
3351 | S'\xaazno\xfc\x02_@=Hl\x08\x02\x1ab@T\xc6\xa4#\\\x8fp@vnc\x7f\x93\xed-@/,7\xd75[k@&\x15\x0c\xc8&\x81b@\xe8id\x14e\xc2w@'
3403 | p1401
3404 | tp1402
3405 | bsS'image_0051.png'
3406 | p1403
3407 | g2
3408 | (g3
3409 | (I0
3410 | tp1404
3411 | g5
3412 | tp1405
3413 | Rp1406
3414 | (I1
3415 | (L4L
3416 | tp1407
3417 | g12
3418 | I00
3419 | S'\xa7\x80\xec]\xe2hh@\xec\xeb\xe2/\x89Dr@\xff\xe3\xadl3&\x85@\xcb9$m?.\x88@'
3420 | p1408
3421 | tp1409
3422 | bsS'image_0166.png'
3423 | p1410
3424 | g2
3425 | (g3
3426 | (I0
3427 | tp1411
3428 | g5
3429 | tp1412
3430 | Rp1413
3431 | (I1
3432 | (L4L
3433 | tp1414
3434 | g12
3435 | I00
3436 | S'4z\xcbY=\xd56@\xda\xa0qh\xd4gU@\xa67\x99\xc6\xba\xa7c@\x12\xc7\x07\xab>\xbci@'
3437 | p1415
3438 | tp1416
3439 | bsS'image_0123.png'
3440 | p1417
3441 | g2
3442 | (g3
3443 | (I0
3444 | tp1418
3445 | g5
3446 | tp1419
3447 | Rp1420
3448 | (I1
3449 | (L4L
3450 | tp1421
3451 | g12
3452 | I00
3453 | S'\xd2\xaa\x1e\xa9\x8c-^@T\xc8\xb6\x0f\x81\xd0n@\x93\xb2\xefK\x9b\xbbw@n"\xfe.i\x13\x81@'
3454 | p1422
3455 | tp1423
3456 | bsS'image_0031.png'
3457 | p1424
3458 | g2
3459 | (g3
3460 | (I0
3461 | tp1425
3462 | g5
3463 | tp1426
3464 | Rp1427
3465 | (I1
3466 | (L4L
3467 | tp1428
3468 | g12
3469 | I00
3470 | S'l\x88\xe3\x12\x97\xaeb@(L\x8eB$&f@{\xc9\xb3}y\tu@l\xc4\xb5\x16\xd5\x99u@'
3471 | p1429
3472 | tp1430
3473 | bsS'image_0046.png'
3474 | p1431
3475 | g2
3476 | (g3
3477 | (I0
3478 | tp1432
3479 | g5
3480 | tp1433
3481 | Rp1434
3482 | (I1
3483 | (L4L
3484 | tp1435
3485 | g12
3486 | I00
3487 | S'X"\x9a\xd8+:c@f,Do=\xc25@r`#\xbb\x08\xbfq@D\x84e\x8f\x85-a@'
3488 | p1436
3489 | tp1437
3490 | bsS'image_0043.png'
3491 | p1438
3492 | g2
3493 | (g3
3494 | (I0
3495 | tp1439
3496 | g5
3497 | tp1440
3498 | Rp1441
3499 | (I1
3500 | (L4L
3501 | tp1442
3502 | g12
3503 | I00
3504 | S'\x1e_zWWrb@^y=\xda\x9dr`@q\xd0BT\xd4\xb6q@QC\xe1\x12\xb1\xb6q@'
3505 | p1443
3506 | tp1444
3507 | bsS'image_0218.png'
3508 | p1445
3509 | g2
3510 | (g3
3511 | (I0
3512 | tp1446
3513 | g5
3514 | tp1447
3515 | Rp1448
3516 | (I1
3517 | (L4L
3518 | tp1449
3519 | g12
3520 | I00
3521 | S'\x1a\\\xda\\o=i@\xaa\x93\x18\xe6\xb8\x83`@V\xccN\xfc\xdbDu@\xb7i\xb6f\x89\\q@'
3522 | p1450
3523 | tp1451
3524 | bsS'image_0067.png'
3525 | p1452
3526 | g2
3527 | (g3
3528 | (I0
3529 | tp1453
3530 | g5
3531 | tp1454
3532 | Rp1455
3533 | (I1
3534 | (L4L
3535 | tp1456
3536 | g12
3537 | I00
3538 | S'\xe8V\xd2,U\x89W@ g\xb8\x87\xe6FV@T\x91\xdf\xb6\xc5\xbbg@8\x89l\t\xfd\\h@'
3539 | p1457
3540 | tp1458
3541 | bsS'image_0222.png'
3542 | p1459
3543 | g2
3544 | (g3
3545 | (I0
3546 | tp1460
3547 | g5
3548 | tp1461
3549 | Rp1462
3550 | (I1
3551 | (L4L
3552 | tp1463
3553 | g12
3554 | I00
3555 | S'c\xd7\xc6\xc0\n(k@j\xbd\xc9w\xa5\x07^@<\xa4\xde$\x83\xd7t@V\xfd\xceJ\xdb\xd0l@'
3556 | p1464
3557 | tp1465
3558 | bsS'image_0219.png'
3559 | p1466
3560 | g2
3561 | (g3
3562 | (I0
3563 | tp1467
3564 | g5
3565 | tp1468
3566 | Rp1469
3567 | (I1
3568 | (L4L
3569 | tp1470
3570 | g12
3571 | I00
3572 | S'\x1cW\xcd\x0b\x02\xb1V@Q\x0e\xcd\x99\xbdYa@rT\x19\xfa~\x87n@\xd8x\x193!\xc3q@'
3573 | p1471
3574 | tp1472
3575 | bsS'image_0133.png'
3576 | p1473
3577 | g2
3578 | (g3
3579 | (I0
3580 | tp1474
3581 | g5
3582 | tp1475
3583 | Rp1476
3584 | (I1
3585 | (L4L
3586 | tp1477
3587 | g12
3588 | I00
3589 | S'\xb8\xe0\x8a\xff\x97\xb1I@\x17\\\xf1\xff26p@\xe9\xa3\x0e\x00\xcd\xb9w@\xf4Q\x07\x80\xe6\\\x82@'
3590 | p1478
3591 | tp1479
3592 | bsS'image_0207.png'
3593 | p1480
3594 | g2
3595 | (g3
3596 | (I0
3597 | tp1481
3598 | g5
3599 | tp1482
3600 | Rp1483
3601 | (I1
3602 | (L4L
3603 | tp1484
3604 | g12
3605 | I00
3606 | S'\xb8\xc3H\xc7\xae\xa3f@:[\xc1\xcbW\x07b@\xd8_\x8e`\x18\xeeu@F\x83m\xf0\xf6\x10s@'
3607 | p1485
3608 | tp1486
3609 | bsS'image_0235.png'
3610 | p1487
3611 | g2
3612 | (g3
3613 | (I0
3614 | tp1488
3615 | g5
3616 | tp1489
3617 | Rp1490
3618 | (I1
3619 | (L4L
3620 | tp1491
3621 | g12
3622 | I00
3623 | S'\xac-\x9e\nC\xdcf@\xc4\\q\xd6\xfe\xe2]@/\xa1\x1e?\xc9\xddq@\x12\xc3\xd7\xde\xce\xd0k@'
3624 | p1492
3625 | tp1493
3626 | bsS'image_0209.png'
3627 | p1494
3628 | g2
3629 | (g3
3630 | (I0
3631 | tp1495
3632 | g5
3633 | tp1496
3634 | Rp1497
3635 | (I1
3636 | (L4L
3637 | tp1498
3638 | g12
3639 | I00
3640 | S'\xc8\xcc\x81\x87\x86\xeef@\xf5,Q^\x82\xa4[@\x1f8I\xb1\xce\x14x@p\xdav\xf5N\xb9q@'
3641 | p1499
3642 | tp1500
3643 | bsS'image_0092.png'
3644 | p1501
3645 | g2
3646 | (g3
3647 | (I0
3648 | tp1502
3649 | g5
3650 | tp1503
3651 | Rp1504
3652 | (I1
3653 | (L4L
3654 | tp1505
3655 | g12
3656 | I00
3657 | S'\xa7\xc8\x1cX\xf3yb@1b\x94\xe5\xcb\xf5^@\xac\x9b\xf1S\x06\xb3s@t\xe7\x9a\x06\x8d2s@'
3658 | p1506
3659 | tp1507
3660 | bsS'image_0154.png'
3661 | p1508
3662 | g2
3663 | (g3
3664 | (I0
3665 | tp1509
3666 | g5
3667 | tp1510
3668 | Rp1511
3669 | (I1
3670 | (L4L
3671 | tp1512
3672 | g12
3673 | I00
3674 | S'\xac&\xa1(\x93mQ@\xcf\x9b\x0fQ\xa7t]@\xaal\xafk6)l@\x0c\x19\xbc+\xd6\x92q@'
3675 | p1513
3676 | tp1514
3677 | bsS'image_0070.png'
3678 | p1515
3679 | g2
3680 | (g3
3681 | (I0
3682 | tp1516
3683 | g5
3684 | tp1517
3685 | Rp1518
3686 | (I1
3687 | (L4L
3688 | tp1519
3689 | g12
3690 | I00
3691 | S'\x88\xe6\xb9d\xf7\xabq@FLB\xaf\x18kY@>\xa9=\xb1\x14\xcby@\x92\xab\xa8\xf0\xc6\xf3l@'
3692 | p1520
3693 | tp1521
3694 | bsS'image_0044.png'
3695 | p1522
3696 | g2
3697 | (g3
3698 | (I0
3699 | tp1523
3700 | g5
3701 | tp1524
3702 | Rp1525
3703 | (I1
3704 | (L4L
3705 | tp1526
3706 | g12
3707 | I00
3708 | S'6\x1a\xa8t\xd1\x8ew@Q\x06\xc0O\xfe\xbeb@\x92\xcb\xe2\xa1\xbcz~@n\xea\xb5\x99\x13\xeeo@'
3709 | p1527
3710 | tp1528
3711 | bsS'image_0211.png'
3712 | p1529
3713 | g2
3714 | (g3
3715 | (I0
3716 | tp1530
3717 | g5
3718 | tp1531
3719 | Rp1532
3720 | (I1
3721 | (L4L
3722 | tp1533
3723 | g12
3724 | I00
3725 | S'\xf0\x96\xcc\xfe\x87\xc4a@x\xcfb{\x91\x8bO@\x9a\xc7\x05$\xd2\x1fp@r\xe9\xe36y\xade@'
3726 | p1534
3727 | tp1535
3728 | bsS'image_0040.png'
3729 | p1536
3730 | g2
3731 | (g3
3732 | (I0
3733 | tp1537
3734 | g5
3735 | tp1538
3736 | Rp1539
3737 | (I1
3738 | (L4L
3739 | tp1540
3740 | g12
3741 | I00
3742 | S'Bz\x03\x80ECV@r\xfd\x1d\xc7W*a@\xdfB\xfe?]\xbem@G\x01q\x1c\xd4\xdap@'
3743 | p1541
3744 | tp1542
3745 | bsS'image_0227.png'
3746 | p1543
3747 | g2
3748 | (g3
3749 | (I0
3750 | tp1544
3751 | g5
3752 | tp1545
3753 | Rp1546
3754 | (I1
3755 | (L4L
3756 | tp1547
3757 | g12
3758 | I00
3759 | S't"Y5\x89Om@\x80#h<*\x1er@x\x8b X\x9e|\x82@\xbe\xa4\xbb\\\xa7\xc6\x84@'
3760 | p1548
3761 | tp1549
3762 | bsS'image_0008.png'
3763 | p1550
3764 | g2
3765 | (g3
3766 | (I0
3767 | tp1551
3768 | g5
3769 | tp1552
3770 | Rp1553
3771 | (I1
3772 | (L4L
3773 | tp1554
3774 | g12
3775 | I00
3776 | S'\x11\xcb\xf2T\xe6Hd@x\x9f\x88\x82\xc7\xc7X@\x0e(}\x0f\xe1\x83p@\x15b\x19\xb9\x08ij@'
3777 | p1555
3778 | tp1556
3779 | bsS'image_0003.png'
3780 | p1557
3781 | g2
3782 | (g3
3783 | (I0
3784 | tp1558
3785 | g5
3786 | tp1559
3787 | Rp1560
3788 | (I1
3789 | (L4L
3790 | tp1561
3791 | g12
3792 | I00
3793 | S'\x86\x86\x0f\x0b\xdd\xe0^@C\xc3\x87\x85npi@^\x1e<\xbd\xc87y@^\x1e<\xbd\xc87~@'
3794 | p1562
3795 | tp1563
3796 | bsS'image_0108.png'
3797 | p1564
3798 | g2
3799 | (g3
3800 | (I0
3801 | tp1565
3802 | g5
3803 | tp1566
3804 | Rp1567
3805 | (I1
3806 | (L4L
3807 | tp1568
3808 | g12
3809 | I00
3810 | S'}y\xb6\xf6b)Z@nf\x8c\xb3(\x9bW@\x12u\x02\xff:\xb8i@\xfe\xb3\xf9}rVj@'
3811 | p1569
3812 | tp1570
3813 | bsS'image_0203.png'
3814 | p1571
3815 | g2
3816 | (g3
3817 | (I0
3818 | tp1572
3819 | g5
3820 | tp1573
3821 | Rp1574
3822 | (I1
3823 | (L4L
3824 | tp1575
3825 | g12
3826 | I00
3827 | S'\x7fuT\xe8\x1f\x17p@c\r0\x11\xa6i\\@\x81\x8a\xab\x17\xe0Xz@\xa7\xfc\xb3{\x96Up@'
3828 | p1576
3829 | tp1577
3830 | bs.
--------------------------------------------------------------------------------
/data/meanFaceShape.npz:
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https://raw.githubusercontent.com/MarekKowalski/DeepAlignmentNetwork/d55244b5a65d5ece73684da06d0dc52b8731f3cd/data/meanFaceShape.npz
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