├── Aptfile
├── ObjectDetector.py
├── Procfile
├── README.md
├── app.py
├── model
├── frozen_inference_graph.pb
└── ssd_mobilenet_v1_coco_2017_11_17.pbtxt
├── requirements.txt
└── templates
└── index.html
/Aptfile:
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1 | libsm6
2 | libxrender1
3 | libfontconfig1
4 | libice6
5 |
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/ObjectDetector.py:
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1 | import cv2 as cv
2 | import numpy
3 |
4 |
5 | classNames = {0: 'background',
6 | 1: 'person', 2: 'bicycle', 3: 'car', 4: 'motorcycle', 5: 'airplane', 6: 'bus',
7 | 7: 'train', 8: 'truck', 9: 'boat', 10: 'traffic light', 11: 'fire hydrant',
8 | 13: 'stop sign', 14: 'parking meter', 15: 'bench', 16: 'bird', 17: 'cat',
9 | 18: 'dog', 19: 'horse', 20: 'sheep', 21: 'cow', 22: 'elephant', 23: 'bear',
10 | 24: 'zebra', 25: 'giraffe', 27: 'backpack', 28: 'umbrella', 31: 'handbag',
11 | 32: 'tie', 33: 'suitcase', 34: 'frisbee', 35: 'skis', 36: 'snowboard',
12 | 37: 'sports ball', 38: 'kite', 39: 'baseball bat', 40: 'baseball glove',
13 | 41: 'skateboard', 42: 'surfboard', 43: 'tennis racket', 44: 'bottle',
14 | 46: 'wine glass', 47: 'cup', 48: 'fork', 49: 'knife', 50: 'spoon',
15 | 51: 'bowl', 52: 'banana', 53: 'apple', 54: 'sandwich', 55: 'orange',
16 | 56: 'broccoli', 57: 'carrot', 58: 'hot dog', 59: 'pizza', 60: 'donut',
17 | 61: 'cake', 62: 'chair', 63: 'couch', 64: 'potted plant', 65: 'bed',
18 | 67: 'dining table', 70: 'toilet', 72: 'tv', 73: 'laptop', 74: 'mouse',
19 | 75: 'remote', 76: 'keyboard', 77: 'cell phone', 78: 'microwave', 79: 'oven',
20 | 80: 'toaster', 81: 'sink', 82: 'refrigerator', 84: 'book', 85: 'clock',
21 | 86: 'vase', 87: 'scissors', 88: 'teddy bear', 89: 'hair drier', 90: 'toothbrush'}
22 |
23 |
24 | class Detector:
25 | def __init__(self):
26 | global cvNet
27 | cvNet = cv.dnn.readNetFromTensorflow('model/frozen_inference_graph.pb',
28 | 'model/ssd_mobilenet_v1_coco_2017_11_17.pbtxt')
29 |
30 | def detectObject(self, imName):
31 | img = cv.cvtColor(numpy.array(imName), cv.COLOR_BGR2RGB)
32 | cvNet.setInput(cv.dnn.blobFromImage(img, 0.007843, (300, 300), (127.5, 127.5, 127.5), swapRB=True, crop=False))
33 | detections = cvNet.forward()
34 | cols = img.shape[1]
35 | rows = img.shape[0]
36 |
37 | for i in range(detections.shape[2]):
38 | confidence = detections[0, 0, i, 2]
39 | if confidence > 0.5:
40 | class_id = int(detections[0, 0, i, 1])
41 |
42 | xLeftBottom = int(detections[0, 0, i, 3] * cols)
43 | yLeftBottom = int(detections[0, 0, i, 4] * rows)
44 | xRightTop = int(detections[0, 0, i, 5] * cols)
45 | yRightTop = int(detections[0, 0, i, 6] * rows)
46 |
47 | cv.rectangle(img, (xLeftBottom, yLeftBottom), (xRightTop, yRightTop),
48 | (0, 0, 255))
49 | if class_id in classNames:
50 | label = classNames[class_id] + ": " + str(confidence)
51 | labelSize, baseLine = cv.getTextSize(label, cv.FONT_HERSHEY_SIMPLEX, 0.5, 1)
52 | yLeftBottom = max(yLeftBottom, labelSize[1])
53 | cv.putText(img, label, (xLeftBottom+5, yLeftBottom), cv.FONT_HERSHEY_SIMPLEX, 0.5, (255,255,255))
54 |
55 | img = cv.imencode('.jpg', img)[1].tobytes()
56 | return img
57 |
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/Procfile:
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1 | web: gunicorn app:app
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/README.md:
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1 | # herokuobjectdetection
2 | This is the code for Medium tutorial
3 | https://medium.com/@rdeep/without-tensorflow-web-app-with-object-detection-api-in-heroku-and-opencv-aa1e54eceee1
4 |
5 | Live Demo
6 | https://objectdetectiontut.herokuapp.com/
7 |
8 | 
9 |
10 | 
11 |
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/app.py:
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1 | from ObjectDetector import Detector
2 | import io
3 |
4 | from flask import Flask, render_template, request
5 |
6 | from PIL import Image
7 | from flask import send_file
8 |
9 | app = Flask(__name__)
10 |
11 | detector = Detector()
12 |
13 |
14 | # detector.detectNumberPlate('twocar.jpg')
15 |
16 |
17 | @app.route("/")
18 | def index():
19 | return render_template('index.html')
20 |
21 |
22 | @app.route("/", methods=['POST'])
23 | def upload():
24 | if request.method == 'POST':
25 | file = Image.open(request.files['file'].stream)
26 | img = detector.detectObject(file)
27 | return send_file(io.BytesIO(img),attachment_filename='image.jpg',mimetype='image/jpg')
28 |
29 |
30 | if __name__ == "__main__":
31 | app.run()
32 |
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/model/frozen_inference_graph.pb:
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https://raw.githubusercontent.com/rdeepc/herokuobjectdetection/b62992562a0ea7f85d1354d5b742c0c09dd403bf/model/frozen_inference_graph.pb
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/model/ssd_mobilenet_v1_coco_2017_11_17.pbtxt:
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1 | node {
2 | name: "image_tensor"
3 | op: "Placeholder"
4 | attr {
5 | key: "dtype"
6 | value {
7 | type: DT_UINT8
8 | }
9 | }
10 | attr {
11 | key: "shape"
12 | value {
13 | shape {
14 | dim {
15 | size: -1
16 | }
17 | dim {
18 | size: -1
19 | }
20 | dim {
21 | size: -1
22 | }
23 | dim {
24 | size: 3
25 | }
26 | }
27 | }
28 | }
29 | }
30 | node {
31 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_0/BatchNorm/batchnorm/mul_1"
32 | op: "Conv2D"
33 | input: "image_tensor"
34 | input: "FeatureExtractor/MobilenetV1/Conv2d_0/weights/read/_104__cf__107"
35 | attr {
36 | key: "padding"
37 | value {
38 | s: "SAME"
39 | }
40 | }
41 | attr {
42 | key: "strides"
43 | value {
44 | list {
45 | i: 1
46 | i: 2
47 | i: 2
48 | i: 1
49 | }
50 | }
51 | }
52 | }
53 | node {
54 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_0/BatchNorm/batchnorm/add_1"
55 | op: "Add"
56 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_0/BatchNorm/batchnorm/mul_1"
57 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_0/BatchNorm/batchnorm/sub/_103__cf__106"
58 | }
59 | node {
60 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_0/Relu6"
61 | op: "Relu6"
62 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_0/BatchNorm/batchnorm/add_1"
63 | }
64 | node {
65 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_depthwise/depthwise"
66 | op: "DepthwiseConv2dNative"
67 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_0/Relu6"
68 | input: "FeatureExtractor/MobilenetV1/Conv2d_1_depthwise/depthwise_weights/read/_101__cf__104"
69 | attr {
70 | key: "padding"
71 | value {
72 | s: "SAME"
73 | }
74 | }
75 | attr {
76 | key: "strides"
77 | value {
78 | list {
79 | i: 1
80 | i: 1
81 | i: 1
82 | i: 1
83 | }
84 | }
85 | }
86 | }
87 | node {
88 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_depthwise/BatchNorm/batchnorm/mul_1"
89 | op: "Mul"
90 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_depthwise/depthwise"
91 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_depthwise/BatchNorm/batchnorm/mul/_99__cf__102"
92 | }
93 | node {
94 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_depthwise/BatchNorm/batchnorm/add_1"
95 | op: "Add"
96 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_depthwise/BatchNorm/batchnorm/mul_1"
97 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_depthwise/BatchNorm/batchnorm/sub/_100__cf__103"
98 | }
99 | node {
100 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_depthwise/Relu6"
101 | op: "Relu6"
102 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_depthwise/BatchNorm/batchnorm/add_1"
103 | }
104 | node {
105 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_pointwise/BatchNorm/batchnorm/mul_1"
106 | op: "Conv2D"
107 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_depthwise/Relu6"
108 | input: "FeatureExtractor/MobilenetV1/Conv2d_1_pointwise/weights/read/_98__cf__101"
109 | attr {
110 | key: "padding"
111 | value {
112 | s: "SAME"
113 | }
114 | }
115 | attr {
116 | key: "strides"
117 | value {
118 | list {
119 | i: 1
120 | i: 1
121 | i: 1
122 | i: 1
123 | }
124 | }
125 | }
126 | }
127 | node {
128 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_pointwise/BatchNorm/batchnorm/add_1"
129 | op: "Add"
130 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_pointwise/BatchNorm/batchnorm/mul_1"
131 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_pointwise/BatchNorm/batchnorm/sub/_97__cf__100"
132 | }
133 | node {
134 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_pointwise/Relu6"
135 | op: "Relu6"
136 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_pointwise/BatchNorm/batchnorm/add_1"
137 | }
138 | node {
139 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_2_depthwise/depthwise"
140 | op: "DepthwiseConv2dNative"
141 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_pointwise/Relu6"
142 | input: "FeatureExtractor/MobilenetV1/Conv2d_2_depthwise/depthwise_weights/read/_95__cf__98"
143 | attr {
144 | key: "padding"
145 | value {
146 | s: "SAME"
147 | }
148 | }
149 | attr {
150 | key: "strides"
151 | value {
152 | list {
153 | i: 1
154 | i: 2
155 | i: 2
156 | i: 1
157 | }
158 | }
159 | }
160 | }
161 | node {
162 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_2_depthwise/BatchNorm/batchnorm/mul_1"
163 | op: "Mul"
164 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_2_depthwise/depthwise"
165 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_2_depthwise/BatchNorm/batchnorm/mul/_93__cf__96"
166 | }
167 | node {
168 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_2_depthwise/BatchNorm/batchnorm/add_1"
169 | op: "Add"
170 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_2_depthwise/BatchNorm/batchnorm/mul_1"
171 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_2_depthwise/BatchNorm/batchnorm/sub/_94__cf__97"
172 | }
173 | node {
174 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_2_depthwise/Relu6"
175 | op: "Relu6"
176 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_2_depthwise/BatchNorm/batchnorm/add_1"
177 | }
178 | node {
179 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_2_pointwise/BatchNorm/batchnorm/mul_1"
180 | op: "Conv2D"
181 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_2_depthwise/Relu6"
182 | input: "FeatureExtractor/MobilenetV1/Conv2d_2_pointwise/weights/read/_92__cf__95"
183 | attr {
184 | key: "padding"
185 | value {
186 | s: "SAME"
187 | }
188 | }
189 | attr {
190 | key: "strides"
191 | value {
192 | list {
193 | i: 1
194 | i: 1
195 | i: 1
196 | i: 1
197 | }
198 | }
199 | }
200 | }
201 | node {
202 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_2_pointwise/BatchNorm/batchnorm/add_1"
203 | op: "Add"
204 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_2_pointwise/BatchNorm/batchnorm/mul_1"
205 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_2_pointwise/BatchNorm/batchnorm/sub/_91__cf__94"
206 | }
207 | node {
208 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_2_pointwise/Relu6"
209 | op: "Relu6"
210 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_2_pointwise/BatchNorm/batchnorm/add_1"
211 | }
212 | node {
213 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_3_depthwise/depthwise"
214 | op: "DepthwiseConv2dNative"
215 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_2_pointwise/Relu6"
216 | input: "FeatureExtractor/MobilenetV1/Conv2d_3_depthwise/depthwise_weights/read/_89__cf__92"
217 | attr {
218 | key: "padding"
219 | value {
220 | s: "SAME"
221 | }
222 | }
223 | attr {
224 | key: "strides"
225 | value {
226 | list {
227 | i: 1
228 | i: 1
229 | i: 1
230 | i: 1
231 | }
232 | }
233 | }
234 | }
235 | node {
236 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_3_depthwise/BatchNorm/batchnorm/mul_1"
237 | op: "Mul"
238 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_3_depthwise/depthwise"
239 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_3_depthwise/BatchNorm/batchnorm/mul/_87__cf__90"
240 | }
241 | node {
242 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_3_depthwise/BatchNorm/batchnorm/add_1"
243 | op: "Add"
244 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_3_depthwise/BatchNorm/batchnorm/mul_1"
245 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_3_depthwise/BatchNorm/batchnorm/sub/_88__cf__91"
246 | }
247 | node {
248 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_3_depthwise/Relu6"
249 | op: "Relu6"
250 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_3_depthwise/BatchNorm/batchnorm/add_1"
251 | }
252 | node {
253 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_3_pointwise/BatchNorm/batchnorm/mul_1"
254 | op: "Conv2D"
255 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_3_depthwise/Relu6"
256 | input: "FeatureExtractor/MobilenetV1/Conv2d_3_pointwise/weights/read/_86__cf__89"
257 | attr {
258 | key: "padding"
259 | value {
260 | s: "SAME"
261 | }
262 | }
263 | attr {
264 | key: "strides"
265 | value {
266 | list {
267 | i: 1
268 | i: 1
269 | i: 1
270 | i: 1
271 | }
272 | }
273 | }
274 | }
275 | node {
276 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_3_pointwise/BatchNorm/batchnorm/add_1"
277 | op: "Add"
278 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_3_pointwise/BatchNorm/batchnorm/mul_1"
279 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_3_pointwise/BatchNorm/batchnorm/sub/_85__cf__88"
280 | }
281 | node {
282 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_3_pointwise/Relu6"
283 | op: "Relu6"
284 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_3_pointwise/BatchNorm/batchnorm/add_1"
285 | }
286 | node {
287 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_4_depthwise/depthwise"
288 | op: "DepthwiseConv2dNative"
289 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_3_pointwise/Relu6"
290 | input: "FeatureExtractor/MobilenetV1/Conv2d_4_depthwise/depthwise_weights/read/_83__cf__86"
291 | attr {
292 | key: "padding"
293 | value {
294 | s: "SAME"
295 | }
296 | }
297 | attr {
298 | key: "strides"
299 | value {
300 | list {
301 | i: 1
302 | i: 2
303 | i: 2
304 | i: 1
305 | }
306 | }
307 | }
308 | }
309 | node {
310 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_4_depthwise/BatchNorm/batchnorm/mul_1"
311 | op: "Mul"
312 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_4_depthwise/depthwise"
313 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_4_depthwise/BatchNorm/batchnorm/mul/_81__cf__84"
314 | }
315 | node {
316 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_4_depthwise/BatchNorm/batchnorm/add_1"
317 | op: "Add"
318 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_4_depthwise/BatchNorm/batchnorm/mul_1"
319 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_4_depthwise/BatchNorm/batchnorm/sub/_82__cf__85"
320 | }
321 | node {
322 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_4_depthwise/Relu6"
323 | op: "Relu6"
324 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_4_depthwise/BatchNorm/batchnorm/add_1"
325 | }
326 | node {
327 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_4_pointwise/BatchNorm/batchnorm/mul_1"
328 | op: "Conv2D"
329 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_4_depthwise/Relu6"
330 | input: "FeatureExtractor/MobilenetV1/Conv2d_4_pointwise/weights/read/_80__cf__83"
331 | attr {
332 | key: "padding"
333 | value {
334 | s: "SAME"
335 | }
336 | }
337 | attr {
338 | key: "strides"
339 | value {
340 | list {
341 | i: 1
342 | i: 1
343 | i: 1
344 | i: 1
345 | }
346 | }
347 | }
348 | }
349 | node {
350 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_4_pointwise/BatchNorm/batchnorm/add_1"
351 | op: "Add"
352 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_4_pointwise/BatchNorm/batchnorm/mul_1"
353 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_4_pointwise/BatchNorm/batchnorm/sub/_79__cf__82"
354 | }
355 | node {
356 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_4_pointwise/Relu6"
357 | op: "Relu6"
358 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_4_pointwise/BatchNorm/batchnorm/add_1"
359 | }
360 | node {
361 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_5_depthwise/depthwise"
362 | op: "DepthwiseConv2dNative"
363 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_4_pointwise/Relu6"
364 | input: "FeatureExtractor/MobilenetV1/Conv2d_5_depthwise/depthwise_weights/read/_77__cf__80"
365 | attr {
366 | key: "padding"
367 | value {
368 | s: "SAME"
369 | }
370 | }
371 | attr {
372 | key: "strides"
373 | value {
374 | list {
375 | i: 1
376 | i: 1
377 | i: 1
378 | i: 1
379 | }
380 | }
381 | }
382 | }
383 | node {
384 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_5_depthwise/BatchNorm/batchnorm/mul_1"
385 | op: "Mul"
386 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_5_depthwise/depthwise"
387 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_5_depthwise/BatchNorm/batchnorm/mul/_75__cf__78"
388 | }
389 | node {
390 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_5_depthwise/BatchNorm/batchnorm/add_1"
391 | op: "Add"
392 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_5_depthwise/BatchNorm/batchnorm/mul_1"
393 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_5_depthwise/BatchNorm/batchnorm/sub/_76__cf__79"
394 | }
395 | node {
396 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_5_depthwise/Relu6"
397 | op: "Relu6"
398 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_5_depthwise/BatchNorm/batchnorm/add_1"
399 | }
400 | node {
401 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_5_pointwise/BatchNorm/batchnorm/mul_1"
402 | op: "Conv2D"
403 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_5_depthwise/Relu6"
404 | input: "FeatureExtractor/MobilenetV1/Conv2d_5_pointwise/weights/read/_74__cf__77"
405 | attr {
406 | key: "padding"
407 | value {
408 | s: "SAME"
409 | }
410 | }
411 | attr {
412 | key: "strides"
413 | value {
414 | list {
415 | i: 1
416 | i: 1
417 | i: 1
418 | i: 1
419 | }
420 | }
421 | }
422 | }
423 | node {
424 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_5_pointwise/BatchNorm/batchnorm/add_1"
425 | op: "Add"
426 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_5_pointwise/BatchNorm/batchnorm/mul_1"
427 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_5_pointwise/BatchNorm/batchnorm/sub/_73__cf__76"
428 | }
429 | node {
430 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_5_pointwise/Relu6"
431 | op: "Relu6"
432 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_5_pointwise/BatchNorm/batchnorm/add_1"
433 | }
434 | node {
435 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_6_depthwise/depthwise"
436 | op: "DepthwiseConv2dNative"
437 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_5_pointwise/Relu6"
438 | input: "FeatureExtractor/MobilenetV1/Conv2d_6_depthwise/depthwise_weights/read/_71__cf__74"
439 | attr {
440 | key: "padding"
441 | value {
442 | s: "SAME"
443 | }
444 | }
445 | attr {
446 | key: "strides"
447 | value {
448 | list {
449 | i: 1
450 | i: 2
451 | i: 2
452 | i: 1
453 | }
454 | }
455 | }
456 | }
457 | node {
458 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_6_depthwise/BatchNorm/batchnorm/mul_1"
459 | op: "Mul"
460 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_6_depthwise/depthwise"
461 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_6_depthwise/BatchNorm/batchnorm/mul/_69__cf__72"
462 | }
463 | node {
464 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_6_depthwise/BatchNorm/batchnorm/add_1"
465 | op: "Add"
466 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_6_depthwise/BatchNorm/batchnorm/mul_1"
467 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_6_depthwise/BatchNorm/batchnorm/sub/_70__cf__73"
468 | }
469 | node {
470 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_6_depthwise/Relu6"
471 | op: "Relu6"
472 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_6_depthwise/BatchNorm/batchnorm/add_1"
473 | }
474 | node {
475 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_6_pointwise/BatchNorm/batchnorm/mul_1"
476 | op: "Conv2D"
477 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_6_depthwise/Relu6"
478 | input: "FeatureExtractor/MobilenetV1/Conv2d_6_pointwise/weights/read/_68__cf__71"
479 | attr {
480 | key: "padding"
481 | value {
482 | s: "SAME"
483 | }
484 | }
485 | attr {
486 | key: "strides"
487 | value {
488 | list {
489 | i: 1
490 | i: 1
491 | i: 1
492 | i: 1
493 | }
494 | }
495 | }
496 | }
497 | node {
498 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_6_pointwise/BatchNorm/batchnorm/add_1"
499 | op: "Add"
500 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_6_pointwise/BatchNorm/batchnorm/mul_1"
501 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_6_pointwise/BatchNorm/batchnorm/sub/_67__cf__70"
502 | }
503 | node {
504 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_6_pointwise/Relu6"
505 | op: "Relu6"
506 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_6_pointwise/BatchNorm/batchnorm/add_1"
507 | }
508 | node {
509 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_7_depthwise/depthwise"
510 | op: "DepthwiseConv2dNative"
511 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_6_pointwise/Relu6"
512 | input: "FeatureExtractor/MobilenetV1/Conv2d_7_depthwise/depthwise_weights/read/_65__cf__68"
513 | attr {
514 | key: "padding"
515 | value {
516 | s: "SAME"
517 | }
518 | }
519 | attr {
520 | key: "strides"
521 | value {
522 | list {
523 | i: 1
524 | i: 1
525 | i: 1
526 | i: 1
527 | }
528 | }
529 | }
530 | }
531 | node {
532 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_7_depthwise/BatchNorm/batchnorm/mul_1"
533 | op: "Mul"
534 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_7_depthwise/depthwise"
535 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_7_depthwise/BatchNorm/batchnorm/mul/_63__cf__66"
536 | }
537 | node {
538 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_7_depthwise/BatchNorm/batchnorm/add_1"
539 | op: "Add"
540 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_7_depthwise/BatchNorm/batchnorm/mul_1"
541 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_7_depthwise/BatchNorm/batchnorm/sub/_64__cf__67"
542 | }
543 | node {
544 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_7_depthwise/Relu6"
545 | op: "Relu6"
546 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_7_depthwise/BatchNorm/batchnorm/add_1"
547 | }
548 | node {
549 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_7_pointwise/BatchNorm/batchnorm/mul_1"
550 | op: "Conv2D"
551 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_7_depthwise/Relu6"
552 | input: "FeatureExtractor/MobilenetV1/Conv2d_7_pointwise/weights/read/_62__cf__65"
553 | attr {
554 | key: "padding"
555 | value {
556 | s: "SAME"
557 | }
558 | }
559 | attr {
560 | key: "strides"
561 | value {
562 | list {
563 | i: 1
564 | i: 1
565 | i: 1
566 | i: 1
567 | }
568 | }
569 | }
570 | }
571 | node {
572 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_7_pointwise/BatchNorm/batchnorm/add_1"
573 | op: "Add"
574 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_7_pointwise/BatchNorm/batchnorm/mul_1"
575 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_7_pointwise/BatchNorm/batchnorm/sub/_61__cf__64"
576 | }
577 | node {
578 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_7_pointwise/Relu6"
579 | op: "Relu6"
580 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_7_pointwise/BatchNorm/batchnorm/add_1"
581 | }
582 | node {
583 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_8_depthwise/depthwise"
584 | op: "DepthwiseConv2dNative"
585 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_7_pointwise/Relu6"
586 | input: "FeatureExtractor/MobilenetV1/Conv2d_8_depthwise/depthwise_weights/read/_59__cf__62"
587 | attr {
588 | key: "padding"
589 | value {
590 | s: "SAME"
591 | }
592 | }
593 | attr {
594 | key: "strides"
595 | value {
596 | list {
597 | i: 1
598 | i: 1
599 | i: 1
600 | i: 1
601 | }
602 | }
603 | }
604 | }
605 | node {
606 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_8_depthwise/BatchNorm/batchnorm/mul_1"
607 | op: "Mul"
608 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_8_depthwise/depthwise"
609 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_8_depthwise/BatchNorm/batchnorm/mul/_57__cf__60"
610 | }
611 | node {
612 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_8_depthwise/BatchNorm/batchnorm/add_1"
613 | op: "Add"
614 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_8_depthwise/BatchNorm/batchnorm/mul_1"
615 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_8_depthwise/BatchNorm/batchnorm/sub/_58__cf__61"
616 | }
617 | node {
618 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_8_depthwise/Relu6"
619 | op: "Relu6"
620 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_8_depthwise/BatchNorm/batchnorm/add_1"
621 | }
622 | node {
623 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_8_pointwise/BatchNorm/batchnorm/mul_1"
624 | op: "Conv2D"
625 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_8_depthwise/Relu6"
626 | input: "FeatureExtractor/MobilenetV1/Conv2d_8_pointwise/weights/read/_56__cf__59"
627 | attr {
628 | key: "padding"
629 | value {
630 | s: "SAME"
631 | }
632 | }
633 | attr {
634 | key: "strides"
635 | value {
636 | list {
637 | i: 1
638 | i: 1
639 | i: 1
640 | i: 1
641 | }
642 | }
643 | }
644 | }
645 | node {
646 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_8_pointwise/BatchNorm/batchnorm/add_1"
647 | op: "Add"
648 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_8_pointwise/BatchNorm/batchnorm/mul_1"
649 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_8_pointwise/BatchNorm/batchnorm/sub/_55__cf__58"
650 | }
651 | node {
652 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_8_pointwise/Relu6"
653 | op: "Relu6"
654 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_8_pointwise/BatchNorm/batchnorm/add_1"
655 | }
656 | node {
657 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_9_depthwise/depthwise"
658 | op: "DepthwiseConv2dNative"
659 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_8_pointwise/Relu6"
660 | input: "FeatureExtractor/MobilenetV1/Conv2d_9_depthwise/depthwise_weights/read/_53__cf__56"
661 | attr {
662 | key: "padding"
663 | value {
664 | s: "SAME"
665 | }
666 | }
667 | attr {
668 | key: "strides"
669 | value {
670 | list {
671 | i: 1
672 | i: 1
673 | i: 1
674 | i: 1
675 | }
676 | }
677 | }
678 | }
679 | node {
680 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_9_depthwise/BatchNorm/batchnorm/mul_1"
681 | op: "Mul"
682 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_9_depthwise/depthwise"
683 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_9_depthwise/BatchNorm/batchnorm/mul/_51__cf__54"
684 | }
685 | node {
686 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_9_depthwise/BatchNorm/batchnorm/add_1"
687 | op: "Add"
688 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_9_depthwise/BatchNorm/batchnorm/mul_1"
689 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_9_depthwise/BatchNorm/batchnorm/sub/_52__cf__55"
690 | }
691 | node {
692 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_9_depthwise/Relu6"
693 | op: "Relu6"
694 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_9_depthwise/BatchNorm/batchnorm/add_1"
695 | }
696 | node {
697 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_9_pointwise/BatchNorm/batchnorm/mul_1"
698 | op: "Conv2D"
699 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_9_depthwise/Relu6"
700 | input: "FeatureExtractor/MobilenetV1/Conv2d_9_pointwise/weights/read/_50__cf__53"
701 | attr {
702 | key: "padding"
703 | value {
704 | s: "SAME"
705 | }
706 | }
707 | attr {
708 | key: "strides"
709 | value {
710 | list {
711 | i: 1
712 | i: 1
713 | i: 1
714 | i: 1
715 | }
716 | }
717 | }
718 | }
719 | node {
720 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_9_pointwise/BatchNorm/batchnorm/add_1"
721 | op: "Add"
722 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_9_pointwise/BatchNorm/batchnorm/mul_1"
723 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_9_pointwise/BatchNorm/batchnorm/sub/_49__cf__52"
724 | }
725 | node {
726 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_9_pointwise/Relu6"
727 | op: "Relu6"
728 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_9_pointwise/BatchNorm/batchnorm/add_1"
729 | }
730 | node {
731 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_10_depthwise/depthwise"
732 | op: "DepthwiseConv2dNative"
733 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_9_pointwise/Relu6"
734 | input: "FeatureExtractor/MobilenetV1/Conv2d_10_depthwise/depthwise_weights/read/_47__cf__50"
735 | attr {
736 | key: "padding"
737 | value {
738 | s: "SAME"
739 | }
740 | }
741 | attr {
742 | key: "strides"
743 | value {
744 | list {
745 | i: 1
746 | i: 1
747 | i: 1
748 | i: 1
749 | }
750 | }
751 | }
752 | }
753 | node {
754 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_10_depthwise/BatchNorm/batchnorm/mul_1"
755 | op: "Mul"
756 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_10_depthwise/depthwise"
757 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_10_depthwise/BatchNorm/batchnorm/mul/_45__cf__48"
758 | }
759 | node {
760 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_10_depthwise/BatchNorm/batchnorm/add_1"
761 | op: "Add"
762 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_10_depthwise/BatchNorm/batchnorm/mul_1"
763 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_10_depthwise/BatchNorm/batchnorm/sub/_46__cf__49"
764 | }
765 | node {
766 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_10_depthwise/Relu6"
767 | op: "Relu6"
768 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_10_depthwise/BatchNorm/batchnorm/add_1"
769 | }
770 | node {
771 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_10_pointwise/BatchNorm/batchnorm/mul_1"
772 | op: "Conv2D"
773 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_10_depthwise/Relu6"
774 | input: "FeatureExtractor/MobilenetV1/Conv2d_10_pointwise/weights/read/_44__cf__47"
775 | attr {
776 | key: "padding"
777 | value {
778 | s: "SAME"
779 | }
780 | }
781 | attr {
782 | key: "strides"
783 | value {
784 | list {
785 | i: 1
786 | i: 1
787 | i: 1
788 | i: 1
789 | }
790 | }
791 | }
792 | }
793 | node {
794 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_10_pointwise/BatchNorm/batchnorm/add_1"
795 | op: "Add"
796 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_10_pointwise/BatchNorm/batchnorm/mul_1"
797 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_10_pointwise/BatchNorm/batchnorm/sub/_43__cf__46"
798 | }
799 | node {
800 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_10_pointwise/Relu6"
801 | op: "Relu6"
802 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_10_pointwise/BatchNorm/batchnorm/add_1"
803 | }
804 | node {
805 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_11_depthwise/depthwise"
806 | op: "DepthwiseConv2dNative"
807 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_10_pointwise/Relu6"
808 | input: "FeatureExtractor/MobilenetV1/Conv2d_11_depthwise/depthwise_weights/read/_41__cf__44"
809 | attr {
810 | key: "padding"
811 | value {
812 | s: "SAME"
813 | }
814 | }
815 | attr {
816 | key: "strides"
817 | value {
818 | list {
819 | i: 1
820 | i: 1
821 | i: 1
822 | i: 1
823 | }
824 | }
825 | }
826 | }
827 | node {
828 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_11_depthwise/BatchNorm/batchnorm/mul_1"
829 | op: "Mul"
830 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_11_depthwise/depthwise"
831 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_11_depthwise/BatchNorm/batchnorm/mul/_39__cf__42"
832 | }
833 | node {
834 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_11_depthwise/BatchNorm/batchnorm/add_1"
835 | op: "Add"
836 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_11_depthwise/BatchNorm/batchnorm/mul_1"
837 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_11_depthwise/BatchNorm/batchnorm/sub/_40__cf__43"
838 | }
839 | node {
840 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_11_depthwise/Relu6"
841 | op: "Relu6"
842 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_11_depthwise/BatchNorm/batchnorm/add_1"
843 | }
844 | node {
845 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_11_pointwise/BatchNorm/batchnorm/mul_1"
846 | op: "Conv2D"
847 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_11_depthwise/Relu6"
848 | input: "FeatureExtractor/MobilenetV1/Conv2d_11_pointwise/weights/read/_38__cf__41"
849 | attr {
850 | key: "padding"
851 | value {
852 | s: "SAME"
853 | }
854 | }
855 | attr {
856 | key: "strides"
857 | value {
858 | list {
859 | i: 1
860 | i: 1
861 | i: 1
862 | i: 1
863 | }
864 | }
865 | }
866 | }
867 | node {
868 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_11_pointwise/BatchNorm/batchnorm/add_1"
869 | op: "Add"
870 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_11_pointwise/BatchNorm/batchnorm/mul_1"
871 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_11_pointwise/BatchNorm/batchnorm/sub/_37__cf__40"
872 | }
873 | node {
874 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_11_pointwise/Relu6"
875 | op: "Relu6"
876 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_11_pointwise/BatchNorm/batchnorm/add_1"
877 | }
878 | node {
879 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_12_depthwise/depthwise"
880 | op: "DepthwiseConv2dNative"
881 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_11_pointwise/Relu6"
882 | input: "FeatureExtractor/MobilenetV1/Conv2d_12_depthwise/depthwise_weights/read/_35__cf__38"
883 | attr {
884 | key: "padding"
885 | value {
886 | s: "SAME"
887 | }
888 | }
889 | attr {
890 | key: "strides"
891 | value {
892 | list {
893 | i: 1
894 | i: 2
895 | i: 2
896 | i: 1
897 | }
898 | }
899 | }
900 | }
901 | node {
902 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_12_depthwise/BatchNorm/batchnorm/mul_1"
903 | op: "Mul"
904 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_12_depthwise/depthwise"
905 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_12_depthwise/BatchNorm/batchnorm/mul/_33__cf__36"
906 | }
907 | node {
908 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_12_depthwise/BatchNorm/batchnorm/add_1"
909 | op: "Add"
910 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_12_depthwise/BatchNorm/batchnorm/mul_1"
911 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_12_depthwise/BatchNorm/batchnorm/sub/_34__cf__37"
912 | }
913 | node {
914 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_12_depthwise/Relu6"
915 | op: "Relu6"
916 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_12_depthwise/BatchNorm/batchnorm/add_1"
917 | }
918 | node {
919 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_12_pointwise/BatchNorm/batchnorm/mul_1"
920 | op: "Conv2D"
921 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_12_depthwise/Relu6"
922 | input: "FeatureExtractor/MobilenetV1/Conv2d_12_pointwise/weights/read/_32__cf__35"
923 | attr {
924 | key: "padding"
925 | value {
926 | s: "SAME"
927 | }
928 | }
929 | attr {
930 | key: "strides"
931 | value {
932 | list {
933 | i: 1
934 | i: 1
935 | i: 1
936 | i: 1
937 | }
938 | }
939 | }
940 | }
941 | node {
942 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_12_pointwise/BatchNorm/batchnorm/add_1"
943 | op: "Add"
944 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_12_pointwise/BatchNorm/batchnorm/mul_1"
945 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_12_pointwise/BatchNorm/batchnorm/sub/_31__cf__34"
946 | }
947 | node {
948 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_12_pointwise/Relu6"
949 | op: "Relu6"
950 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_12_pointwise/BatchNorm/batchnorm/add_1"
951 | }
952 | node {
953 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_13_depthwise/depthwise"
954 | op: "DepthwiseConv2dNative"
955 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_12_pointwise/Relu6"
956 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_depthwise/depthwise_weights/read/_29__cf__32"
957 | attr {
958 | key: "padding"
959 | value {
960 | s: "SAME"
961 | }
962 | }
963 | attr {
964 | key: "strides"
965 | value {
966 | list {
967 | i: 1
968 | i: 1
969 | i: 1
970 | i: 1
971 | }
972 | }
973 | }
974 | }
975 | node {
976 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_13_depthwise/BatchNorm/batchnorm/mul_1"
977 | op: "Mul"
978 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_13_depthwise/depthwise"
979 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_13_depthwise/BatchNorm/batchnorm/mul/_27__cf__30"
980 | }
981 | node {
982 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_13_depthwise/BatchNorm/batchnorm/add_1"
983 | op: "Add"
984 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_13_depthwise/BatchNorm/batchnorm/mul_1"
985 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_13_depthwise/BatchNorm/batchnorm/sub/_28__cf__31"
986 | }
987 | node {
988 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_13_depthwise/Relu6"
989 | op: "Relu6"
990 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_13_depthwise/BatchNorm/batchnorm/add_1"
991 | }
992 | node {
993 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_13_pointwise/BatchNorm/batchnorm/mul_1"
994 | op: "Conv2D"
995 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_13_depthwise/Relu6"
996 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise/weights/read/_26__cf__29"
997 | attr {
998 | key: "padding"
999 | value {
1000 | s: "SAME"
1001 | }
1002 | }
1003 | attr {
1004 | key: "strides"
1005 | value {
1006 | list {
1007 | i: 1
1008 | i: 1
1009 | i: 1
1010 | i: 1
1011 | }
1012 | }
1013 | }
1014 | }
1015 | node {
1016 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_13_pointwise/BatchNorm/batchnorm/add_1"
1017 | op: "Add"
1018 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_13_pointwise/BatchNorm/batchnorm/mul_1"
1019 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_13_pointwise/BatchNorm/batchnorm/sub/_25__cf__28"
1020 | }
1021 | node {
1022 | name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_13_pointwise/Relu6"
1023 | op: "Relu6"
1024 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_13_pointwise/BatchNorm/batchnorm/add_1"
1025 | }
1026 | node {
1027 | name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_2_1x1_256/BatchNorm/batchnorm/mul_1"
1028 | op: "Conv2D"
1029 | input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_13_pointwise/Relu6"
1030 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_2_1x1_256/weights/read/_23__cf__26"
1031 | attr {
1032 | key: "padding"
1033 | value {
1034 | s: "SAME"
1035 | }
1036 | }
1037 | attr {
1038 | key: "strides"
1039 | value {
1040 | list {
1041 | i: 1
1042 | i: 1
1043 | i: 1
1044 | i: 1
1045 | }
1046 | }
1047 | }
1048 | }
1049 | node {
1050 | name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_2_1x1_256/BatchNorm/batchnorm/add_1"
1051 | op: "Add"
1052 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_2_1x1_256/BatchNorm/batchnorm/mul_1"
1053 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_2_1x1_256/BatchNorm/batchnorm/sub/_22__cf__25"
1054 | }
1055 | node {
1056 | name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_2_1x1_256/Relu6"
1057 | op: "Relu6"
1058 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_2_1x1_256/BatchNorm/batchnorm/add_1"
1059 | }
1060 | node {
1061 | name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_2_3x3_s2_512/BatchNorm/batchnorm/mul_1"
1062 | op: "Conv2D"
1063 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_2_1x1_256/Relu6"
1064 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_2_3x3_s2_512/weights/read/_20__cf__23"
1065 | attr {
1066 | key: "padding"
1067 | value {
1068 | s: "SAME"
1069 | }
1070 | }
1071 | attr {
1072 | key: "strides"
1073 | value {
1074 | list {
1075 | i: 1
1076 | i: 2
1077 | i: 2
1078 | i: 1
1079 | }
1080 | }
1081 | }
1082 | }
1083 | node {
1084 | name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_2_3x3_s2_512/BatchNorm/batchnorm/add_1"
1085 | op: "Add"
1086 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_2_3x3_s2_512/BatchNorm/batchnorm/mul_1"
1087 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_2_3x3_s2_512/BatchNorm/batchnorm/sub/_19__cf__22"
1088 | }
1089 | node {
1090 | name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_2_3x3_s2_512/Relu6"
1091 | op: "Relu6"
1092 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_2_3x3_s2_512/BatchNorm/batchnorm/add_1"
1093 | }
1094 | node {
1095 | name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_3_1x1_128/BatchNorm/batchnorm/mul_1"
1096 | op: "Conv2D"
1097 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_2_3x3_s2_512/Relu6"
1098 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_3_1x1_128/weights/read/_17__cf__20"
1099 | attr {
1100 | key: "padding"
1101 | value {
1102 | s: "SAME"
1103 | }
1104 | }
1105 | attr {
1106 | key: "strides"
1107 | value {
1108 | list {
1109 | i: 1
1110 | i: 1
1111 | i: 1
1112 | i: 1
1113 | }
1114 | }
1115 | }
1116 | }
1117 | node {
1118 | name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_3_1x1_128/BatchNorm/batchnorm/add_1"
1119 | op: "Add"
1120 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_3_1x1_128/BatchNorm/batchnorm/mul_1"
1121 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_3_1x1_128/BatchNorm/batchnorm/sub/_16__cf__19"
1122 | }
1123 | node {
1124 | name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_3_1x1_128/Relu6"
1125 | op: "Relu6"
1126 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_3_1x1_128/BatchNorm/batchnorm/add_1"
1127 | }
1128 | node {
1129 | name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/BatchNorm/batchnorm/mul_1"
1130 | op: "Conv2D"
1131 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_3_1x1_128/Relu6"
1132 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/weights/read/_14__cf__17"
1133 | attr {
1134 | key: "padding"
1135 | value {
1136 | s: "SAME"
1137 | }
1138 | }
1139 | attr {
1140 | key: "strides"
1141 | value {
1142 | list {
1143 | i: 1
1144 | i: 2
1145 | i: 2
1146 | i: 1
1147 | }
1148 | }
1149 | }
1150 | }
1151 | node {
1152 | name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/BatchNorm/batchnorm/add_1"
1153 | op: "Add"
1154 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/BatchNorm/batchnorm/mul_1"
1155 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/BatchNorm/batchnorm/sub/_13__cf__16"
1156 | }
1157 | node {
1158 | name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/Relu6"
1159 | op: "Relu6"
1160 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/BatchNorm/batchnorm/add_1"
1161 | }
1162 | node {
1163 | name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/BatchNorm/batchnorm/mul_1"
1164 | op: "Conv2D"
1165 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/Relu6"
1166 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/weights/read/_11__cf__14"
1167 | attr {
1168 | key: "padding"
1169 | value {
1170 | s: "SAME"
1171 | }
1172 | }
1173 | attr {
1174 | key: "strides"
1175 | value {
1176 | list {
1177 | i: 1
1178 | i: 1
1179 | i: 1
1180 | i: 1
1181 | }
1182 | }
1183 | }
1184 | }
1185 | node {
1186 | name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/BatchNorm/batchnorm/add_1"
1187 | op: "Add"
1188 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/BatchNorm/batchnorm/mul_1"
1189 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/BatchNorm/batchnorm/sub/_10__cf__13"
1190 | }
1191 | node {
1192 | name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/Relu6"
1193 | op: "Relu6"
1194 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/BatchNorm/batchnorm/add_1"
1195 | }
1196 | node {
1197 | name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/BatchNorm/batchnorm/mul_1"
1198 | op: "Conv2D"
1199 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/Relu6"
1200 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/weights/read/_8__cf__11"
1201 | attr {
1202 | key: "padding"
1203 | value {
1204 | s: "SAME"
1205 | }
1206 | }
1207 | attr {
1208 | key: "strides"
1209 | value {
1210 | list {
1211 | i: 1
1212 | i: 2
1213 | i: 2
1214 | i: 1
1215 | }
1216 | }
1217 | }
1218 | }
1219 | node {
1220 | name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/BatchNorm/batchnorm/add_1"
1221 | op: "Add"
1222 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/BatchNorm/batchnorm/mul_1"
1223 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/BatchNorm/batchnorm/sub/_7__cf__10"
1224 | }
1225 | node {
1226 | name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/Relu6"
1227 | op: "Relu6"
1228 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/BatchNorm/batchnorm/add_1"
1229 | }
1230 | node {
1231 | name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_5_1x1_64/BatchNorm/batchnorm/mul_1"
1232 | op: "Conv2D"
1233 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/Relu6"
1234 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_5_1x1_64/weights/read/_5__cf__8"
1235 | attr {
1236 | key: "padding"
1237 | value {
1238 | s: "SAME"
1239 | }
1240 | }
1241 | attr {
1242 | key: "strides"
1243 | value {
1244 | list {
1245 | i: 1
1246 | i: 1
1247 | i: 1
1248 | i: 1
1249 | }
1250 | }
1251 | }
1252 | }
1253 | node {
1254 | name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_5_1x1_64/BatchNorm/batchnorm/add_1"
1255 | op: "Add"
1256 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_5_1x1_64/BatchNorm/batchnorm/mul_1"
1257 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_5_1x1_64/BatchNorm/batchnorm/sub/_4__cf__7"
1258 | }
1259 | node {
1260 | name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_5_1x1_64/Relu6"
1261 | op: "Relu6"
1262 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_5_1x1_64/BatchNorm/batchnorm/add_1"
1263 | }
1264 | node {
1265 | name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_5_3x3_s2_128/BatchNorm/batchnorm/mul_1"
1266 | op: "Conv2D"
1267 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_5_1x1_64/Relu6"
1268 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_5_3x3_s2_128/weights/read/_2__cf__5"
1269 | attr {
1270 | key: "padding"
1271 | value {
1272 | s: "SAME"
1273 | }
1274 | }
1275 | attr {
1276 | key: "strides"
1277 | value {
1278 | list {
1279 | i: 1
1280 | i: 2
1281 | i: 2
1282 | i: 1
1283 | }
1284 | }
1285 | }
1286 | }
1287 | node {
1288 | name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_5_3x3_s2_128/BatchNorm/batchnorm/add_1"
1289 | op: "Add"
1290 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_5_3x3_s2_128/BatchNorm/batchnorm/mul_1"
1291 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_5_3x3_s2_128/BatchNorm/batchnorm/sub/_1__cf__4"
1292 | }
1293 | node {
1294 | name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_5_3x3_s2_128/Relu6"
1295 | op: "Relu6"
1296 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_5_3x3_s2_128/BatchNorm/batchnorm/add_1"
1297 | }
1298 | node {
1299 | name: "BoxPredictor_5/BoxEncodingPredictor/Conv2D"
1300 | op: "Conv2D"
1301 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_5_3x3_s2_128/Relu6"
1302 | input: "BoxPredictor_5/BoxEncodingPredictor/weights/read/_106__cf__109"
1303 | attr {
1304 | key: "padding"
1305 | value {
1306 | s: "SAME"
1307 | }
1308 | }
1309 | attr {
1310 | key: "strides"
1311 | value {
1312 | list {
1313 | i: 1
1314 | i: 1
1315 | i: 1
1316 | i: 1
1317 | }
1318 | }
1319 | }
1320 | }
1321 | node {
1322 | name: "BoxPredictor_5/BoxEncodingPredictor/BiasAdd"
1323 | op: "BiasAdd"
1324 | input: "BoxPredictor_5/BoxEncodingPredictor/Conv2D"
1325 | input: "BoxPredictor_5/BoxEncodingPredictor/biases/read/_105__cf__108"
1326 | }
1327 | node {
1328 | name: "BoxPredictor_5/ClassPredictor/Conv2D"
1329 | op: "Conv2D"
1330 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_5_3x3_s2_128/Relu6"
1331 | input: "BoxPredictor_5/ClassPredictor/weights/read/_168__cf__171"
1332 | attr {
1333 | key: "padding"
1334 | value {
1335 | s: "SAME"
1336 | }
1337 | }
1338 | attr {
1339 | key: "strides"
1340 | value {
1341 | list {
1342 | i: 1
1343 | i: 1
1344 | i: 1
1345 | i: 1
1346 | }
1347 | }
1348 | }
1349 | }
1350 | node {
1351 | name: "BoxPredictor_5/ClassPredictor/BiasAdd"
1352 | op: "BiasAdd"
1353 | input: "BoxPredictor_5/ClassPredictor/Conv2D"
1354 | input: "BoxPredictor_5/ClassPredictor/biases/read/_167__cf__170"
1355 | }
1356 | node {
1357 | name: "BoxPredictor_4/BoxEncodingPredictor/Conv2D"
1358 | op: "Conv2D"
1359 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/Relu6"
1360 | input: "BoxPredictor_4/BoxEncodingPredictor/weights/read/_108__cf__111"
1361 | attr {
1362 | key: "padding"
1363 | value {
1364 | s: "SAME"
1365 | }
1366 | }
1367 | attr {
1368 | key: "strides"
1369 | value {
1370 | list {
1371 | i: 1
1372 | i: 1
1373 | i: 1
1374 | i: 1
1375 | }
1376 | }
1377 | }
1378 | }
1379 | node {
1380 | name: "BoxPredictor_4/BoxEncodingPredictor/BiasAdd"
1381 | op: "BiasAdd"
1382 | input: "BoxPredictor_4/BoxEncodingPredictor/Conv2D"
1383 | input: "BoxPredictor_4/BoxEncodingPredictor/biases/read/_107__cf__110"
1384 | }
1385 | node {
1386 | name: "BoxPredictor_4/ClassPredictor/Conv2D"
1387 | op: "Conv2D"
1388 | input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/Relu6"
1389 | input: "BoxPredictor_4/ClassPredictor/weights/read/_170__cf__173"
1390 | attr {
1391 | key: "padding"
1392 | value {
1393 | s: "SAME"
1394 | }
1395 | }
1396 | attr {
1397 | key: "strides"
1398 | value {
1399 | list {
1400 | i: 1
1401 | i: 1
1402 | i: 1
1403 | i: 1
1404 | }
1405 | }
1406 | }
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2178 | input: "PriorBox_0"
2179 | input: "PriorBox_1"
2180 | input: "PriorBox_2"
2181 | input: "PriorBox_3"
2182 | input: "PriorBox_4"
2183 | input: "PriorBox_5"
2184 | input: "concat/axis_flatten"
2185 | }
2186 | node {
2187 | name: "ClassPredictor/concat/sigmoid"
2188 | op: "Sigmoid"
2189 | input: "ClassPredictor/concat"
2190 | }
2191 | node {
2192 | name: "detection_out"
2193 | op: "DetectionOutput"
2194 | input: "BoxEncodingPredictor/concat"
2195 | input: "ClassPredictor/concat/sigmoid"
2196 | input: "PriorBox/concat"
2197 | attr {
2198 | key: "background_label_id"
2199 | value {
2200 | i: 0
2201 | }
2202 | }
2203 | attr {
2204 | key: "code_type"
2205 | value {
2206 | s: "CENTER_SIZE"
2207 | }
2208 | }
2209 | attr {
2210 | key: "confidence_threshold"
2211 | value {
2212 | f: 0.00999999977648
2213 | }
2214 | }
2215 | attr {
2216 | key: "keep_top_k"
2217 | value {
2218 | i: 100
2219 | }
2220 | }
2221 | attr {
2222 | key: "loc_pred_transposed"
2223 | value {
2224 | b: true
2225 | }
2226 | }
2227 | attr {
2228 | key: "nms_threshold"
2229 | value {
2230 | f: 0.600000023842
2231 | }
2232 | }
2233 | attr {
2234 | key: "num_classes"
2235 | value {
2236 | i: 91
2237 | }
2238 | }
2239 | attr {
2240 | key: "share_location"
2241 | value {
2242 | b: true
2243 | }
2244 | }
2245 | attr {
2246 | key: "top_k"
2247 | value {
2248 | i: 100
2249 | }
2250 | }
2251 | }
2252 | library {
2253 | }
2254 |
--------------------------------------------------------------------------------
/requirements.txt:
--------------------------------------------------------------------------------
1 | opencv-python
2 | numpy
3 | flask
4 | pillow
5 | gunicorn
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/templates/index.html:
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1 |
2 |
3 |
4 |
5 |
6 | Object detection Demo
7 |
8 |
17 |
18 |
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