├── README.md ├── __init__.py ├── config.py ├── driver ├── __init__.py ├── __init__.pyc ├── cam.py ├── cam.pyc ├── face_search.py ├── face_search.pyc └── haarcascade_frontalface_alt.xml ├── font └── fzyy.TTF ├── images ├── black.jpg ├── mark.jpg ├── mask.jpg └── yellow.png ├── models ├── cnn_deploy.prototxt └── cnn_iter_3560000.caffemodel ├── tmp └── buffer └── ui ├── __init__.py ├── frame.py ├── frame.pyc ├── frame.ui ├── launcher.py ├── launcher_sing_face.py ├── save_face.py ├── save_face.pyc ├── save_face.ui ├── sign_face.py ├── sign_face.pyc └── sign_face.ui /README.md: -------------------------------------------------------------------------------- 1 | ## 基于CNN的人脸识别考勤demo 2 | 3 | ### 是什么 4 | - 帮朋友写的一个基于CNN的人脸识别考勤项目 5 | - 可以进行 人脸+姓名录入 6 | - 可以识别已经录入的人脸，返回人脸对应的姓名和相似度 7 | 8 | ### 环境 9 | - python2.7 10 | - linux 11 | - caffe+gpu 12 | - python opencv 13 | - pyqt5 14 | - python pil 15 | 16 | ### 如何运行 17 | - 运行 launcher_sing_face.py, 摄像头录入人脸，标记人脸姓名 18 | - 运行 launcher.py，摄像头识别人脸，并找到与已知人脸相似度最高的人脸的姓名 19 | 20 | 21 | -------------------------------------------------------------------------------- /__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/reece15/cnn_face_detection/d4274440050ae31f345eaa298ab2477b77c16cae/__init__.py -------------------------------------------------------------------------------- /config.py: -------------------------------------------------------------------------------- 1 | # coding: utf-8 2 | 3 | import os 4 | 5 | 6 | BASE_PATH = os.path.dirname(os.path.abspath(__file__)) 7 | 8 | MODEL_PATH = os.path.join(BASE_PATH, "models") 9 | 10 | DATA_PATH = os.path.join(BASE_PATH, "data") 11 | 12 | IMG_PATH = os.path.join(BASE_PATH, "images") 13 | 14 | FACE_POINT = 8 15 | 16 | BUFFER_DIR = os.path.join(BASE_PATH, "tmp") 17 | 18 | FONT_PATH = os.path.join(BASE_PATH, "font") 19 | 20 | TH = 0.7 -------------------------------------------------------------------------------- /driver/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/reece15/cnn_face_detection/d4274440050ae31f345eaa298ab2477b77c16cae/driver/__init__.py -------------------------------------------------------------------------------- /driver/__init__.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/reece15/cnn_face_detection/d4274440050ae31f345eaa298ab2477b77c16cae/driver/__init__.pyc -------------------------------------------------------------------------------- /driver/cam.py: -------------------------------------------------------------------------------- 1 | # coding:utf-8 2 | 3 | import cv2 4 | import config 5 | import os 6 | import numpy 7 | from PIL import Image, ImageFont, ImageDraw 8 | ttfont = ImageFont.truetype(os.path.join(config.FONT_PATH, "fzyy.TTF"), 26) 9 | 10 | 11 | class Cam(object): 12 | 13 | CONFIG_PATH = "haarcascade_frontalface_alt.xml" 14 | 15 | def __init__(self): 16 | self.cap = cv2.VideoCapture(0) 17 | self.fps = self.cap.get(cv2.CAP_PROP_FPS) 18 | self.classifier = cv2.CascadeClassifier(os.path.join(os.path.dirname(os.path.abspath(__file__)), self.CONFIG_PATH)) 19 | self.mark = Image.open(os.path.join(config.IMG_PATH, "yellow.png")) 20 | 21 | def get_photo(self): 22 | if self.cap.isOpened(): 23 | ret, img = self.cap.read() 24 | if ret: 25 | h, w = img.shape[:2] 26 | min_size = (int(h/config.FACE_POINT), int(w/config.FACE_POINT)) 27 | face_rects = self.classifier.detectMultiScale(img, 1.2, 2, cv2.CASCADE_SCALE_IMAGE, min_size) 28 | if len(face_rects) > 0: 29 | return img, face_rects[0] 30 | return img, None 31 | return None, None 32 | 33 | def draw_text(self, img, face_rects, text=u"welcome admin"): 34 | x, y, h, w = face_rects 35 | # cv2.rectangle(img, (int(x), int(y)), (int(x) + int(w), int(y) + int(h)), (0, 255, 0), 2, 0) 36 | image = Image.fromarray(cv2.cvtColor(img, cv2.COLOR_BGR2RGB)) 37 | draw = ImageDraw.Draw(image) 38 | out = self.mark.resize((w + 50, h + 20)) 39 | image.paste(out, (x - 20, y - 15), mask=out) 40 | draw.text((int(x + 20), int(y - 20)), text, fill="red", font=ttfont) 41 | 42 | img = cv2.cvtColor(numpy.asarray(image), cv2.COLOR_RGB2BGR) 43 | 44 | return img 45 | 46 | def show_image(self, image): 47 | pass 48 | 49 | 50 | cams = Cam() 51 | 52 | 53 | if __name__ == "__main__": 54 | while True: 55 | 56 | photo, face = cams.get_photo() 57 | if photo is None: 58 | break 59 | cv2.imshow("img", photo) 60 | k = cv2.waitKey(1) 61 | if(k== ord('q')): 62 | break -------------------------------------------------------------------------------- /driver/cam.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/reece15/cnn_face_detection/d4274440050ae31f345eaa298ab2477b77c16cae/driver/cam.pyc -------------------------------------------------------------------------------- /driver/face_search.py: -------------------------------------------------------------------------------- 1 | # coding:utf-8 2 | import os 3 | import config 4 | import caffe 5 | import cv2 6 | import numpy as np 7 | import matplotlib.pyplot as plt 8 | import scipy 9 | import re 10 | 11 | cnn_model = os.path.join(config.MODEL_PATH, "cnn_iter_3560000.caffemodel") 12 | pro_txt = os.path.join(config.MODEL_PATH, "cnn_deploy.prototxt") 13 | 14 | 15 | def load_cnn_net(): 16 | caffe.set_mode_cpu() 17 | net = caffe.Net(pro_txt, cnn_model, caffe.TEST) 18 | return net 19 | 20 | 21 | def load_image_paths(p): 22 | res = [] 23 | if os.path.isdir(p): 24 | files = os.listdir(p) 25 | for file in files: 26 | f = os.path.join(config.DATA_PATH, file) 27 | yield f 28 | res.append(f) 29 | 30 | 31 | def load_feats(net, images): 32 | feats = np.zeros((100, 256), dtype=np.float32) 33 | inp = [] 34 | for i, image in enumerate(images): 35 | input = cv2.imread(image, 0) 36 | input = cv2.resize(input, (128, 128), interpolation=cv2.INTER_CUBIC) 37 | inp.append(input) 38 | img_blobinp = input[np.newaxis, np.newaxis, :, :] / 255.0 39 | net.blobs['data'].reshape(*img_blobinp.shape) 40 | net.blobs['data'].data[...] = img_blobinp 41 | net.blobs['data'].data.shape 42 | net.forward() 43 | feature = net.blobs['eltwise_fc1'].data 44 | feats[i, :] = feature 45 | return feats, inp 46 | 47 | 48 | def load_feat(image, net): 49 | 50 | input = cv2.resize(image, (128, 128), interpolation=cv2.INTER_CUBIC) 51 | img_blobinp = input[np.newaxis, np.newaxis, :, :] / 255.0 52 | net.blobs['data'].reshape(*img_blobinp.shape) 53 | net.blobs['data'].data[...] = img_blobinp 54 | net.blobs['data'].data.shape 55 | out = net.forward() 56 | feature = net.blobs['eltwise_fc1'].data 57 | return feature 58 | 59 | 60 | def search_one(feat, feats, images): 61 | 62 | max_s = 0 63 | max_item = None 64 | for index, item in enumerate(images): 65 | s = scipy.spatial.distance.cosine(feats[index, :], feat) 66 | similar = 1 - s 67 | print similar, s 68 | if similar > max_s: 69 | max_s = similar 70 | max_item = index 71 | 72 | return max_s, max_item, re.split("[\./]", images[max_item])[-2] 73 | 74 | net = load_cnn_net() 75 | images = list(load_image_paths(config.DATA_PATH)) 76 | feats, inps =load_feats(net, images) 77 | 78 | -------------------------------------------------------------------------------- /driver/face_search.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/reece15/cnn_face_detection/d4274440050ae31f345eaa298ab2477b77c16cae/driver/face_search.pyc -------------------------------------------------------------------------------- /font/fzyy.TTF: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/reece15/cnn_face_detection/d4274440050ae31f345eaa298ab2477b77c16cae/font/fzyy.TTF -------------------------------------------------------------------------------- /images/black.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/reece15/cnn_face_detection/d4274440050ae31f345eaa298ab2477b77c16cae/images/black.jpg -------------------------------------------------------------------------------- /images/mark.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/reece15/cnn_face_detection/d4274440050ae31f345eaa298ab2477b77c16cae/images/mark.jpg -------------------------------------------------------------------------------- /images/mask.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/reece15/cnn_face_detection/d4274440050ae31f345eaa298ab2477b77c16cae/images/mask.jpg -------------------------------------------------------------------------------- /images/yellow.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/reece15/cnn_face_detection/d4274440050ae31f345eaa298ab2477b77c16cae/images/yellow.png -------------------------------------------------------------------------------- /models/cnn_deploy.prototxt: -------------------------------------------------------------------------------- 1 | name: "LCNN_net" 2 | input: "data" 3 | input_dim: 1 4 | input_dim: 1 5 | input_dim: 128 6 | input_dim: 128 7 | layer{ 8 | name: "conv1" 9 | type: "Convolution" 10 | bottom: "data" 11 | top: "conv1" 12 | param{ 13 | lr_mult:1 14 | decay_mult:1 15 | } 16 | param{ 17 | lr_mult:2 18 | decay_mult:0 19 | } 20 | convolution_param { 21 | num_output: 96 22 | kernel_size: 5 23 | stride: 1 24 | pad: 2 25 | weight_filler { 26 | type: "xavier" 27 | } 28 | bias_filler { 29 | type: "constant" 30 | value: 0.1 31 | } 32 | } 33 | } 34 | layer{ 35 | name: "slice1" 36 | type:"Slice" 37 | slice_param { 38 | slice_dim: 1 39 | } 40 | bottom: "conv1" 41 | top: "slice1_1" 42 | top: "slice1_2" 43 | } 44 | layer{ 45 | name: "etlwise1" 46 | type: "Eltwise" 47 | bottom: "slice1_1" 48 | bottom: "slice1_2" 49 | top: "eltwise1" 50 | eltwise_param { 51 | operation: MAX 52 | } 53 | } 54 | layer{ 55 | name: "pool1" 56 | type: "Pooling" 57 | pooling_param { 58 | pool: MAX 59 | kernel_size: 2 60 | stride: 2 61 | } 62 | bottom: "eltwise1" 63 | top: "pool1" 64 | } 65 | 66 | layer{ 67 | name: "conv2a" 68 | type: "Convolution" 69 | bottom: "pool1" 70 | top: "conv2a" 71 | param{ 72 | lr_mult:1 73 | decay_mult:1 74 | } 75 | param{ 76 | lr_mult:2 77 | decay_mult:0 78 | } 79 | convolution_param { 80 | num_output: 96 81 | kernel_size: 1 82 | stride: 1 83 | weight_filler { 84 | type: "xavier" 85 | } 86 | bias_filler { 87 | type: "constant" 88 | value: 0.1 89 | } 90 | } 91 | } 92 | layer{ 93 | name: "slice2a" 94 | type:"Slice" 95 | slice_param { 96 | slice_dim: 1 97 | } 98 | bottom: "conv2a" 99 | top: "slice2a_1" 100 | top: "slice2a_2" 101 | } 102 | layer{ 103 | name: "etlwise2a" 104 | type: "Eltwise" 105 | bottom: "slice2a_1" 106 | bottom: "slice2a_2" 107 | top: "eltwise2a" 108 | eltwise_param { 109 | operation: MAX 110 | } 111 | } 112 | 113 | layer{ 114 | name: "conv2" 115 | type: "Convolution" 116 | bottom: "eltwise2a" 117 | top: "conv2" 118 | param{ 119 | lr_mult:1 120 | decay_mult:1 121 | } 122 | param{ 123 | lr_mult:2 124 | decay_mult:0 125 | } 126 | convolution_param { 127 | num_output: 192 128 | kernel_size: 3 129 | stride: 1 130 | pad: 1 131 | weight_filler { 132 | type: "xavier" 133 | } 134 | bias_filler { 135 | type: "constant" 136 | value: 0.1 137 | } 138 | } 139 | 140 | } 141 | layer{ 142 | name: "slice2" 143 | type:"Slice" 144 | slice_param { 145 | slice_dim: 1 146 | } 147 | bottom: "conv2" 148 | top: "slice2_1" 149 | top: "slice2_2" 150 | } 151 | layer{ 152 | name: "etlwise2" 153 | type: "Eltwise" 154 | bottom: "slice2_1" 155 | bottom: "slice2_2" 156 | top: "eltwise2" 157 | eltwise_param { 158 | operation: MAX 159 | } 160 | } 161 | layer{ 162 | name: "pool2" 163 | type: "Pooling" 164 | pooling_param { 165 | pool: MAX 166 | kernel_size: 2 167 | stride: 2 168 | } 169 | bottom: "eltwise2" 170 | top: "pool2" 171 | } 172 | 173 | layer{ 174 | name: "conv3a" 175 | type: "Convolution" 176 | bottom: "pool2" 177 | top: "conv3a" 178 | param{ 179 | lr_mult:1 180 | decay_mult:1 181 | } 182 | param{ 183 | lr_mult:2 184 | decay_mult:0 185 | } 186 | convolution_param { 187 | num_output: 192 188 | kernel_size: 1 189 | stride: 1 190 | weight_filler { 191 | type: "xavier" 192 | } 193 | bias_filler { 194 | type: "constant" 195 | value: 0.1 196 | } 197 | } 198 | } 199 | layer{ 200 | name: "slice3a" 201 | type:"Slice" 202 | slice_param { 203 | slice_dim: 1 204 | } 205 | bottom: "conv3a" 206 | top: "slice3a_1" 207 | top: "slice3a_2" 208 | } 209 | layer{ 210 | name: "etlwise3a" 211 | type: "Eltwise" 212 | bottom: "slice3a_1" 213 | bottom: "slice3a_2" 214 | top: "eltwise3a" 215 | eltwise_param { 216 | operation: MAX 217 | } 218 | } 219 | 220 | layer{ 221 | name: "conv3" 222 | type: "Convolution" 223 | bottom: "eltwise3a" 224 | top: "conv3" 225 | param{ 226 | lr_mult:1 227 | decay_mult:1 228 | } 229 | param{ 230 | lr_mult:2 231 | decay_mult:0 232 | } 233 | convolution_param { 234 | num_output: 384 235 | kernel_size: 3 236 | stride: 1 237 | pad: 1 238 | weight_filler { 239 | type: "xavier" 240 | } 241 | bias_filler { 242 | type: "constant" 243 | value: 0.1 244 | } 245 | } 246 | } 247 | layer{ 248 | name: "slice3" 249 | type:"Slice" 250 | slice_param { 251 | slice_dim: 1 252 | } 253 | bottom: "conv3" 254 | top: "slice3_1" 255 | top: "slice3_2" 256 | } 257 | layer{ 258 | name: "etlwise3" 259 | type: "Eltwise" 260 | bottom: "slice3_1" 261 | bottom: "slice3_2" 262 | top: "eltwise3" 263 | eltwise_param { 264 | operation: MAX 265 | } 266 | } 267 | layer{ 268 | name: "pool3" 269 | type: "Pooling" 270 | pooling_param { 271 | pool: MAX 272 | kernel_size: 2 273 | stride: 2 274 | } 275 | bottom: "eltwise3" 276 | top: "pool3" 277 | } 278 | 279 | layer{ 280 | name: "conv4a" 281 | type: "Convolution" 282 | bottom: "pool3" 283 | top: "conv4a" 284 | param{ 285 | lr_mult:1 286 | decay_mult:1 287 | } 288 | param{ 289 | lr_mult:2 290 | decay_mult:0 291 | } 292 | convolution_param{ 293 | num_output: 384 294 | kernel_size: 1 295 | stride: 1 296 | weight_filler{ 297 | type:"xavier" 298 | } 299 | bias_filler{ 300 | type: "constant" 301 | value: 0.1 302 | } 303 | } 304 | } 305 | layer{ 306 | name: "slice4a" 307 | type:"Slice" 308 | slice_param { 309 | slice_dim: 1 310 | } 311 | bottom: "conv4a" 312 | top: "slice4a_1" 313 | top: "slice4a_2" 314 | } 315 | layer{ 316 | name: "etlwise4a" 317 | type: "Eltwise" 318 | bottom: "slice4a_1" 319 | bottom: "slice4a_2" 320 | top: "eltwise4a" 321 | eltwise_param { 322 | operation: MAX 323 | } 324 | } 325 | layer{ 326 | name: "conv4" 327 | type: "Convolution" 328 | bottom: "eltwise4a" 329 | top: "conv4" 330 | param{ 331 | lr_mult:1 332 | decay_mult:1 333 | } 334 | param{ 335 | lr_mult:2 336 | decay_mult:0 337 | } 338 | convolution_param{ 339 | num_output: 256 340 | kernel_size: 3 341 | stride: 1 342 | pad: 1 343 | weight_filler{ 344 | type:"xavier" 345 | } 346 | bias_filler{ 347 | type: "constant" 348 | value: 0.1 349 | } 350 | } 351 | } 352 | layer{ 353 | name: "slice4" 354 | type:"Slice" 355 | slice_param { 356 | slice_dim: 1 357 | } 358 | bottom: "conv4" 359 | top: "slice4_1" 360 | top: "slice4_2" 361 | } 362 | layer{ 363 | name: "etlwise4" 364 | type: "Eltwise" 365 | bottom: "slice4_1" 366 | bottom: "slice4_2" 367 | top: "eltwise4" 368 | eltwise_param { 369 | operation: MAX 370 | } 371 | } 372 | 373 | layer{ 374 | name: "conv5a" 375 | type: "Convolution" 376 | bottom: "eltwise4" 377 | top: "conv5a" 378 | param{ 379 | lr_mult:1 380 | decay_mult:1 381 | } 382 | param{ 383 | lr_mult:2 384 | decay_mult:0 385 | } 386 | convolution_param{ 387 | num_output: 256 388 | kernel_size: 1 389 | stride: 1 390 | weight_filler{ 391 | type:"xavier" 392 | } 393 | bias_filler{ 394 | type: "constant" 395 | value: 0.1 396 | } 397 | } 398 | } 399 | layer{ 400 | name: "slice5a" 401 | type:"Slice" 402 | slice_param { 403 | slice_dim: 1 404 | } 405 | bottom: "conv5a" 406 | top: "slice5a_1" 407 | top: "slice5a_2" 408 | } 409 | layer{ 410 | name: "etlwise5a" 411 | type: "Eltwise" 412 | bottom: "slice5a_1" 413 | bottom: "slice5a_2" 414 | top: "eltwise5a" 415 | eltwise_param { 416 | operation: MAX 417 | } 418 | } 419 | layer{ 420 | name: "conv5" 421 | type: "Convolution" 422 | bottom: "eltwise5a" 423 | top: "conv5" 424 | param{ 425 | lr_mult:1 426 | decay_mult:1 427 | } 428 | param{ 429 | lr_mult:2 430 | decay_mult:0 431 | } 432 | convolution_param{ 433 | num_output: 256 434 | kernel_size: 3 435 | stride: 1 436 | pad: 1 437 | weight_filler{ 438 | type:"xavier" 439 | } 440 | bias_filler{ 441 | type: "constant" 442 | value: 0.1 443 | } 444 | } 445 | } 446 | layer{ 447 | name: "slice5" 448 | type:"Slice" 449 | slice_param { 450 | slice_dim: 1 451 | } 452 | bottom: "conv5" 453 | top: "slice5_1" 454 | top: "slice5_2" 455 | } 456 | layer{ 457 | name: "etlwise5" 458 | type: "Eltwise" 459 | bottom: "slice5_1" 460 | bottom: "slice5_2" 461 | top: "eltwise5" 462 | eltwise_param { 463 | operation: MAX 464 | } 465 | } 466 | 467 | layer{ 468 | name: "pool4" 469 | type: "Pooling" 470 | pooling_param { 471 | pool: MAX 472 | kernel_size: 2 473 | stride: 2 474 | } 475 | bottom: "eltwise5" 476 | top: "pool4" 477 | } 478 | 479 | layer{ 480 | name: "fc1" 481 | type: "InnerProduct" 482 | bottom: "pool4" 483 | top: "fc1" 484 | param{ 485 | lr_mult:1 486 | decay_mult:1 487 | } 488 | param{ 489 | lr_mult:2 490 | decay_mult:0 491 | } 492 | inner_product_param { 493 | num_output: 512 494 | weight_filler { 495 | type: "xavier" 496 | } 497 | bias_filler { 498 | type: "constant" 499 | value: 0.1 500 | } 501 | } 502 | } 503 | layer{ 504 | name: "slice_fc1" 505 | type:"Slice" 506 | slice_param { 507 | slice_dim: 1 508 | } 509 | bottom: "fc1" 510 | top: "slice_fc1_1" 511 | top: "slice_fc1_2" 512 | } 513 | layer{ 514 | name: "eltwise_fc1" 515 | type: "Eltwise" 516 | bottom: "slice_fc1_1" 517 | bottom: "slice_fc1_2" 518 | top: "eltwise_fc1" 519 | eltwise_param { 520 | operation: MAX 521 | } 522 | } 523 | # don't need dropout when testing. 524 | -------------------------------------------------------------------------------- /models/cnn_iter_3560000.caffemodel: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/reece15/cnn_face_detection/d4274440050ae31f345eaa298ab2477b77c16cae/models/cnn_iter_3560000.caffemodel -------------------------------------------------------------------------------- /tmp/buffer: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/reece15/cnn_face_detection/d4274440050ae31f345eaa298ab2477b77c16cae/tmp/buffer -------------------------------------------------------------------------------- /ui/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/reece15/cnn_face_detection/d4274440050ae31f345eaa298ab2477b77c16cae/ui/__init__.py -------------------------------------------------------------------------------- /ui/frame.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | 3 | # Form implementation generated from reading ui file 'frame.ui' 4 | # 5 | # Created by: PyQt5 UI code generator 5.10.1 6 | # 7 | # WARNING! All changes made in this file will be lost! 8 | 9 | from PyQt5 import QtCore, QtGui, QtWidgets 10 | import os 11 | from config import IMG_PATH 12 | 13 | class Ui_MainWindow(object): 14 | def setupUi(self, MainWindow): 15 | MainWindow.setObjectName("MainWindow") 16 | 17 | MainWindow.resize(835, 517) 18 | self.centralwidget = QtWidgets.QWidget(MainWindow) 19 | self.centralwidget.setObjectName("centralwidget") 20 | self.label = QtWidgets.QLabel(self.centralwidget) 21 | self.label.setEnabled(False) 22 | self.label.setGeometry(QtCore.QRect(50, 400, 721, 51)) 23 | 24 | 25 | font = QtGui.QFont() 26 | font.setFamily("TlwgTypewriter") 27 | font.setPointSize(24) 28 | font.setBold(False) 29 | font.setItalic(False) 30 | font.setWeight(50) 31 | font.setStrikeOut(False) 32 | font.setKerning(True) 33 | self.label.setFont(font) 34 | self.label.setAccessibleName("") 35 | self.label.setLayoutDirection(QtCore.Qt.LeftToRight) 36 | self.label.setAlignment(QtCore.Qt.AlignCenter) 37 | self.label.setObjectName("label") 38 | self.calendarWidget = QtWidgets.QCalendarWidget(self.centralwidget) 39 | self.calendarWidget.setEnabled(False) 40 | self.calendarWidget.setGeometry(QtCore.QRect(350, 130, 451, 201)) 41 | self.calendarWidget.setNavigationBarVisible(False) 42 | self.calendarWidget.setDateEditEnabled(False) 43 | self.calendarWidget.setObjectName("calendarWidget") 44 | self.timeEdit = QtWidgets.QTimeEdit(self.centralwidget) 45 | self.timeEdit.setEnabled(False) 46 | self.timeEdit.setGeometry(QtCore.QRect(530, 60, 118, 27)) 47 | self.timeEdit.setObjectName("timeEdit") 48 | self.label_2 = QtWidgets.QLabel(self.centralwidget) 49 | self.label_2.setGeometry(QtCore.QRect(40, 60, 291, 311)) 50 | self.label_2.setContextMenuPolicy(QtCore.Qt.DefaultContextMenu) 51 | self.label_2.setText("") 52 | self.label_2.setObjectName("label_2") 53 | self.label_2.setScaledContents(True) 54 | self.label_2.setPixmap(QtGui.QPixmap(os.path.join(IMG_PATH, "black.jpg"))) 55 | MainWindow.setCentralWidget(self.centralwidget) 56 | 57 | 58 | self.retranslateUi(MainWindow) 59 | QtCore.QMetaObject.connectSlotsByName(MainWindow) 60 | 61 | MainWindow.show() 62 | 63 | self.image = None 64 | def retranslateUi(self, MainWindow): 65 | _translate = QtCore.QCoreApplication.translate 66 | MainWindow.setWindowTitle(_translate("MainWindow", "人脸识别智能考勤")) 67 | self.label.setText(_translate("MainWindow", "欢迎使用")) 68 | 69 | 70 | 71 | -------------------------------------------------------------------------------- /ui/frame.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/reece15/cnn_face_detection/d4274440050ae31f345eaa298ab2477b77c16cae/ui/frame.pyc -------------------------------------------------------------------------------- /ui/frame.ui: -------------------------------------------------------------------------------- 1 | 2 | 3 | MainWindow 4 | 5 | 6 | false 7 | 8 | 9 | 10 | 0 11 | 0 12 | 835 13 | 517 14 | 15 | 16 | 17 | 人脸识别智能考勤 18 | 19 | 20 | 21 | 22 | false 23 | 24 | 25 | 26 | 50 27 | 400 28 | 721 29 | 51 30 | 31 | 32 | 33 | 34 | TlwgTypewriter 35 | 24 36 | 50 37 | false 38 | false 39 | false 40 | true 41 | 42 | 43 | 44 | 45 | 46 | 47 | Qt::LeftToRight 48 | 49 | 50 | 欢迎使用 51 | 52 | 53 | Qt::AlignCenter 54 | 55 | 56 | 57 | 58 | false 59 | 60 | 61 | 62 | 350 63 | 130 64 | 451 65 | 201 66 | 67 | 68 | 69 | false 70 | 71 | 72 | false 73 | 74 | 75 | 76 | 77 | false 78 | 79 | 80 | 81 | 530 82 | 60 83 | 118 84 | 27 85 | 86 | 87 | 88 | 89 | 90 | 91 | 40 92 | 60 93 | 291 94 | 311 95 | 96 | 97 | 98 | false 99 | 100 | 101 | Qt::DefaultContextMenu 102 | 103 | 104 | 105 | 106 | 107 | 108 | 109 | 110 | toolBar 111 | 112 | 113 | TopToolBarArea 114 | 115 | 116 | false 117 | 118 | 119 | 120 | 121 | toolBar_2 122 | 123 | 124 | TopToolBarArea 125 | 126 | 127 | false 128 | 129 | 130 | 131 | 132 | 登陆 133 | 134 | 135 | 136 | 137 | 设置 138 | 139 | 140 | 141 | 142 | 考勤 143 | 144 | 145 | 146 | 147 | 148 | 149 | -------------------------------------------------------------------------------- /ui/launcher.py: -------------------------------------------------------------------------------- 1 | # coding:utf-8 2 | 3 | from PyQt5.QtCore import * 4 | from PyQt5.QtWidgets import * 5 | from PyQt5.QtGui import * 6 | from frame import Ui_MainWindow 7 | import time 8 | import sys 9 | from driver.cam import cams 10 | import cv2 11 | from driver.face_search import search_one, load_feat, feats, images, net 12 | import traceback 13 | import config 14 | 15 | 16 | class MainWindow(QMainWindow, Ui_MainWindow): 17 | def __init__(self, parent=None): 18 | super(MainWindow, self).__init__(parent=parent) 19 | self.setupUi(self) 20 | # 定时器 21 | self.timer = QTimer() 22 | 23 | self.timer.setInterval(100) 24 | self.timer.timeout.connect(self.flush_image) 25 | self.timer.start() 26 | 27 | # 时间刷新 28 | self.timer_time = QTimer() 29 | 30 | self.timer_time.setInterval(60000) #60000 31 | self.timer_time.timeout.connect(self.flush_time) 32 | self.timer_time.start() 33 | self.flush_time() 34 | self.cnt_timer = 5 # 延时刷新 35 | 36 | def flush_image(self): 37 | print "timer running!" 38 | photo, face = cams.get_photo() 39 | if photo is not None: 40 | if face is not None: 41 | x, y, h, w = face 42 | 43 | gray = cv2.cvtColor(photo, cv2.COLOR_BGR2GRAY) 44 | roi = gray[y:y + h, x:x + w] 45 | faces = cv2.resize(roi, (128, 128), interpolation=cv2.INTER_CUBIC) 46 | try: 47 | max_s, index, name = search_one(load_feat(faces, net), feats, images) 48 | print "max_s:{max_s}|index:{index}|name:{name}".format(**vars()) 49 | except: 50 | print traceback.format_exc() 51 | else: 52 | uname = "no name!" 53 | if max_s > config.TH: 54 | uname = name 55 | 56 | self.cnt_timer = 5 57 | self.label.setText("欢迎您, {uname}".format(uname=uname)) 58 | photo = cams.draw_text(photo, face_rects=face, text=u"welcome {} p:{:.2f}".format(unicode(uname, "utf-8"), max_s)) 59 | else: 60 | 61 | self.cnt_timer -= 1 62 | 63 | if self.cnt_timer <= 0: 64 | self.label.setText("欢迎使用") 65 | photo = cams.draw_text(photo, face_rects=face, text=u"Sorry {name}".format(name=uname)) 66 | else: 67 | self.cnt_timer -= 1 68 | 69 | if self.cnt_timer == 0: 70 | self.label.setText("欢迎使用") 71 | 72 | height, width, bytesPerComponent = photo.shape 73 | bytesPerLine = bytesPerComponent * width 74 | cv2.cvtColor(photo, cv2.COLOR_BGR2RGB, photo) 75 | image = QImage(photo.data, width, height, bytesPerLine, QImage.Format_RGB888) 76 | self.image = image 77 | self.label_2.setPixmap(QPixmap.fromImage(image).scaled(self.label_2.width(), self.label_2.height())) 78 | cv2.waitKey(1) 79 | 80 | else: 81 | print "err" 82 | 83 | def flush_time(self): 84 | now_day = time.strftime("%Y-%m-%d", time.localtime()) 85 | self.calendarWidget.setSelectedDate(QDate.fromString(now_day, 'yyyy-MM-dd')) 86 | self.timeEdit.setTime(QTime.currentTime()) 87 | 88 | 89 | if __name__ == "__main__": 90 | app = QApplication(sys.argv) 91 | w = MainWindow() 92 | w.show() 93 | sys.exit(app.exec_()) 94 | 95 | -------------------------------------------------------------------------------- /ui/launcher_sing_face.py: -------------------------------------------------------------------------------- 1 | # coding:utf-8 2 | 3 | from PyQt5.QtCore import * 4 | from PyQt5.QtWidgets import * 5 | from PyQt5.QtGui import * 6 | from sign_face import Ui_SignFaceWindow 7 | from save_face import Ui_Dialog 8 | import time 9 | import sys 10 | from driver.cam import cams 11 | import cv2 12 | import config 13 | import os 14 | 15 | 16 | class MainWindow(QMainWindow, Ui_SignFaceWindow): 17 | def __init__(self, parent=None): 18 | super(MainWindow, self).__init__(parent=parent) 19 | self.setupUi(self) 20 | # 定时器 21 | self.timer = QTimer() 22 | 23 | self.timer.setInterval(100) 24 | self.timer.timeout.connect(self.flush_image) 25 | self.timer.start() 26 | self.face = None 27 | 28 | def flush_image(self): 29 | photo, face = cams.get_photo() 30 | if photo is not None: 31 | if face is not None: 32 | x, y, h, w = face 33 | roi = photo[y:y + h, x:x + w] 34 | img = cv2.cvtColor(roi, cv2.COLOR_BGR2RGB) 35 | self.face = img 36 | 37 | photo = cams.draw_text(photo, face_rects=face, text=u"scaning") 38 | height, width, bytesPerComponent = photo.shape 39 | bytesPerLine = bytesPerComponent * width 40 | cv2.cvtColor(photo, cv2.COLOR_BGR2RGB, photo) 41 | image = QImage(photo.data, width, height, bytesPerLine, QImage.Format_RGB888) 42 | 43 | self.cam_label.setPixmap(QPixmap.fromImage(image).scaled(self.cam_label.width(), self.cam_label.height())) 44 | cv2.waitKey(1) 45 | else: 46 | print "err" 47 | 48 | def show_save_diglog(self): 49 | if self.face is not None: 50 | save_dialog = SaveDialog(self) 51 | save_dialog.show() 52 | 53 | 54 | class SaveDialog(QDialog, Ui_Dialog): 55 | def __init__(self, parent=None): 56 | super(SaveDialog, self).__init__(parent=parent) 57 | self.setupUi(self) 58 | 59 | self.cancel_btn.clicked.connect(self.close) 60 | self.save_btn.clicked.connect(self.save) 61 | 62 | photo = parent.face 63 | self.photo = photo 64 | height, width, bytesPerComponent = photo.shape 65 | bytesPerLine = bytesPerComponent * width 66 | 67 | with open(os.path.join(config.BUFFER_DIR, "buffer"), "wb") as f: 68 | photo.tofile(f) 69 | 70 | with open(os.path.join(config.BUFFER_DIR, "buffer"), "rb") as f: 71 | image = QImage(f.read(), width, height, bytesPerLine, QImage.Format_RGB888) 72 | 73 | self.face_label.setPixmap(QPixmap.fromImage(image).scaled(self.face_label.width(), self.face_label.height())) 74 | self.image = image 75 | 76 | def save(self): 77 | timer = QTimer(self) 78 | timer.setSingleShot(True) 79 | timer.timeout.connect(self.save_image) 80 | timer.start() 81 | 82 | def save_image(self): 83 | t = self.name_input.text() 84 | if len(t) >= 2: 85 | self.image.save(os.path.join(config.DATA_PATH, t + ".jpg"), "jpg", 100) 86 | button = QMessageBox.warning( 87 | self, 88 | u"提示", 89 | u"录入成功", 90 | QMessageBox.Close 91 | ) 92 | self.close() 93 | 94 | else: 95 | QMessageBox.warning( 96 | self, 97 | u"错误", 98 | u"姓名长度必须大于1！", 99 | QMessageBox.Yes 100 | ) 101 | 102 | 103 | if __name__ == "__main__": 104 | app = QApplication(sys.argv) 105 | w = MainWindow() 106 | w.show() 107 | sys.exit(app.exec_()) -------------------------------------------------------------------------------- /ui/save_face.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | 3 | # Form implementation generated from reading ui file 'save_face.ui' 4 | # 5 | # Created by: PyQt5 UI code generator 5.10.1 6 | # 7 | # WARNING! All changes made in this file will be lost! 8 | 9 | from PyQt5 import QtCore, QtGui, QtWidgets 10 | 11 | class Ui_Dialog(object): 12 | def setupUi(self, Dialog): 13 | Dialog.setObjectName("Dialog") 14 | Dialog.resize(368, 546) 15 | self.face_label = QtWidgets.QLabel(Dialog) 16 | self.face_label.setGeometry(QtCore.QRect(70, 70, 231, 241)) 17 | self.face_label.setText("") 18 | self.face_label.setObjectName("face_label") 19 | self.save_btn = QtWidgets.QPushButton(Dialog) 20 | self.save_btn.setGeometry(QtCore.QRect(80, 470, 99, 27)) 21 | self.save_btn.setObjectName("save_btn") 22 | self.cancel_btn = QtWidgets.QPushButton(Dialog) 23 | self.cancel_btn.setGeometry(QtCore.QRect(200, 470, 99, 27)) 24 | self.cancel_btn.setObjectName("cancel_btn") 25 | 26 | self.name_input = QtWidgets.QLineEdit(Dialog) 27 | self.name_input.setGeometry(QtCore.QRect(180, 360, 113, 27)) 28 | self.name_input.setObjectName("name_input") 29 | self.label = QtWidgets.QLabel(Dialog) 30 | self.label.setGeometry(QtCore.QRect(70, 360, 71, 31)) 31 | self.label.setObjectName("label") 32 | 33 | self.retranslateUi(Dialog) 34 | QtCore.QMetaObject.connectSlotsByName(Dialog) 35 | 36 | def retranslateUi(self, Dialog): 37 | _translate = QtCore.QCoreApplication.translate 38 | Dialog.setWindowTitle(_translate("Dialog", "录入")) 39 | self.save_btn.setText(_translate("Dialog", "录入")) 40 | self.cancel_btn.setText(_translate("Dialog", "取消")) 41 | self.name_input.setPlaceholderText(_translate("Dialog", "请输入姓名")) 42 | self.label.setText(_translate("Dialog", " 姓名")) 43 | 44 | -------------------------------------------------------------------------------- /ui/save_face.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/reece15/cnn_face_detection/d4274440050ae31f345eaa298ab2477b77c16cae/ui/save_face.pyc -------------------------------------------------------------------------------- /ui/save_face.ui: -------------------------------------------------------------------------------- 1 | 2 | 3 | Dialog 4 | 5 | 6 | 7 | 0 8 | 0 9 | 368 10 | 546 11 | 12 | 13 | 14 | 录入 15 | 16 | 17 | 18 | 19 | 70 20 | 70 21 | 231 22 | 241 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 | 80 33 | 470 34 | 99 35 | 27 36 | 37 | 38 | 39 | 录入 40 | 41 | 42 | 43 | 44 | 45 | 200 46 | 470 47 | 99 48 | 27 49 | 50 | 51 | 52 | 取消 53 | 54 | 55 | 56 | 57 | 58 | 180 59 | 360 60 | 113 61 | 27 62 | 63 | 64 | 65 | 请输入姓名 66 | 67 | 68 | 69 | 70 | 71 | 70 72 | 360 73 | 71 74 | 31 75 | 76 | 77 | 78 | 姓名 79 | 80 | 81 | 82 | 83 | 84 | 85 | -------------------------------------------------------------------------------- /ui/sign_face.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | 3 | # Form implementation generated from reading ui file 'sign_face.ui' 4 | # 5 | # Created by: PyQt5 UI code generator 5.10.1 6 | # 7 | # WARNING! All changes made in this file will be lost! 8 | 9 | from PyQt5 import QtCore, QtGui, QtWidgets 10 | import time 11 | 12 | class Ui_SignFaceWindow(object): 13 | def setupUi(self, SignFaceWindow): 14 | self.catching = False 15 | SignFaceWindow.setObjectName("SignFaceWindow") 16 | SignFaceWindow.resize(800, 600) 17 | self.centralwidget = QtWidgets.QWidget(SignFaceWindow) 18 | self.centralwidget.setObjectName("centralwidget") 19 | self.cam_label = QtWidgets.QLabel(self.centralwidget) 20 | self.cam_label.setGeometry(QtCore.QRect(250, 110, 231, 271)) 21 | self.cam_label.setText("") 22 | self.cam_label.setObjectName("cam_label") 23 | self.catch_btn = QtWidgets.QPushButton(self.centralwidget) 24 | self.catch_btn.setGeometry(QtCore.QRect(320, 470, 99, 27)) 25 | self.catch_btn.setObjectName("catch_btn") 26 | self.catch_btn.clicked.connect(self.catch_clicked) 27 | 28 | 29 | # self.sleep_box = QtWidgets.QSpinBox(self.centralwidget) 30 | # self.sleep_box.setGeometry(QtCore.QRect(290, 470, 48, 27)) 31 | # self.sleep_box.setProperty("value", 5) 32 | # self.sleep_box.setObjectName("sleep_box") 33 | # self.label_2 = QtWidgets.QLabel(self.centralwidget) 34 | # self.label_2.setGeometry(QtCore.QRect(220, 470, 67, 31)) 35 | # self.label_2.setObjectName("label_2") 36 | # self.label_3 = QtWidgets.QLabel(self.centralwidget) 37 | # self.label_3.setGeometry(QtCore.QRect(350, 470, 67, 31)) 38 | # self.label_3.setObjectName("label_3") 39 | SignFaceWindow.setCentralWidget(self.centralwidget) 40 | self.statusbar = QtWidgets.QStatusBar(SignFaceWindow) 41 | self.statusbar.setObjectName("statusbar") 42 | SignFaceWindow.setStatusBar(self.statusbar) 43 | 44 | self.retranslateUi(SignFaceWindow) 45 | QtCore.QMetaObject.connectSlotsByName(SignFaceWindow) 46 | 47 | def retranslateUi(self, SignFaceWindow): 48 | _translate = QtCore.QCoreApplication.translate 49 | SignFaceWindow.setWindowTitle(_translate("SignFaceWindow", "人脸数据录入")) 50 | self.catch_btn.setText(_translate("SignFaceWindow", "抓取")) 51 | #self.label_2.setText(_translate("SignFaceWindow", "延时")) 52 | #self.label_3.setText(_translate("SignFaceWindow", "秒")) 53 | 54 | def catch_clicked(self): 55 | #val = self.sleep_box.value() 56 | save_timer = QtCore.QTimer(self) 57 | save_timer.setSingleShot(True) 58 | save_timer.timeout.connect(self.save_dialog) 59 | save_timer.start() 60 | 61 | def save_dialog(self): 62 | self.show_save_diglog() 63 | self.face = None 64 | self.catching = False 65 | 66 | 67 | def show_save_diglog(self): 68 | pass -------------------------------------------------------------------------------- /ui/sign_face.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/reece15/cnn_face_detection/d4274440050ae31f345eaa298ab2477b77c16cae/ui/sign_face.pyc -------------------------------------------------------------------------------- /ui/sign_face.ui: -------------------------------------------------------------------------------- 1 | 2 | 3 | SignFaceWindow 4 | 5 | 6 | 7 | 0 8 | 0 9 | 800 10 | 600 11 | 12 | 13 | 14 | 人脸数据录入 15 | 16 | 17 | 18 | 19 | 20 | 250 21 | 110 22 | 231 23 | 271 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 | 33 | 420 34 | 470 35 | 99 36 | 27 37 | 38 | 39 | 40 | 抓取 41 | 42 | 43 | 44 | 45 | 46 | 290 47 | 470 48 | 48 49 | 27 50 | 51 | 52 | 53 | 5 54 | 55 | 56 | 57 | 58 | 59 | 220 60 | 470 61 | 67 62 | 31 63 | 64 | 65 | 66 | 延时 67 | 68 | 69 | 70 | 71 | 72 | 350 73 | 470 74 | 67 75 | 31 76 | 77 | 78 | 79 | 秒 80 | 81 | 82 | 83 | 84 | 85 | 86 | 87 | 88 | --------------------------------------------------------------------------------