Created
July 24, 2020 09:53
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| import numpy as np | |
| import cv2 | |
| from sklearn.externals import joblib | |
| def calc_hist(img): | |
| histogram = [0] * 3 | |
| for j in range(3): | |
| histr = cv2.calcHist([img], [j], None, [256], [0, 256]) | |
| histr *= 255.0 / histr.max() | |
| histogram[j] = histr | |
| return np.array(histogram) | |
| modelFile = "models/res10_300x300_ssd_iter_140000.caffemodel" | |
| configFile = "models/deploy.prototxt" | |
| net = cv2.dnn.readNetFromCaffe(configFile, modelFile) | |
| clf = joblib.load('models/face_spoofing.pkl') | |
| cap = cv2.VideoCapture(0) | |
| # width = 320 | |
| # height = 240 | |
| # cap.set(cv2.CAP_PROP_FRAME_HEIGHT, height) | |
| # cap.set(cv2.CAP_PROP_FRAME_WIDTH, width) | |
| sample_number = 1 | |
| count = 0 | |
| measures = np.zeros(sample_number, dtype=np.float) | |
| while True: | |
| ret, img = cap.read() | |
| blob = cv2.dnn.blobFromImage(cv2.resize(img, (300, 300)), 1.0,(300, 300), (104.0, 177.0, 123.0)) | |
| net.setInput(blob) | |
| faces3 = net.forward() | |
| measures[count%sample_number]=0 | |
| height, width = img.shape[:2] | |
| for i in range(faces3.shape[2]): | |
| confidence = faces3[0, 0, i, 2] | |
| if confidence > 0.5: | |
| box = faces3[0, 0, i, 3:7] * np.array([width, height, width, height]) | |
| (x, y, x1, y1) = box.astype("int") | |
| # cv2.rectangle(img, (x, y), (x1, y1), (0, 0, 255), 5) | |
| roi = img[y:y1, x:x1] | |
| point = (0,0) | |
| img_ycrcb = cv2.cvtColor(roi, cv2.COLOR_BGR2YCR_CB) | |
| img_luv = cv2.cvtColor(roi, cv2.COLOR_BGR2LUV) | |
| ycrcb_hist = calc_hist(img_ycrcb) | |
| luv_hist = calc_hist(img_luv) | |
| feature_vector = np.append(ycrcb_hist.ravel(), luv_hist.ravel()) | |
| feature_vector = feature_vector.reshape(1, len(feature_vector)) | |
| prediction = clf.predict_proba(feature_vector) | |
| prob = prediction[0][1] | |
| measures[count % sample_number] = prob | |
| cv2.rectangle(img, (x, y), (x1, y1), (255, 0, 0), 2) | |
| point = (x, y-5) | |
| print (measures, np.mean(measures)) | |
| if 0 not in measures: | |
| text = "True" | |
| if np.mean(measures) >= 0.7: | |
| text = "False" | |
| font = cv2.FONT_HERSHEY_SIMPLEX | |
| cv2.putText(img=img, text=text, org=point, fontFace=font, fontScale=0.9, color=(0, 0, 255), | |
| thickness=2, lineType=cv2.LINE_AA) | |
| else: | |
| font = cv2.FONT_HERSHEY_SIMPLEX | |
| cv2.putText(img=img, text=text, org=point, fontFace=font, fontScale=0.9, | |
| color=(0, 255, 0), thickness=2, lineType=cv2.LINE_AA) | |
| count+=1 | |
| cv2.imshow('img_rgb', img) | |
| key = cv2.waitKey(1) | |
| if key & 0xFF == 27: | |
| break | |
| cap.release() | |
| cv2.destroyAllWindows() |
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where this file is located models/face_spoofing.pkl. can you please share the details