54 lines
1.9 KiB
Python
54 lines
1.9 KiB
Python
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from deepface.detectors import FaceDetector
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# Link - https://google.github.io/mediapipe/solutions/face_detection
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def build_model():
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import mediapipe as mp # this is not a must dependency. do not import it in the global level.
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mp_face_detection = mp.solutions.face_detection
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face_detection = mp_face_detection.FaceDetection(min_detection_confidence=0.7)
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return face_detection
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def detect_face(face_detector, img, align=True):
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resp = []
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img_width = img.shape[1]
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img_height = img.shape[0]
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results = face_detector.process(img)
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if results.detections:
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for detection in results.detections:
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(confidence,) = detection.score
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bounding_box = detection.location_data.relative_bounding_box
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landmarks = detection.location_data.relative_keypoints
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x = int(bounding_box.xmin * img_width)
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w = int(bounding_box.width * img_width)
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y = int(bounding_box.ymin * img_height)
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h = int(bounding_box.height * img_height)
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right_eye = (int(landmarks[0].x * img_width), int(landmarks[0].y * img_height))
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left_eye = (int(landmarks[1].x * img_width), int(landmarks[1].y * img_height))
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# nose = (int(landmarks[2].x * img_width), int(landmarks[2].y * img_height))
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# mouth = (int(landmarks[3].x * img_width), int(landmarks[3].y * img_height))
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# right_ear = (int(landmarks[4].x * img_width), int(landmarks[4].y * img_height))
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# left_ear = (int(landmarks[5].x * img_width), int(landmarks[5].y * img_height))
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if x > 0 and y > 0:
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detected_face = img[y : y + h, x : x + w]
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img_region = [x, y, w, h]
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if align:
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detected_face = FaceDetector.alignment_procedure(
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detected_face, left_eye, right_eye
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)
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resp.append((detected_face, img_region, confidence))
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return resp
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