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DNN-based Face Detection And Recognition | OpenCV Tutorials
cv::FaceDetectorYN Class Reference | OpenCV Online Documentation
2023/06/27 OpenCV DNN based Face Detection API/Model will update to YuNet v2 from OpenCV 4.8.0. If you want more detail, Please refer to Pull Request.
| import os | |
| import numpy as np | |
| import cv2 | |
| def main(): | |
| # キャプチャを開く | |
| directory = os.path.dirname(__file__) | |
| #capture = cv2.VideoCapture(os.path.join(directory, "image.jpg")) # 画像ファイル | |
| capture = cv2.VideoCapture(0) # カメラ | |
| if not capture.isOpened(): | |
| exit() | |
| # モデルを読み込む | |
| weights = os.path.join(directory, "yunet.onnx") | |
| face_detector = cv2.FaceDetectorYN_create(weights, "", (0, 0)) | |
| while True: | |
| # フレームをキャプチャして画像を読み込む | |
| result, image = capture.read() | |
| if result is False: | |
| cv2.waitKey(0) | |
| break | |
| # 画像が3チャンネル以外の場合は3チャンネルに変換する | |
| channels = 1 if len(image.shape) == 2 else image.shape[2] | |
| if channels == 1: | |
| image = cv2.cvtColor(image, cv2.COLOR_GRAY2BGR) | |
| if channels == 4: | |
| image = cv2.cvtColor(image, cv2.COLOR_BGRA2BGR) | |
| # 入力サイズを指定する | |
| height, width, _ = image.shape | |
| face_detector.setInputSize((width, height)) | |
| # 顔を検出する | |
| _, faces = face_detector.detect(image) | |
| faces = faces if faces is not None else [] | |
| # 検出した顔のバウンディングボックスとランドマークを描画する | |
| for face in faces: | |
| # バウンディングボックス | |
| box = list(map(int, face[:4])) | |
| color = (0, 0, 255) | |
| thickness = 2 | |
| cv2.rectangle(image, box, color, thickness, cv.LINE_AA) | |
| # ランドマーク（右目、左目、鼻、右口角、左口角） | |
| landmarks = list(map(int, face[4:len(face)-1])) | |
| landmarks = np.array_split(landmarks, len(landmarks) / 2) | |
| for landmark in landmarks: | |
| radius = 5 | |
| thickness = -1 | |
| cv2.circle(image, landmark, radius, color, thickness, cv2.LINE_AA) | |
| # 信頼度 | |
| confidence = face[-1] | |
| confidence = "{:.2f}".format(confidence) | |
| position = (box[0], box[1] - 10) | |
| font = cv2.FONT_HERSHEY_SIMPLEX | |
| scale = 0.5 | |
| thickness = 2 | |
| cv2.putText(image, confidence, position, font, scale, color, thickness, cv2.LINE_AA) | |
| # 画像を表示する | |
| cv2.imshow("face detection", image) | |
| key = cv2.waitKey(10) | |
| if key == ord('q'): | |
| break | |
| cv2.destroyAllWindows() | |
| if __name__ == '__main__': | |
| main() |
Hi @UnaNancyOwen. First of all, Great work!
The link to download the model (yunet.onnx) does not seem to be working now for some reason. Can you kindly look into it?
Thanks!
@ayanatherate There is a model at https://github.com/opencv/opencv_zoo/tree/master/models/face_detection_yunet.
i.e face_detection_yunet_2022mar.onnx
There is a model at https://github.com/opencv/opencv_zoo/tree/master/models/face_detection_yunet.
i.e face_detection_yunet_2022mar.onnx
This model is NOT compatible with your sample project.
That is an updated model that has bugs listed in
ShiqiYu/libfacedetection#294
But if you can get your project working with the new ONNX model let me know.
As far as I know it just doesn't work correctly.
Works perfectly, just had to change the source onnx file (sort of like a .xml cascade file) to exclude the path, (currently using "face_detection_yunet_2022mar.onnx")
. Also had to add a "2" after a "cv" and before "LINE_AA"
TIme to pick at it and see if I can add so me little if statements in there to control things
The only source online!
As said by @JamesAkers2022 those two are the only problems!
Thanks a lot!
Can someone link to the fixed file here for submit a pull request ?
45行目のLINE_AAの指定がcv2ではなく、cvとなっています。
x cv2.rectangle(image, box, color, thickness, cv.LINE_AA)
o cv2.rectangle(image, box, color, thickness, cv2.LINE_AA)