Witrynaorgimg = cv2.imread(image_path) # BGR: img0 = copy.deepcopy(orgimg) assert orgimg is not None, 'Image Not Found ' + image_path: h0, w0 = orgimg.shape[:2] # orig hw: r = img_size / max(h0, w0) # resize image to img_size: if r != 1: # always resize down, only resize up if training with augmentation: interp = cv2.INTER_AREA if r < 1 else … Witrynaorgimg = cv2. imread (image_path) # BGR: img0 = copy. deepcopy (orgimg) assert orgimg is not None, 'Image Not Found ' + image_path: h0, w0 = orgimg. shape [: 2] # orig hw: r = img_size / max (h0, w0) # resize image to img_size: if r!= 1: # always resize down, only resize up if training with augmentation: interp = cv2. INTER_AREA if r < 1 …
yolov5-face/detect_face.py at master · deepcam-cn/yolov5-face
Witrynaorgimg = cv2. imread (image_path) # BGR: img0 = copy. deepcopy (orgimg) assert orgimg is not None, 'Image Not Found ' + image_path: h0, w0 = orgimg. shape [: 2] # orig hw: r = img_size / max (h0, w0) # resize image to img_size: if r!= 1: # always resize down, only resize up if training with augmentation: interp = cv2. INTER_AREA if r < 1 … WitrynaContribute to TaoTaoBuTao/YOLOv5_LPRNet_flask development by creating an account on GitHub. black charcoal hair
yolov5-face-annotation/detect_face.py at master · …
Witrynaorgimg = show_results(orgimg, xywh, conf, landmarks, class_num) cv2.imwrite(cur_path+'/result.jpg', orgimg) print('result save in '+cur_path+'/result.jpg') if __name__ == '__main__': parser = argparse.ArgumentParser() parser.add_argument('--img_path', type=str, default=cur_path+"/sample.jpg", help='img path') WitrynaThe region score localizes individual characters in the image, and the affinity score groups each character into a single instance. The character-level region awareness mechanism helps in detecting texts of various shapes such as long, curved, and arbitrarily shaped texts. Getting Started Witrynaorgimg = cv2.imread(opt.image) # BGR: img0 = copy.deepcopy(orgimg) assert orgimg is not None, 'Image Not Found ' + opt.image: h0, w0 = orgimg.shape[:2] # orig hw: r = img_size / max(h0, w0) # resize image to img_size: if r != 1: # always resize down, only resize up if training with augmentation: interp = cv2.INTER_AREA if r < 1 else … black charcoal for teeth