48 lines
1.4 KiB
Python
48 lines
1.4 KiB
Python
# Copyright (c) OpenMMLab. All rights reserved.
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import argparse
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import cv2
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from mmdeploy_python import Detector
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def parse_args():
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parser = argparse.ArgumentParser(
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description='show how to use sdk python api')
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parser.add_argument('device_name', help='name of device, cuda or cpu')
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parser.add_argument(
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'model_path',
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help='path of mmdeploy SDK model dumped by model converter')
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parser.add_argument('image_path', help='path of an image')
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args = parser.parse_args()
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return args
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def main():
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args = parse_args()
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img = cv2.imread(args.image_path)
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detector = Detector(
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model_path=args.model_path, device_name=args.device_name, device_id=0)
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bboxes, labels, masks = detector(img)
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indices = [i for i in range(len(bboxes))]
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for index, bbox, label_id in zip(indices, bboxes, labels):
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[left, top, right, bottom], score = bbox[0:4].astype(int), bbox[4]
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if score < 0.3:
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continue
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cv2.rectangle(img, (left, top), (right, bottom), (0, 255, 0))
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if masks[index].size:
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mask = masks[index]
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blue, green, red = cv2.split(img)
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mask_img = blue[top:top + mask.shape[0], left:left + mask.shape[1]]
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cv2.bitwise_or(mask, mask_img, mask_img)
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img = cv2.merge([blue, green, red])
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cv2.imwrite('output_detection.png', img)
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if __name__ == '__main__':
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main()
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