59 lines
1.7 KiB
Python
59 lines
1.7 KiB
Python
# Copyright (c) OpenMMLab. All rights reserved.
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from argparse import ArgumentParser
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from io import BytesIO
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import matplotlib.pyplot as plt
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import mmcv
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import requests
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from mmseg.apis import inference_model, init_model
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def parse_args():
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parser = ArgumentParser(
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description='Compare result of torchserve and pytorch,'
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'and visualize them.')
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parser.add_argument('img', help='Image file')
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parser.add_argument('config', help='Config file')
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parser.add_argument('checkpoint', help='Checkpoint file')
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parser.add_argument('model_name', help='The model name in the server')
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parser.add_argument(
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'--inference-addr',
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default='127.0.0.1:8080',
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help='Address and port of the inference server')
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parser.add_argument(
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'--result-image',
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type=str,
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default=None,
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help='save server output in result-image')
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parser.add_argument(
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'--device', default='cuda:0', help='Device used for inference')
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args = parser.parse_args()
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return args
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def main(args):
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url = 'http://' + args.inference_addr + '/predictions/' + args.model_name
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with open(args.img, 'rb') as image:
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tmp_res = requests.post(url, image)
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content = tmp_res.content
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if args.result_image:
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with open(args.result_image, 'wb') as out_image:
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out_image.write(content)
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plt.imshow(mmcv.imread(args.result_image, 'grayscale'))
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plt.show()
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else:
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plt.imshow(plt.imread(BytesIO(content)))
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plt.show()
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model = init_model(args.config, args.checkpoint, args.device)
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image = mmcv.imread(args.img)
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result = inference_model(model, image)
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plt.imshow(result[0])
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plt.show()
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if __name__ == '__main__':
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args = parse_args()
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main(args)
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