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https://github.com/open-mmlab/mmdeploy.git
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ea73f20fe4
* rename mmdeploy_python -> mmdeploy_runtime * remove incompatible build config * Revert "remove incompatible build config" This reverts commit cdc780cde52c0417e6a5408001fb5ddef1a9498d. * fix builder * update package_tools docs * fix linux set_env script * fix gcc 7.3 aligned_alloc * fix link * comment temporarily as text_det_recog can't be built with prebuild package built under manylinux
68 lines
1.9 KiB
Python
68 lines
1.9 KiB
Python
# Copyright (c) OpenMMLab. All rights reserved.
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import argparse
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import json
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import cv2
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from mmdeploy_runtime import Context, Device, Model, Pipeline
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def parse_args():
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parser = argparse.ArgumentParser(
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description='Demo of MMDeploy SDK pipeline API')
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parser.add_argument('device', help='name of device, cuda or cpu')
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parser.add_argument('det_model_path', help='path of detection model')
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parser.add_argument('cls_model_path', help='path of classification model')
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parser.add_argument('image_path', help='path to test 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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det_model = Model(args.det_model_path)
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reg_model = Model(args.cls_model_path)
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config = dict(
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type='Pipeline',
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input='img',
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tasks=[
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dict(
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type='Inference',
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input='img',
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output='dets',
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params=dict(model=det_model)),
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dict(
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type='Pipeline',
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# flatten dets ([[a]] -> [a]) and broadcast img
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input=['boxes=*dets', 'imgs=+img'],
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tasks=[
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dict(
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type='Task',
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module='CropBox',
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input=['imgs', 'boxes'],
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output='patches'),
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dict(
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type='Inference',
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input='patches',
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output='labels',
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params=dict(model=reg_model))
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],
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# unflatten labels ([a] -> [[a]])
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output='*labels')
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],
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output=['dets', 'labels'])
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device = Device(args.device)
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pipeline = Pipeline(config, Context(device))
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img = cv2.imread(args.image_path)
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output = pipeline(dict(ori_img=img))
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print(json.dumps(output, indent=4))
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if __name__ == '__main__':
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main()
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