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* Support PETR v2 * make petrv2 precision equal with the origin repo * delete extra func * modify review problem * delete visualize * Update README_CN.md * Update README.md * Update README_CN.md * fix build problem * delete external variable and function --------- Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>
46 lines
1.2 KiB
Python
Executable File
46 lines
1.2 KiB
Python
Executable File
import fastdeploy as fd
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import cv2
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import os
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from fastdeploy import ModelFormat
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def parse_arguments():
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import argparse
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import ast
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parser = argparse.ArgumentParser()
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parser.add_argument(
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"--model", required=True, help="Path of petr paddle model.")
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parser.add_argument(
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"--image", required=True, help="Path of test image file.")
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parser.add_argument(
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"--device",
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type=str,
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default='cpu',
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help="Type of inference device, support 'cpu' or 'gpu'.")
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return parser.parse_args()
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def build_option(args):
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option = fd.RuntimeOption()
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if args.device.lower() == "gpu":
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option.use_gpu(0)
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if args.device.lower() == "cpu":
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option.use_cpu()
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return option
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args = parse_arguments()
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model_file = os.path.join(args.model, "petrv2_inference.pdmodel")
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params_file = os.path.join(args.model, "petrv2_inference.pdiparams")
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config_file = os.path.join(args.model, "infer_cfg.yml")
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# 配置runtime,加载模型
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runtime_option = build_option(args)
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model = fd.vision.perception.Petr(
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model_file, params_file, config_file, runtime_option=runtime_option)
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# 预测图片检测结果
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im = cv2.imread(args.image)
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result = model.predict(im)
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print(result)
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