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	23dfcac891
	
	
	
		
			
			* 更新ppdet * 更新ppdet * 更新ppdet * 更新ppdet * 更新ppdet * 新增ppdet_decode * 更新多batch支持 * 更新多batch支持 * 更新多batch支持 * 更新注释内容 * 尝试解决pybind问题 * 尝试解决pybind的问题 * 尝试解决pybind的问题 * 重构代码 * 重构代码 * 重构代码 * 按照要求修改 * 修复部分bug 加入pybind * 修复pybind * 修复pybind错误的问题
		
			
				
	
	
		
			68 lines
		
	
	
		
			2.0 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			68 lines
		
	
	
		
			2.0 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
| # Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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| #
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| # Licensed under the Apache License, Version 2.0 (the "License");
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| # you may not use this file except in compliance with the License.
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| # You may obtain a copy of the License at
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| #
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| #     http://www.apache.org/licenses/LICENSE-2.0
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| #
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| # Unless required by applicable law or agreed to in writing, software
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| # distributed under the License is distributed on an "AS IS" BASIS,
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| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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| # See the License for the specific language governing permissions and
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| # limitations under the License.
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| import fastdeploy as fd
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| import cv2
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| import os
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| 
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| 
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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_file",
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|         default="./picodet_s_416_coco_lcnet_non_postprocess/picodet_xs_416_coco_lcnet.onnx",
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|         help="Path of rknn model.")
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|     parser.add_argument(
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|         "--config_file",
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|         default="./picodet_s_416_coco_lcnet_non_postprocess/infer_cfg.yml",
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|         help="Path of config.")
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|     parser.add_argument(
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|         "--image",
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|         type=str,
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|         default="./000000014439.jpg",
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|         help="Path of test image file.")
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|     return parser.parse_args()
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| 
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| 
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| if __name__ == "__main__":
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|     args = parse_arguments()
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| 
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|     model_file = args.model_file
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|     params_file = ""
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|     config_file = args.config_file
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| 
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|     # 配置runtime,加载模型
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|     runtime_option = fd.RuntimeOption()
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|     runtime_option.use_cpu()
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| 
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|     model = fd.vision.detection.PPYOLOE(
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|         model_file,
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|         params_file,
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|         config_file,
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|         runtime_option=runtime_option,
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|         model_format=fd.ModelFormat.ONNX)
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| 
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|     model.postprocessor.apply_decode_and_nms()
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| 
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|     # 预测图片分割结果
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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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| 
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|     # 可视化结果
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|     vis_im = fd.vision.vis_detection(im, result, score_threshold=0.5)
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|     cv2.imwrite("visualized_result.jpg", vis_im)
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|     print("Visualized result save in ./visualized_result.jpg")
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