Merge branch 'master' of https://gitea.star-rising.cn/xkrs_manan/RODY
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commit
012b878e5e
@ -102,8 +102,8 @@ def start_download_pt():
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@bp.route('/start_download_pt', methods=['get'])
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@bp.route('/start_download_pt', methods=['get'])
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def wrapped_function_start_download_pt():
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def wrapped_function_start_download_pt():
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param = request.args.get('param')
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param = request.args.get('param')
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func(param)
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data = func(param)
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return output_wrapped(0, 'success', '成功')
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return output_wrapped(0, 'success', data)
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return wrapped_function_start_download_pt
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return wrapped_function_start_download_pt
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@ -309,9 +309,6 @@ def Export_model_RODY(params_str):
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zipf.write(file, arcname=Path(file).name) # 将torchscript和onnx模型压缩
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zipf.write(file, arcname=Path(file).name) # 将torchscript和onnx模型压缩
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return exp_outputPath
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return exp_outputPath
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zipf.write(modellist[1], arcname=modellist[1])
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zip_inputpath = os.path.join(exp_outputPath, "inference_model")
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zip_outputPath = os.path.join(exp_outputPath, "inference_model.zip")
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@obtain_train_param()
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@obtain_train_param()
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@ -397,7 +394,7 @@ def returnDownloadParams():
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params_list = [
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params_list = [
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{"index": 0, "name": "exp_inputPath", "value": 'E:/alg_demo-master/alg_demo/app/yolov5/圆孔_123_RODY_1_640.pt',
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{"index": 0, "name": "exp_inputPath", "value": 'E:/alg_demo-master/alg_demo/app/yolov5/圆孔_123_RODY_1_640.pt',
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"description": '转化模型输入路径',
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"description": '转化模型输入路径',
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"default": '/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights/new磁环检测test_183504733393264640_R-DDM_11.pt/',
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"default": 'E:/alg_demo-master/alg_demo/app/yolov5/圆孔_123_RODY_1_640.pt/',
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"type": "S", 'show': False},
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"type": "S", 'show': False},
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{"index": 1, "name": "device", "value": 'gpu', "description": 'CPU或GPU', "default": 'gpu', "type": "S",
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{"index": 1, "name": "device", "value": 'gpu', "description": 'CPU或GPU', "default": 'gpu', "type": "S",
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'show': False}
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'show': False}
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@ -224,10 +224,10 @@ def run(id,
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# 原始图像路径/结果图像路径 传参
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# 原始图像路径/结果图像路径 传参
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#online_img_tools.get_res_img(res_path=save_path, img_path=path, proj_no=pro)
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#online_img_tools.get_res_img(res_path=save_path, img_path=path, proj_no=pro)
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print('数量:',count)
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# print('数量:',count)
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print('总量:',len(os.listdir(source)))
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# print('总量:',len(os.listdir(source)))
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print('path:',path)
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# print('path:',path)
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print('path:', str(save_path))
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# print('path:', str(save_path))
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report_cellback(count,len(os.listdir(source)),path,str(save_path))
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report_cellback(count,len(os.listdir(source)),path,str(save_path))
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# Print time (inference-only)
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# Print time (inference-only)
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LOGGER.info(f"{s}{'' if len(det) else '(no detections), '}{dt[1].dt * 1E3:.1f}ms")
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LOGGER.info(f"{s}{'' if len(det) else '(no detections), '}{dt[1].dt * 1E3:.1f}ms")
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