调试
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@ -29,8 +29,10 @@ import os
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import platform
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import platform
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import sys
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import sys
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from pathlib import Path
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from pathlib import Path
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from app.schemas.TrainResult import DetectReport, DetectProcessValueDice
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from app.controller.AlgorithmController import algorithm_process_value_websocket
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import torch
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import torch
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from datetime import datetime
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FILE = Path(__file__).resolve()
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FILE = Path(__file__).resolve()
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ROOT = FILE.parents[0] # YOLOv5 root directory
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ROOT = FILE.parents[0] # YOLOv5 root directory
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@ -113,14 +115,28 @@ def run(id,
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# Run inference
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# Run inference
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model.warmup(imgsz=(1 if pt else bs, 3, *imgsz)) # warmup
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model.warmup(imgsz=(1 if pt else bs, 3, *imgsz)) # warmup
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seen, windows, dt = 0, [], (Profile(), Profile(), Profile())
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seen, windows, dt = 0, [], (Profile(), Profile(), Profile())
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#回调函数参数定义
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report = DetectReport(rate_of_progess=0, precision=[], id=id)
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@algorithm_process_value_websocket()
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def report_cellback(i, num_epochs, ori_img, res_img):
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report.rate_of_progess = ((i + 1) / num_epochs) * 100
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#report.progress = (i + 1)
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report.end_time = datetime.now()
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#report.precision[0].value.append(reportAccu)
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process_value_list = DetectProcessValueDice(ori_img=ori_img, res_img=res_img)
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report.precision.append(process_value_list)
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return report.dict()
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#######定义声明完成##################
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count = 0
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for path, im, im0s, vid_cap, s in dataset:
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for path, im, im0s, vid_cap, s in dataset:
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count = count + 1
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with dt[0]:
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with dt[0]:
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im = torch.from_numpy(im).to(device)
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im = torch.from_numpy(im).to(device)
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im = im.half() if model.fp16 else im.float() # uint8 to fp16/32
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im = im.half() if model.fp16 else im.float() # uint8 to fp16/32
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im /= 255 # 0 - 255 to 0.0 - 1.0
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im /= 255 # 0 - 255 to 0.0 - 1.0
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if len(im.shape) == 3:
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if len(im.shape) == 3:
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im = im[None] # expand for batch dim
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im = im[None] # expand for batch dim
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# Inference
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# Inference
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with dt[1]:
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with dt[1]:
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visualize = increment_path(save_dir / Path(path).stem, mkdir=True) if visualize else False
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visualize = increment_path(save_dir / Path(path).stem, mkdir=True) if visualize else False
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@ -206,9 +222,9 @@ def run(id,
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vid_writer[i] = cv2.VideoWriter(save_path, cv2.VideoWriter_fourcc(*'mp4v'), fps, (w, h))
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vid_writer[i] = cv2.VideoWriter(save_path, cv2.VideoWriter_fourcc(*'mp4v'), fps, (w, h))
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vid_writer[i].write(im0)
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vid_writer[i].write(im0)
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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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report_cellback(count,len(os.listdir(source)),path,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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#######统计检测结果:图片总数量,成功数量,失败数量
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#######统计检测结果:图片总数量,成功数量,失败数量
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