From 364a7be64d6a961ae68276a96442f852b1b46bee Mon Sep 17 00:00:00 2001 From: "552068321@qq.com" Date: Tue, 8 Nov 2022 13:37:02 +0800 Subject: [PATCH] =?UTF-8?q?=E8=B0=83=E8=AF=95?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- app/yolov5/detect_server.py | 22 +++++++++++++++++++--- 1 file changed, 19 insertions(+), 3 deletions(-) diff --git a/app/yolov5/detect_server.py b/app/yolov5/detect_server.py index f6a14c0..d96e104 100644 --- a/app/yolov5/detect_server.py +++ b/app/yolov5/detect_server.py @@ -29,8 +29,10 @@ import os import platform import sys from pathlib import Path - +from app.schemas.TrainResult import DetectReport, DetectProcessValueDice +from app.controller.AlgorithmController import algorithm_process_value_websocket import torch +from datetime import datetime FILE = Path(__file__).resolve() ROOT = FILE.parents[0] # YOLOv5 root directory @@ -113,14 +115,28 @@ def run(id, # Run inference model.warmup(imgsz=(1 if pt else bs, 3, *imgsz)) # warmup seen, windows, dt = 0, [], (Profile(), Profile(), Profile()) + #回调函数参数定义 + report = DetectReport(rate_of_progess=0, precision=[], id=id) + + @algorithm_process_value_websocket() + def report_cellback(i, num_epochs, ori_img, res_img): + report.rate_of_progess = ((i + 1) / num_epochs) * 100 + #report.progress = (i + 1) + report.end_time = datetime.now() + #report.precision[0].value.append(reportAccu) + process_value_list = DetectProcessValueDice(ori_img=ori_img, res_img=res_img) + report.precision.append(process_value_list) + return report.dict() + #######定义声明完成################## + count = 0 for path, im, im0s, vid_cap, s in dataset: + count = count + 1 with dt[0]: im = torch.from_numpy(im).to(device) im = im.half() if model.fp16 else im.float() # uint8 to fp16/32 im /= 255 # 0 - 255 to 0.0 - 1.0 if len(im.shape) == 3: im = im[None] # expand for batch dim - # Inference with dt[1]: visualize = increment_path(save_dir / Path(path).stem, mkdir=True) if visualize else False @@ -206,9 +222,9 @@ def run(id, vid_writer[i] = cv2.VideoWriter(save_path, cv2.VideoWriter_fourcc(*'mp4v'), fps, (w, h)) vid_writer[i].write(im0) - # 原始图像路径/结果图像路径 传参 #online_img_tools.get_res_img(res_path=save_path, img_path=path, proj_no=pro) + report_cellback(count,len(os.listdir(source)),path,save_path) # Print time (inference-only) LOGGER.info(f"{s}{'' if len(det) else '(no detections), '}{dt[1].dt * 1E3:.1f}ms") #######统计检测结果:图片总数量,成功数量,失败数量