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Question
YOLOV5版本：V6.0
1、关于“TypeError: attempt_load() got an unexpected keyword argument 'map_location'”的提示，详细如下是执行和提示 (y5x11) D:\workspace\yolov5>python web_main.py [INFO] YOLOv5 Config: {'source': 'streams.txt', '@source': '为视频图像文件 地址', 'weights': 'runs/train/exp14/weights/best.pt', '@weights': '自己的 模型地址', 'device': '0', '@device': ' 使用的device类别，如是GPU，可填0', 'imgsz': 640, '@imgsz': '输入图像的大小', 'stride': 32, '@stride': ' 步长', 'conf_thres': 0.35, '@conf_thres': '置信值阈值', 'iou_thres': 0.45, '@iou_thres': ' iou阈值', 'augment': False, '@augment': '是否使用图像增强'}
fatal: Not a valid object name HEAD YOLOv5 2022-6-1 Python-3.8.13 torch-1.10.0+cu113 CUDA:0 (NVIDIA GeForce RTX 3060, 12288MiB)
Traceback (most recent call last): File "web_main.py", line 25, in
(y5x11) D:\workspace\yolov5>python web_main.py [INFO] YOLOv5 Config: {'source': 'streams.txt', '@source': '为视频图像文件 地址', 'weights': 'runs/train/exp14/weights/best.pt', '@weights': '自己的 模型地址', 'device': '0', '@device': ' 使用的device类别，如是GPU，可填0', 'imgsz': 640, '@imgsz': '输入图像的大小', 'stride': 32, '@stride': ' 步长', 'conf_thres': 0.35, '@conf_thres': '置信值阈值', 'iou_thres': 0.45, '@iou_thres': ' iou阈值', 'augment': False, '@augment': '是否使用图像增强'}
fatal: Not a valid object name HEAD YOLOv5 2022-6-1 Python-3.8.13 torch-1.10.0+cu113 CUDA:0 (NVIDIA GeForce RTX 3060, 12288MiB)
Traceback (most recent call last): File "web_main.py", line 25, in
darknet = Darknet(opt)
File "D:\workspace\yolov5\yolov5.py", line 20, in init
self.model = attempt_load(self.opt["weights"], map_location=self.device)
TypeError: attempt_load() got an unexpected keyword argument 'map_location'
2、代码如下：
web_main.py
import the necessary packages
from yolov5 import Darknet from camera import LoadStreams, LoadImages from utils.general import non_max_suppression, scale_coords, check_imshow from flask import Response from flask import Flask from flask import render_template import time import torch import json import cv2 import os
initialize a flask object
app = Flask(name)
initialize the video stream and allow the camera sensor to warmup
with open('yolov5_config.json', 'r', encoding='utf8') as fp: opt = json.load(fp) print('[INFO] YOLOv5 Config:', opt)
darknet = Darknet(opt) if darknet.webcam:
cudnn.benchmark = True # set True to speed up constant image size inference
else: dataset = LoadImages(darknet.source, img_size=opt["imgsz"], stride=darknet.stride) time.sleep(2.0)
@app.route("/") def index():
return the rendered template
def detect_gen(dataset, feed_type): view_img = check_imshow() t0 = time.time() for path, img, img0s, vid_cap in dataset: img = darknet.preprocess(img)
@app.route('/video_feed/')
def video_feed(feed_type):
"""Video streaming route. Put this in the src attribute of an img tag."""
if feed_type == 'Camera_0':
return Response(detect_gen(dataset=dataset, feed_type=feed_type),
mimetype='multipart/x-mixed-replace; boundary=frame')
if name == 'main': app.run(host='0.0.0.0', port="5000", threaded=True)
Additional
No response