yolov5之可视化特征图和检测结果

(1)对640*480*3的狗图进行检测和特征可视化

这个模型使用的是6.1版本的yolov5s.pt,狗图我放在百度云盘了,链接为:

链接:https://pan.baidu.com/s/1uPNK40bYCxHqIkd5LfMcuA 
提取码:lf0h 

import warnings

warnings.filterwarnings('ignore')
warnings.simplefilter('ignore')
import torch
import torch.nn as nn
import cv2
import numpy as np
import requests
import torchvision.transforms as transforms
from pytorch_grad_cam import EigenCAM
from pytorch_grad_cam.utils.image import show_cam_on_image, scale_cam_image
from PIL import Image

COLORS = np.random.uniform(0, 255, size=(80, 3))


def parse_detections(results):
    detections = results.pandas().xyxy[0]
    detections = detections.to_dict()
    boxes, colors, names = [], [], []

    for i in range(len(detections["xmin"])):
        confidence = detections["confidence"][i]
        if confidence < 0.2:
            continue
       

你可能感兴趣的:(深度学习,目标检测,pytorch,深度学习,python)