yolov7 姿态识别-人体骨架-实时检测

利用官方发布的yolov7-w6-pose.pt权值文件，调用摄像头进行检测，直接附代码：（将该py文件加入官方代码yolov7-main根目录下，直接运行即可）

import matplotlib.pyplot as plt
import torch
import cv2
from torchvision import transforms
import numpy as np
from utils.datasets import letterbox
from utils.general import non_max_suppression_kpt
from utils.plots import output_to_keypoint, plot_skeleton_kpts

# 加载模型
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
weigths = torch.load('yolov7-w6-pose.pt')
model = weigths['model']
model = model.half().to(device)
_ = model.eval()


# 读取摄像头画面
url=0
cap = cv2.VideoCapture(url)
while (cap.isOpened()):
    ret, image = cap.read()
    #image = cv2.imread('xiaolu.jpg')
    image = letterbox(image, 960, stride=64, auto=True)[0]
    image_ = image.copy()
    image = transforms.ToTensor()(image)
    image = torch.tensor(np.array([image.numpy()]))
    image = image.to(device)
    image = image.half()

# 姿势识别
    with torch.no_grad():
        output, _ = model(image)
        output = non_max_suppression_kpt(output, 0.25, 0.65, nc=model.yaml['nc'], nkpt=model.yaml['nkpt'], kpt_label=True)
        output = output_to_keypoint(output)
    nimg = image[0].permute(1, 2, 0) * 255
    nimg = nimg.cpu().numpy().astype(np.uint8)
    nimg = cv2.cvtColor(nimg, cv2.COLOR_RGB2BGR)
    for idx in range(output.shape[0]):
        plot_skeleton_kpts(nimg, output[idx, 7:].T, 3)


# 打开摄像头
    cv2.imshow("ning",nimg)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break
cap.release()
cv2.destroyAllWindows()

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