yolo将标签数据打到原图上形成目标框

第一章

目标：为了查看自己在标注标签时是否准确，写了这段代码来将标注的框打到原图上

第二章

步骤：进行反归一化得到坐标画出矩形框

第二行是目标图片对应的txt,第三行是目标图片

第三章

全部代码如下：

import cv2
import numpy as nplabel_path = 'C:/Users/23918/Desktop/01_missing_hole_01.txt'
image_path = 'C:/Users/23918/Desktop/01_missing_hole_01.jpg'# 坐标转换，原始存储的是YOLOv5格式
# Convert nx4 boxes from [x, y, w, h] normalized to [x1, y1, x2, y2] where xy1=top-left, xy2=bottom-right
def xywh2xyxy(x, y, w, h, w1, h1, img):print("原图宽高:\nw1={}\nh1={}".format(w1, h1))# 边界框反归一化x_t = x * w1y_t = y * h1w_t = w * w1h_t = h * h1print("反归一化后输出：\n第一个:{}\t第二个:{}\t第三个:{}\t第四个:{}\t\n\n".format(x_t, y_t, w_t, h_t))# 计算坐标top_left_x = x_t - w_t / 2top_left_y = y_t - h_t / 2bottom_right_x = x_t + w_t / 2bottom_right_y = y_t + h_t / 2print("左上x坐标:{}".format(top_left_x))print("左上y坐标:{}".format(top_left_y))print("右下x坐标:{}".format(bottom_right_x))print("右下y坐标:{}".format(bottom_right_y))# 绘图  rectangle()函数需要坐标为整数cv2.rectangle(img, (int(top_left_x), int(top_left_y)), (int(bottom_right_x), int(bottom_right_y)), (0, 255, 0), 2)# cv2.imshow('show', img)cv2.imwrite('11.png', img)cv2.waitKey(0)  # 按键结束cv2.destroyAllWindows()# 读取labels
with open(label_path, 'r') as f:lines = f.read().strip().splitlines()lb = np.array([x.split() for x in lines], dtype=np.float32)  # labelsprint(lb)# 读取图像文件
img = cv2.imread(str(image_path))
h, w = img.shape[:2]# 反归一化并得到左上和右下坐标，画出矩形框
for label in lb:x, y, width, height = label[:4]xywh2xyxy(x, y, width, height, w, h, img)