import numpy as np
import cv2
import torch

label_path = './coco128/labels/train2017/000000000094.txt'
image_path = './coco128/images/train2017/000000000094.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 xywhn2xyxy(x, w=640, h=640, padw=0, padh=0):

    y = x.clone() if isinstance(x, torch.Tensor) else np.copy(x)
    y[:, 0] = w * (x[:, 0] - x[:, 2] / 2) + padw  # top left x
    y[:, 1] = h * (x[:, 1] - x[:, 3] / 2) + padh  # top left y
    y[:, 2] = w * (x[:, 0] + x[:, 2] / 2) + padw  # bottom right x
    y[:, 3] = h * (x[:, 1] + x[:, 3] / 2) + padh  # bottom right y
    return y

#读取labels
with open(label_path, 'r') as f:
    lb = np.array([x.split() for x in f.read().strip().splitlines()], dtype=np.float32)  # labels
    print(lb)

# 读取图像文件
img = cv2.imread(str(image_path))
h, w = img.shape[:2]
lb[:, 1:] = xywhn2xyxy(lb[:, 1:], w, h, 0, 0)#反归一化
print(lb)

#绘图
for _, x in enumerate(lb):
    class_label = int(x[0])  # class

    cv2.rectangle(img,(x[1],x[2]),(x[3],x[4]),(0, 255, 0) )
    cv2.putText(img,str(class_label), (int(x[1]), int(x[2] - 2)),fontFace = cv2.FONT_HERSHEY_SIMPLEX,fontScale=1,color=(0, 0, 255),thickness=2)
cv2.imshow('show', img)
cv2.waitKey(0)#按键结束
cv2.destroyAllWindows()