此代码的功能是标注信息验证，将原图和YOLOv8标注文件（txt）放在同一个文件夹中，作为输入文件夹
程序将标注的信息还原到原图中，并将原图和标注后的图像一同保存，以便查看

两个draw_labels函数，分别是将目标区域轮廓标出来或者颜色填充

import cv2
import numpy as np
import osdef read_txt_labels(txt_file):"""从 txt 标注文件中读取标签:param txt_file: txt 标注文件路径:return: 标签列表"""with open(txt_file, "r") as f:labels = []for line in f.readlines():label_data = line.strip().split(" ")class_id = int(label_data[0])# 解析边界框坐标coordinates = [float(x) for x in label_data[1:]]labels.append([class_id, coordinates])return labelsdef draw_labels(image, labels):"""在图像上绘制分割区域轮廓:param image: 图像:param labels: 标签列表"""for label in labels:class_id, coordinates = label# 将坐标转换为整数并重新塑形为多边形points = [(int(x * image.shape[1]), int(y * image.shape[0])) for x, y in zip(coordinates[::2], coordinates[1::2])]# 使用多边形绘制轮廓cv2.polylines(image, [np.array(points)], True, (0, 0, 255), 2)  # 红色表示分割区域轮廓# def draw_labels(image, labels):
#   """
#   在图像上绘制分割区域
#   :param image: 图像
#   :param labels: 标签列表
#   """
#   for label in labels:
#     class_id, coordinates = label
#     # 将坐标转换为整数并重新塑形为多边形
#     points = [(int(x * image.shape[1]), int(y * image.shape[0])) for x, y in zip(coordinates[::2], coordinates[1::2])]
#     # 使用多边形填充
#     cv2.fillPoly(image, [np.array(points)], (0, 255, 0))  # 绿色表示分割区域def process_and_save_image(image_path, txt_path, output_folder):# 读取图像image = cv2.imread(image_path)labels = read_txt_labels(txt_path)# 复制原始图像以进行绘制image_with_labels = image.copy()# 绘制分割区域draw_labels(image_with_labels, labels)# 创建一个新的图像，左侧是原图，右侧是带标注的图combined_image = np.concatenate((image, image_with_labels), axis=1)# 定义输出图像路径base_filename = os.path.basename(image_path)output_image_path = os.path.join(output_folder, base_filename)# 保存图像cv2.imwrite(output_image_path, combined_image)def main(input_folder, output_folder):# 确保输出文件夹存在if not os.path.exists(output_folder):os.makedirs(output_folder)# 获取输入文件夹中的所有图片文件image_files = [f for f in os.listdir(input_folder) if f.lower().endswith(('.png', '.jpg', '.jpeg'))]for image_file in image_files:# 构建图像和标注文件的路径image_path = os.path.join(input_folder, image_file)txt_file = os.path.splitext(image_path)[0] + '.txt'# 检查标注文件是否存在if os.path.exists(txt_file):process_and_save_image(image_path, txt_file, output_folder)else:print(f"标注文件 {txt_file} 不存在，跳过图像 {image_file}")if __name__ == "__main__":input_folder_path = 'D:\Desktop\images'  # 替换为实际的输入文件夹路径output_folder_path = 'D:\Desktop\images_02'  # 替换为实际的输出文件夹路径main(input_folder_path, output_folder_path)

示例：