# coding=utf-8 # Description: visualize yolo label image. import argparse import os import cv2 import numpy as np IMG_FORMATS = ["bmp", "jpg", "jpeg", "png", "tif", "tiff", "dng", "webp", "mpo"] def main(args): img_dir, label_dir, class_names = args.img_dir, args.label_dir, args.class_names label_map = dict() for class_id, classname in enumerate(class_names): label_map[class_id] = classname for file in os.listdir(img_dir): if file.split('.')[-1] not in IMG_FORMATS: print(f'[Warning]: Non-image file {file}') continue img_path = os.path.join(img_dir, file) label_path = os.path.join(label_dir, file[: file.rindex('.')] + '.txt') try: img_data = cv2.imread(img_path) height, width, _ = img_data.shape color = [tuple(np.random.choice(range(256), size=3)) for i in class_names] thickness = 2 with open(label_path, 'r') as f: for bbox in f: cls, x_c, y_c, w, h = [float(v) if i > 0 else int(v) for i, v in enumerate(bbox.split('\n')[0].split(' '))] x_tl = int((x_c - w / 2) * width) y_tl = int((y_c - h / 2) * height) cv2.rectangle(img_data, (x_tl, y_tl), (x_tl + int(w * width), y_tl + int(h * height)), tuple([int(x) for x in color[cls]]), thickness) cv2.putText(img_data, label_map[cls], (x_tl, y_tl - 10), cv2.FONT_HERSHEY_COMPLEX, 1, tuple([int(x) for x in color[cls]]), thickness) cv2.imshow('image', img_data) cv2.waitKey(0) except Exception as e: print(f'[Error]: {e} {img_path}') print('======All Done!======') if __name__ == '__main__': parser = argparse.ArgumentParser() parser.add_argument('--img_dir', default='VOCdevkit/voc_07_12/images') parser.add_argument('--label_dir', default='VOCdevkit/voc_07_12/labels') parser.add_argument('--class_names', default=['aeroplane', 'bicycle', 'bird', 'boat', 'bottle', 'bus', 'car', 'cat', 'chair', 'cow', 'diningtable', 'dog', 'horse', 'motorbike', 'person', 'pottedplant', 'sheep', 'sofa', 'train', 'tvmonitor']) args = parser.parse_args() print(args) main(args)