yolo2kitti.py

from PIL import Image

import glob
import os


original_label_dir = '{YOLO DATASET PATH}'

image_dir = '{PNG IMAGE DIR}'
label_dir = '{KITTI TYPE LABEL PATH}'

images = glob.glob(os.path.join(image_dir, '*.png'))

# below ones are example of 7 class examples
name = [
    'bus',
    'car',
    'truck',
    'human',
    'bicycle',
    'motorcycle',
    'phone'
]

for im in images:
    
    fname = os.path.basename(im)
    print(fname)
    base_name = os.path.splitext(fname)[0]

    image = Image.open(im)
    w, h = image.size
    image.close()
    
    f = open(os.path.join(original_label_dir, '%s.txt' % base_name))
    data = f.read()
    f.close()

    data = data.split('\n')
    labels = []
    for d in data:
        if len(d) <= 1:
            continue
        d = d.split()
        d = [int(d[0])] + [float(e) for e in d[1:]]

        d[1] *= w
        d[3] *= w
        d[2] *= h
        d[4] *= h
        
        obj_name = name[d[0]]
        xmin = d[1] - d[3] / 2
        ymin = d[2] - d[4] / 2
        xmax = d[1] + d[3] / 2
        ymax = d[2] + d[4] / 2
                
        labels.append('%s 0.00 0 0.0 %.2f %.2f %.2f %.2f 0.0 0.0 0.0 0.0 0.0 0.0 0.0' % (obj_name, xmin, ymin, xmax, ymax))

    with open(os.path.join(label_dir, '%s.txt' % base_name), 'wt') as f:
        f.write('\n'.join(labels))