训练时有一种报错：no labels found in xxx.cache
首先要确定我们的图像，标签文件夹内容无误。检查完后如果还不行，就看看训练用到的东西，比如dataset.py，部分代码如下：

def get_labels(self):
        """Returns dictionary of labels for YOLO training."""
        self.label_files = img2label_paths(self.im_files)
        cache_path = Path(self.label_files[0]).parent.with_suffix('.cache')
        try:
            cache, exists = load_dataset_cache_file(cache_path), True  # attempt to load a *.cache file
            assert cache['version'] == DATASET_CACHE_VERSION  # matches current version
            assert cache['hash'] == get_hash(self.label_files + self.im_files)  # identical hash
        except (FileNotFoundError, AssertionError, AttributeError):
            cache, exists = self.cache_labels(cache_path), False  # run cache ops

        # Display cache
        nf, nm, ne, nc, n = cache.pop('results')  # found, missing, empty, corrupt, total
        if exists and LOCAL_RANK in (-1, 0):
            d = f'Scanning {cache_path}... {nf} images, {nm + ne} backgrounds, {nc} corrupt'
            tqdm(None, desc=self.prefix + d, total=n, initial=n, bar_format=TQDM_BAR_FORMAT)  # display results
            if cache['msgs']:
                LOGGER.info('\n'.join(cache['msgs']))  # display warnings
        if nf == 0:  # number of labels found
            raise FileNotFoundError(f'{self.prefix}No labels found in {cache_path}, can not start training. {HELP_URL}')

img2label_paths(self.im_files)这个函数大概率有猫腻，跳进去看看。
以下是其中部分代码，发现人家用的名字叫images和labels

def img2label_paths(img_paths):
    """Define label paths as a function of image paths."""
    sa, sb = f'{os.sep}images{os.sep}', f'{os.sep}labels{os.sep}'  # /images/, /labels/ substrings
    return [sb.join(x.rsplit(sa, 1)).rsplit('.', 1)[0] + '.txt' for x in img_paths]

但我的文件夹名字对不上，所以把函数里的名字改过来就可以了（数据集小的话也可以直接改数据集名字）