I've analyzed the content of the uploaded Python script related to the COIL-100 dataset. Here are potential issues identified based on the provided hint regarding incorrect labels:

```json
{
    "issue": "Incorrect label extraction logic",
    "evidence": "label = file_name.split('_')[2].split('.')[0]",
    "description": "The script attempts to extract the label from the filename by splitting it at underscores and accessing the third element. This approach assumes a specific naming convention and may lead to incorrect labels if the filenames change or are not consistent with the expected format. This could result in inaccurate labeling of images in the dataset."
},
{
    "issue": "Label values do not correspond to object identifiers",
    "evidence": "LABELS = [str(x) for x in range(0, 360, 5)]",
    "description": "The defined labels range from 0 to 355 in increments of 5, which does not correspond to the actual number of objects in the COIL-100 dataset (which contains 100 objects). Therefore, this discrepancy indicates that the labels being assigned to images may not be valid, leading to further issues in dataset usability and analysis."
}
```

These identified issues relate directly to the script's functionality, indicating potential mislabeling and inconsistencies within the dataset itself.