Datasets:
| license: mit | |
| task_categories: | |
| - computer-vision | |
| - image-classification | |
| tags: | |
| - computer-vision | |
| - image-quality | |
| - data-centric-ai | |
| size_categories: | |
| - 10K<n<100K | |
| # CleanVision Sample Images | |
| This dataset contains sample images for demonstrating [CleanVision](https://github.com/cleanlab/cleanvision), a Python package for automatically detecting issues in image datasets. | |
| ## Dataset Description | |
| This collection includes various images with different quality issues such as: | |
| - Blurry images | |
| - Dark/underexposed images | |
| - Overexposed images | |
| - Near-duplicate images | |
| - Images with various other quality issues | |
| ## Usage | |
| Download the dataset: | |
| ```bash | |
| wget https://huggingface.co/datasets/cleanlab/cleanvision-sample-images/resolve/main/image_files.zip | |
| unzip image_files.zip | |
| ``` | |
| Use with CleanVision: | |
| ```python | |
| from cleanvision import Imagelab | |
| # Point to the extracted images folder | |
| imagelab = Imagelab(data_path="path/to/extracted/images/") | |
| # Find issues in the dataset | |
| imagelab.find_issues() | |
| # Generate report | |
| imagelab.report() | |
| ``` | |
| ## License | |
| mit - see the [CleanVision repository](https://github.com/cleanlab/cleanvision) for details. | |