| --- |
| title: Human Face Filter Tool |
| license: other |
| tags: |
| - image-processing |
| - face-detection |
| - dataset-cleaning |
| - opencv |
| - yunet |
| - python |
| pretty_name: Human Face Filter Tool |
| --- |
| |
| # Human Face Filter Tool |
|
|
| A simple local dataset cleaning tool for detecting and separating images that contain human faces. |
|
|
| This tool scans a local `dataset` folder using OpenCV YuNet face detection and moves images with detected human faces into a separate `removed_human_faces` folder. |
|
|
| It is designed for dataset preparation workflows where human face images should be filtered out before uploading or using the cleaned dataset. |
|
|
| ## Features |
|
|
| * Detects human faces using OpenCV YuNet |
| * Moves detected face images outside the dataset folder |
| * Keeps the original folder structure when moving files |
| * Supports common image formats such as JPG, PNG, WEBP, BMP, and TIFF |
| * Uses strict landmark geometry checks to reduce false positives |
| * Safer default behavior: files are moved, not deleted |
|
|
| ## Folder Structure |
|
|
| ```text |
| human-face-filter-tool/ |
| ├─ dataset/ |
| ├─ face_detection_yunet.onnx |
| ├─ remove_face_images.py |
| ├─ remove_face_images.bat |
| ├─ requirements.txt |
| └─ README.md |
| ``` |
|
|
| After running the script, images with detected human faces will be moved to: |
|
|
| ```text |
| removed_human_faces/ |
| ``` |
|
|
| ## Installation |
|
|
| Install the required Python packages: |
|
|
| ```bash |
| pip install -r requirements.txt |
| ``` |
|
|
| ## Usage |
|
|
| Place the images you want to scan inside the `dataset` folder. |
|
|
| Then run: |
|
|
| ```bash |
| python remove_face_images.py |
| ``` |
|
|
| On Windows, you can also run: |
|
|
| ```bash |
| remove_face_images.bat |
| ``` |
|
|
| ## Output |
|
|
| The script scans all supported image files inside: |
|
|
| ```text |
| dataset/ |
| ``` |
|
|
| Images that contain detected human faces are moved to: |
|
|
| ```text |
| removed_human_faces/ |
| ``` |
|
|
| Images without detected human faces remain inside: |
|
|
| ```text |
| dataset/ |
| ``` |
|
|
| ## Important Notes |
|
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| This tool does not modify the image content. It only moves images that are detected as containing human faces. |
|
|
| By default, files are not deleted. They are moved to `removed_human_faces` for manual review. |
|
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| Do not upload the `removed_human_faces` folder if your goal is to publish only the cleaned dataset. |
|
|
| ## Detection Settings |
|
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| The script uses strict filtering settings to reduce false positives, especially for nature, animal, texture, and object images. |
|
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| Main safety settings include: |
|
|
| ```python |
| SCORE_THRESHOLD = 0.80 |
| MIN_FACE_AREA_RATIO = 0.0015 |
| MAX_IMAGE_SIDE_FOR_SCAN = 1280 |
| DELETE_INSTEAD_OF_MOVE = False |
| ``` |
|
|
| You can adjust these values inside `remove_face_images.py` if needed. |
|
|
| ## Recommended Workflow |
|
|
| 1. Put your raw images inside the `dataset` folder. |
| 2. Run the script. |
| 3. Review the `removed_human_faces` folder. |
| 4. Keep only the cleaned `dataset` folder for your final dataset workflow. |
|
|
| ## Requirements |
|
|
| * Python 3.9+ |
| * OpenCV |
| * NumPy |
| * Pillow |
| * tqdm |
|
|
| Install all requirements with: |
|
|
| ```bash |
| pip install -r requirements.txt |
| ``` |
|
|
| ## License |
|
|
| Please check the license terms of the YuNet ONNX model and any datasets you process with this tool. |
|
|
| ## Disclaimer |
|
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| Face detection may not be perfect. Always manually review important datasets before publishing, training, or distribution. |
|
|
