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# ComfyUI-AutoCropFaces | |
Use RetinaFace to detect and automatically crop faces | |
Forked and modified from [biubug6/Pytorch_Retinaface](https://github.com/biubug6/Pytorch_Retinaface) | |
## Custom Nodes | |
### Auto Crop Faces | |
Detect faces and focus on one of them. | |
Sure, here is the updated documentation: | |
### Auto Crop Faces | |
Detect faces and focus on one of them. | |
* `number_of_faces`: How many faces would you like to detect in total? (default: 5, min: 1, max: 100) | |
* `start_index`: Which face would you like to start with? (default: 0, step: 1). The starting index of the detected faces list. If the start index is out of bounds, it wraps around in a circular fashion just like a Python list. | |
* `scale_factor`: How much padding would you like to add? 1 for no padding. (default: 1.5, min: 0.5, max: 10, step: 0.5) | |
* `shift_factor`: Where would you like the face to be placed in the output image? Set to 0 to place the face at the top edge, 0.5 to center it, and 1.0 to place it at the bottom edge. (default: 0.45, min: 0, max: 1, step: 0.01) | |
* `max_faces_per_image`: The maximum number of faces to detect for each image. (default: 50, min: 1, max: 1000, step: 1) | |
* `aspect_ratio`: The aspect ratio for cropping, specified as `width` : `height`. (default: 1:1) | |
![Simple Usage](images/workflow-AutoCropFaces-Simple.png) | |
![At Bottom Edge](images/workflow-AutoCropFaces-bottom.png) | |
Recommandation: | |
Users might upload extremely large images, so it would be a good idea to first pass through the ["Constrain Image"](https://github.com/pythongosssss/ComfyUI-Custom-Scripts#constrain-image) node. | |
![Pass Through Constrain Image first](images/workflow-AutoCropFaces-with-Constrain.png) | |
It now supports CROP_DATA, which is compatible with [WAS node suite](https://github.com/WASasquatch/was-node-suite-comfyui). | |
![Crop and Paste](images/Crop_Data.png) | |