Segment Animals is a Python package for segmenting (extracting) animals from images using deep learning models. It provides a pipeline that combines object detection and segmentation to identify and extract animals from images, making it useful for wildlife research, conservation efforts, and any application where you wish to remove the background from images containing animals.

Segment Animals builds upon the Segment Anything and MegaDetector models.

You can install Segment Animals using pip:

pip install segment-animals

Here's a quick example of how to use Segment Animals, for a more detailed guide refer to the notebook.

fromsegment_animalsimportAutoAnimalSegmenterfromsegment_animals.utilimportload_imagemodel=AutoAnimalSegmenter() image=load_image("path/to/your/image.jpg") detections, masks=model.process_image(image) print(f"Found {len(detections)} animals.")

fromsegment_animals.vizimportplot_detections_and_masksplot_detections_and_masks(image, detections, masks)

You should then see a visualisation along the lines of this (original image from Wikipedia)...

fromsegment_animals.vizimportextract_masks# Setting whole_image to False will return individual masks cropped to the extent# of the predicted masks.fori, mask_extractinenumerate(extract_masks(image, masks, whole_image=False)): # mask_extract is a PIL Image object so you can save it or manipulate it furthermask_extract.save(f"animal_mask_{i}.png")

Resulting in something like this:

It'd be great to hear how you're using Segment Animals! Drop me a line at Benjamin.Evans at ioz.ac.uk or open an issue on the GitHub repository.