{"library":"sahi","type":"library","category":null,"description":"SAHI (Slicing Aided Hyper Inference) is a lightweight Python library designed to improve object detection and instance segmentation performance, especially for small objects in large or high-resolution images. It achieves this by dividing images into smaller overlapping slices, running inference on each slice, and then intelligently merging the predictions. Currently at version 0.11.36, SAHI has a frequent release cadence, often issuing patch releases to address bugs and introduce minor enhancements.","language":"python","status":"active","version":"0.11.36","tags":["computer vision","object detection","instance segmentation","deep learning","slicing inference","small object detection","YOLO","MMDetection","Detectron2","PyTorch"],"install":[{"cmd":"pip install sahi","imports":["from sahi import AutoDetectionModel","from sahi.predict import get_sliced_prediction","from sahi.utils.cv import read_image_as_pil","from sahi.utils.file import download_from_url"]},{"cmd":"pip install sahi[yolov5]","imports":[]},{"cmd":"pip install sahi[ultralytics]","imports":[]},{"cmd":"pip install sahi[mmdet]","imports":[]},{"cmd":"pip install sahi[detectron2]","imports":[]},{"cmd":"pip install sahi[huggingface]","imports":[]},{"cmd":"pip install sahi[torchvision]","imports":[]}],"homepage":null,"github":"https://github.com/obss/sahi","docs":"https://github.com/obss/sahi/tree/main/docs","changelog":"https://github.com/obss/sahi/releases","pypi":"https://pypi.org/project/sahi/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":46,"avg_install_s":53.1,"avg_import_s":null,"wheel_type":"wheel"},"url":"https://checklist.day/v1/registry/sahi/compatibility"},"provenance":{"verified_status":"passing","verified_at":"Sun Jun 28","last_verified":"Sun Jun 28","next_check":"Tue Jul 28","install_tag":null}}