#python #coco #computervision #demo #detection #efficientdetd0 #efficientnet #focalloss #multibox #nms #objectdetection #pascalvoc #pytorch

https://github.com/toandaominh1997/EfficientDet.Pytorch

#javascript #annotation #annotation_tool #coco #computer_vision #create #image #labelling #machine_learning #ml #model #object_detection #tensorflow #training_data #vgg #vision #yolo

https://github.com/OvidijusParsiunas/myvision

#python #coco #computer_vision #conda #deep_learning #detectron2 #instance_segmentation #jupyter_notebook #large_image #machine_learning #mmdetection #object_detection #pip #pytorch #small_object_detection #yolov5

https://github.com/obss/sahi

#jupyter_notebook #ade20k #cityscapes #coco #image_segmentation #instance_segmentation #oneformer #panoptic_segmentation #semantic_segmentation #transformer #universal_segmentation

https://github.com/SHI-Labs/OneFormer

#python #classification #coco #computer_vision #deep_learning #hacktoberfest #image_processing #instance_segmentation #low_code #machine_learning #metrics #object_detection #oriented_bounding_box #pascal_voc #python #pytorch #tensorflow #tracking #video_processing #yolo

Supervision is a powerful tool for building computer vision applications. It allows you to easily load datasets, draw detections on images or videos, and count detections in specific zones. You can use any classification, detection, or segmentation model with it, and it has connectors for popular libraries like Ultralytics and Transformers. Supervision also offers customizable annotators to visualize your data and utilities to manage datasets in various formats. By using Supervision, you can streamline your computer vision projects and make them more reliable and efficient. Additionally, there are extensive tutorials and documentation available to help you get started quickly.

https://github.com/roboflow/supervision