Jan 31, 2024 · YOLO-World supports zero-shot inference, and three types of fine-tuning recipes: (1) normal fine-tuning, (2) prompt tuning, and (3) reparameterized fine-tuning.

Ultralytics offers two licensing options to suit different needs: AGPL-3.0 License: This OSI-approved open-source license is perfect for students, researchers, and enthusiasts.

Better, faster, peering over yonder. Improved large scale object detection in aerial/satellite imagery. - avanetten/yoltv4

Nov 14, 2021 · YOLOv3 in PyTorch > ONNX > CoreML > TFLite. Contribute to ultralytics/yolov3 development by creating an account on GitHub.

YOLOv5 is an open-source object detection framework in PyTorch developed by Ultralytics, supporting ONNX, CoreML, and TFLite.

Extension library for bluetooh support for Yolo:Bit - AITT-VN/yolobit_bluetooth

This video tutorial series shows you how to infer and train your own custom YOLOv4 models, Step-by-step - YOLOv4-Tutorials/3.

Create /results/ folder near with ./darknet executable file; Run validation: ./darknet detector valid cfg/coco.data cfg/yolov4.cfg yolov4.weights

Contribute to AITT-VN/yolobit_homebit_v3 development by creating an account on GitHub.

🍅🍅🍅YOLOv5-Lite: Evolved from yolov5 and the size of model is only 900+kb (int8) and 1.7M (fp16). Reach 15 FPS on the Raspberry Pi 4B~ - ppogg/YOLO