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.

2024年1月31日 · 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.

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

2021年11月14日 · YOLOv3 in PyTorch > ONNX > CoreML > TFLite. Contribute to ultralytics/yolov3 development by creating an account on GitHub.

detections = darknet.detect_image(netMain, metaMain, darknet_image, thresh=0.25) # Detection occurs at this line and return detections, for customize we can change the threshold.

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

5 天之前 · GitHub is where people build software. More than 150 million people use GitHub to discover, fork, and contribute to over 420 million projects.

Contribute to AITT-VN/yolobit_homebit_v3 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.

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