YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
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Updated
Oct 19, 2024 - Python
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )
YOLOv3 in PyTorch > ONNX > CoreML > TFLite
Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.
YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/
Implementation of popular deep learning networks with TensorRT network definition API
PyTorch ,ONNX and TensorRT implementation of YOLOv4
🔥 TensorFlow Code for technical report: "YOLOv3: An Incremental Improvement"
YOLOv4, YOLOv4-tiny, YOLOv3, YOLOv3-tiny Implemented in Tensorflow 2.0, Android. Convert YOLO v4 .weights tensorflow, tensorrt and tflite
A PyTorch implementation of the YOLO v3 object detection algorithm
YoloV3 Implemented in Tensorflow 2.0
Accompanying code for Paperspace tutorial series "How to Implement YOLO v3 Object Detector from Scratch"
🙄 Difficult algorithm, Simple code.
Real-time Multi-person tracker using YOLO v3 and deep_sort with tensorflow
Complete YOLO v3 TensorFlow implementation. Support training on your own dataset.
Scaled-YOLOv4: Scaling Cross Stage Partial Network
TensorRT MODNet, YOLOv4, YOLOv3, SSD, MTCNN, and GoogLeNet
Collaboration with wangxupeng(https://github.com/wangxupeng)
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