yolov5 and yolov3-tf2
These two tools are competitors, with A representing a more recent and actively developed iteration of the YOLO object detection family, offering a wider range of export formats and a significantly larger community, while B provides an implementation of an earlier YOLO version in a specific TensorFlow 2.0 framework.
About yolov5
ultralytics/yolov5
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
Supports object detection, instance segmentation, and image classification tasks across diverse hardware through unified training and inference pipelines. Built on PyTorch with automated model optimization for deployment via PyTorch Hub, offering pre-trained weights and reproducible training from scratch with configurable architectures (Nano to Extra-Large). Integrates native inference acceleration through TorchScript, Docker containers, and cloud platforms like Google Colab and Kaggle for streamlined development and deployment workflows.
About yolov3-tf2
zzh8829/yolov3-tf2
YoloV3 Implemented in Tensorflow 2.0
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