Ultralytics YOLOv5 in PyTorch for object detection, instance segmentation, classification, training, and export.
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Open standard for machine learning interoperability
Unified framework for building enterprise RAG pipelines with small, specialized models
🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP
YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/
PyTorch implementation of YOLOv3, YOLOv3-SPP, and YOLOv3-tiny for real-time object detection with training, validation, inference, and multi-format export.
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.
1M param OCR model - runs on CPU, 15x faster than tesseract, close to 1B+ param models in accuracy
PyTorch to Keras model convertor