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.
Simple and Distributed Machine Learning Python Library porting ML algorithms for Spark
1M param OCR model - runs on CPU, 15x faster than tesseract, close to 1B+ param models in accuracy
PyTorch to Keras model convertor