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Unified framework for building enterprise RAG pipelines with small, specialized models
State-of-the-Art Text Embeddings
The fundamental package for scientific computing with Python.
Intel® Graphics Compute Runtime for oneAPI Level Zero and OpenCL™ Driver
GIMP AI plugins with OpenVINO Backend
🤗 Optimum Intel: Accelerate inference with Intel optimization tools
Software Development Kit (SDK) for the Intel® Geti™ platform for Computer Vision AI model training.
An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.
OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
📚 Jupyter notebook tutorials for OpenVINO™
The code for our newly accepted paper in Pattern Recognition 2020: "U^2-Net: Going Deeper with Nested U-Structure for Salient Object Detection."
🤘 A curated list of DX (Developer Experience) resources
[ICLR 2020] "FasterSeg: Searching for Faster Real-time Semantic Segmentation" by Wuyang Chen, Xinyu Gong, Xianming Liu, Qian Zhang, Yuan Li, Zhangyang Wang
A scalable inference server for models optimized with OpenVINO™
Code for robust monocular depth estimation described in "Ranftl et. al., Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer, TPAMI 2022"
Train, Evaluate, Optimize, Deploy Computer Vision Models via OpenVINO™
Neural Network Compression Framework for enhanced OpenVINO™ inference
Pre-trained Deep Learning models and demos (high quality and extremely fast)
12 Weeks, 24 Lessons, IoT for All!
An Emacs framework for the stubborn martian hacker
Wasm powered Jupyter running in the browser 💡
📸 PyTorch implementation of MobileNetV3 for real-time semantic segmentation, with pretrained weights & state-of-the-art performance
Repository for OpenVINO's extra modules
GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training