OpenVINO notebooks documentation¶
Getting Started¶
Convert & Optimize¶
- Post-Training Quantization of PyTorch models with NNCF
- Convert a PyTorch Model to ONNX and OpenVINO IR
- Convert a TensorFlow Model to OpenVINO
- Quantize NLP models with OpenVINO Post-Training Optimization Tool
- Convert a PaddlePaddle Model to ONNX and OpenVINO IR
- Quantize a Segmentation Model and Show Live Inference
- Quantization of Image Classification Models
- Working with Open Model Zoo Models
- Object Detection Quantization
Model Demos¶
- Speech to Text with OpenVINO
- Optical Character Recognition (OCR) with OpenVINO
- Single Image Super Resolution with OpenVINO
- Super Resolution with PaddleGAN and OpenVINO
- Photos to Anime with PaddleGAN and OpenVINO
- Video Super Resolution with OpenVINO
- Image Background Removal with U^2-Net and OpenVINO
- Live Inference and Benchmark CT-scan Data with OpenVINO
- Monodepth Estimation with OpenVINO
- Style Transfer on ONNX Models with OpenVINO
- Handwritten Chinese and Japanese OCR