mmagic
openvino
| mmagic | openvino | |
|---|---|---|
| 5 | 17 | |
| 6,588 | 5,911 | |
| 1.1% | 3.0% | |
| 8.7 | 10.0 | |
| about 2 months ago | 6 days ago | |
| Jupyter Notebook | C++ | |
| Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
mmagic
- More than Editing, Unlock the Magic!
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MMEditing v1.0.0rc4 has been released （including Disco-Diffusion）
Join us to make it better! Try at https://github.com/open-mmlab/mmediting/tree/1.x
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MMDeploy: Deploy All the Algorithms of OpenMMLab
MMEditing: OpenMMLab image and video editing toolbox.
openvino
- FLaNK Stack 05 Feb 2024
- QUIK is a method for quantizing LLM post-training weights to 4 bit precision
- Intel OpenVINO 2023.1.0 released
- Intel OpenVINO 2023.1.0 released, open-source toolkit for optimizing and deploying AI inference
- OpenVINO 2023.1.0 released
- [N] Intel OpenVINO 2023.1.0 released, open-source toolkit for optimizing and deploying AI inference
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Powering Anomaly Detection for Industry 4.0
Anomalib is an open-source deep learning library developed by Intel that makes it easy to benchmark different anomaly detection algorithms on both public and custom datasets, all by simply modifying a config file. As the largest public collection of anomaly detection algorithms and datasets, it has a strong focus on image-based anomaly detection. It’s a comprehensive, end-to-end solution that includes cutting-edge algorithms, relevant evaluation methods, prediction visualizations, hyperparameter optimization, and inference deployment code with Intel’s OpenVINO Toolkit.
What are some alternatives?
a-PyTorch-Tutorial-to-Super-Resolution - Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network | a PyTorch Tutorial to Super-Resolution
TensorRT - NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference on NVIDIA GPUs. This repository contains the open source components of TensorRT.
Real-ESRGAN - Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.
deepsparse - Sparsity-aware deep learning inference runtime for CPUs
Image-Super-Resolution-via-Iterative-Refinement - Unofficial implementation of Image Super-Resolution via Iterative Refinement by Pytorch
mediapipe - Cross-platform, customizable ML solutions for live and streaming media.
Real-ESRGAN-colab - A Real-ESRGAN model trained on a custom dataset
stable-diffusion - Go to lstein/stable-diffusion for all the best stuff and a stable release. This repository is my testing ground and it's very likely that I've done something that will break it.
cnn-watermark-removal - Fully convolutional deep neural network to remove transparent overlays from images
neural-compressor - SOTA low-bit LLM quantization (INT8/FP8/INT4/FP4/NF4) & sparsity; leading model compression techniques on TensorFlow, PyTorch, and ONNX Runtime
Deep-Exemplar-based-Video-Colorization - The source code of CVPR 2019 paper "Deep Exemplar-based Video Colorization".
nebuly - The user analytics platform for LLMs