SUPIR
openvino
| SUPIR | openvino | |
|---|---|---|
| 3 | 17 | |
| 3,458 | 5,996 | |
| - | 3.8% | |
| 7.1 | 10.0 | |
| 27 days ago | about 7 hours ago | |
| Python | C++ | |
| GNU General Public License v3.0 or later | 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.
SUPIR
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Compressing Images with Neural Networks
Current SOTA open source is I believe SUPIR (Example - https://replicate.com/p/okgiybdbnlcpu23suvqq6lufze), but it needs a lot of VRAM, or you can run it through replicate, or here's the repo (https://github.com/Fanghua-Yu/SUPIR)
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SUPIR Full Tutorial + 1 Click 12GB VRAM Windows & RunPod / Linux Installer + Batch Upscale + Comparison With Magnific
Original repo of SUPIR: https://github.com/Fanghua-Yu/SUPIR
- FLaNK Stack 05 Feb 2024
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?
Stable-Diffusion - Stable Diffusion, SDXL, LoRA Training, DreamBooth Training, Automatic1111 Web UI, DeepFake, Deep Fakes, TTS, Animation, Text To Video, Tutorials, Guides, Lectures, Courses, ComfyUI, Google Colab, RunPod, NoteBooks, ControlNet, TTS, Voice Cloning, AI, AI News, ML, ML News, News, Tech, Tech News, Kohya LoRA, Kandinsky 2, DeepFloyd IF, Midjourney
TensorRT - NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference on NVIDIA GPUs. This repository contains the open source components of TensorRT.
Graal - GraalVM compiles Java applications into native executables that start instantly, scale fast, and use fewer compute resources 🚀
deepsparse - Sparsity-aware deep learning inference runtime for CPUs
metaflow - :rocket: Build and manage real-life ML, AI, and data science projects with ease!
mediapipe - Cross-platform, customizable ML solutions for live and streaming media.
StableSR - Exploiting Diffusion Prior for Real-World Image Super-Resolution
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.
DeepCache - [CVPR 2024] DeepCache: Accelerating Diffusion Models for Free
neural-compressor - SOTA low-bit LLM quantization (INT8/FP8/INT4/FP4/NF4) & sparsity; leading model compression techniques on TensorFlow, PyTorch, and ONNX Runtime
nebuly - The user analytics platform for LLMs
tflite-micro - Infrastructure to enable deployment of ML models to low-power resource-constrained embedded targets (including microcontrollers and digital signal processors).