chainer
caer
Our great sponsors
| chainer | caer | |
|---|---|---|
| 2 | 8 | |
| 5,862 | 749 | |
| 0.3% | - | |
| 0.0 | 0.0 | |
| 8 months ago | 6 months ago | |
| Python | Python | |
| MIT License | MIT License |
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.
chainer
-
ChaiNNer – Node/Graph based image processing and AI upscaling GUI
There is already an AI framework named Chainer: https://github.com/chainer/chainer
-
Protip: the upscaler matters a lot
Sorry maybe someone could chime in and help but I use chainer to upscale. https://github.com/chainer/chainer
caer
- Show HN: Caer – A lightweight GPU-accelerated Vision library in Python
- I wrote a lightweight GPU-accelerated Vision library in Python
-
Jetson nano python3 illegal instruction problem
I think it may have. If you look at line 10 of https://github.com/jasmcaus/caer/blob/master/configs.ini, you’ll see that caer has numpy and opencv-contrib-python dependencies that get referenced in its setup.py. If I recall correctly, pip on the nano doesn’t pick up the default numpy and opencv-python system installs, so when you go to install something like caer that has them as dependencies, it will install new copies except the wheel files that it grabs are incompatible. The solution I have found to work is to run something similar to the command above: “pip3 install —no-binary caer —no-binary numpy—no-binary opencv-contrib-python —no-binary typing-extensions —no-binary mypy —force-reinstall caer”. Some of those —no-binary options may not be necessary but they’ll at least ensure pip grabs the source for each of the dependencies and rebuilds it locally rather than using an imcompatible version. This command will take awhile! But you only should have to do it once.
- jasmcaus/caer Modern Computer Vision on the Fly
- Caer: High-performance Vision Library in Python (faster than Torchvision)
- Caer – A GPU-accelerated Computer Vision library (faster than Torchvision)
- jasmcaus/caer lightweight, scalable Computer Vision library for high-performance AI research
- Caer – A GPU-Accelerated Computer Vision Library in Python
What are some alternatives?
chaiNNer - A node-based image processing GUI aimed at making chaining image processing tasks easy and customizable. Born as an AI upscaling application, chaiNNer has grown into an extremely flexible and powerful programmatic image processing application.
fiftyone - The open-source tool for building high-quality datasets and computer vision models
leptonai - A Pythonic framework to simplify AI service building
img2table - img2table is a table identification and extraction Python Library for PDF and images, based on OpenCV image processing
tmu - Implements the Tsetlin Machine, Coalesced Tsetlin Machine, Convolutional Tsetlin Machine, Regression Tsetlin Machine, and Weighted Tsetlin Machine, with support for continuous features, drop clause, Type III Feedback, focused negative sampling, multi-task classifier, autoencoder, literal budget, and one-vs-one multi-class classifier. TMU is written in Python with wrappers for C and CUDA-based clause evaluation and updating.
opencv - Haskell binding to OpenCV-3.x
XNOR-popcount-GEMM-PyTorch-CPU-CUDA - A PyTorch implemenation of real XNOR-popcount (1-bit op) GEMM Linear PyTorch extension support both CPU and CUDA
Single-Image-Dehazing-Python - python implementation of the paper: "Efficient Image Dehazing with Boundary Constraint and Contextual Regularization"
SmallPebble - Minimal deep learning library written from scratch in Python, using NumPy/CuPy.
instant-ngp - Instant neural graphics primitives: lightning fast NeRF and more
warp-drive - Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning Framework on a GPU (JMLR 2022)
moviepy - Video editing with Python