deepchem
caer
| deepchem | caer | |
|---|---|---|
| 4 | 8 | |
| 5,124 | 749 | |
| 1.8% | - | |
| 9.9 | 0.0 | |
| 4 days ago | 7 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.
deepchem
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Query
You can see a number of splitter implementations from the DeepChem package here. The code is quite elaborate but for your case it may not need to be. Still, if you can use their package for splitting that would be easiest.
- Deepchem – Democratizing Deep-Learning for Drug Discovery
- Deepchem dataset load_tox21()
- How do I transition into bioinformatics from a senior software engineer (14 years of experience)?
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?
torchdrug - A powerful and flexible machine learning platform for drug discovery
fiftyone - The open-source tool for building high-quality datasets and computer vision models
deepqmc - Deep learning quantum Monte Carlo for electrons in real space
img2table - img2table is a table identification and extraction Python Library for PDF and images, based on OpenCV image processing
bidd-molmap - MolMapNet: An Efficient ConvNet with Knowledge-based Molecular Represenations for Molecular Deep Learning
opencv - Haskell binding to OpenCV-3.x
OpenWorm - Repository for the main Dockerfile with the OpenWorm software stack and project-wide issues
Single-Image-Dehazing-Python - python implementation of the paper: "Efficient Image Dehazing with Boundary Constraint and Contextual Regularization"
chemicalx - A PyTorch and TorchDrug based deep learning library for drug pair scoring. (KDD 2022)
instant-ngp - Instant neural graphics primitives: lightning fast NeRF and more
pytorch_tempest - My repo for training neural nets using pytorch-lightning and hydra
moviepy - Video editing with Python