uformer-pytorch
caer
| uformer-pytorch | caer | |
|---|---|---|
| 1 | 8 | |
| 91 | 749 | |
| - | - | |
| 0.0 | 0.0 | |
| over 2 years ago | 7 months ago | |
| Python | Python | |
| MIT License | MIT License |
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uformer-pytorch
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[D] How to integrate ViT into U-Net using this library?
just use https://github.com/lucidrains/uformer-pytorch
caer
- Show HN: Caer – A lightweight GPU-accelerated Vision library in Python
- I wrote a lightweight GPU-accelerated Vision library in Python
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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?
Speech-enhancement - Deep learning for audio denoising
fiftyone - The open-source tool for building high-quality datasets and computer vision models
mixture-of-experts - A Pytorch implementation of Sparsely-Gated Mixture of Experts, for massively increasing the parameter count of language models
img2table - img2table is a table identification and extraction Python Library for PDF and images, based on OpenCV image processing
conformer - Implementation of the convolutional module from the Conformer paper, for use in Transformers
opencv - Haskell binding to OpenCV-3.x
Mask-RCNN-TF2.7.0-keras2.7.0 - Mask R-CNN for object detection and instance segmentation on Keras==2.7.0 and TensorFlow==2.7.0
Single-Image-Dehazing-Python - python implementation of the paper: "Efficient Image Dehazing with Boundary Constraint and Contextual Regularization"
instant-ngp - Instant neural graphics primitives: lightning fast NeRF and more
moviepy - Video editing with Python
RobustVideoMatting - Robust Video Matting in PyTorch, TensorFlow, TensorFlow.js, ONNX, CoreML!
Activeloop Hub - Data Lake for Deep Learning. Build, manage, query, version, & visualize datasets. Stream data real-time to PyTorch/TensorFlow. https://activeloop.ai [Moved to: https://github.com/activeloopai/deeplake]