nind-denoise
pytorch-tutorial
| nind-denoise | pytorch-tutorial | |
|---|---|---|
| 1 | 3 | |
| 23 | 29,160 | |
| - | - | |
| 2.1 | 0.0 | |
| 10 months ago | 9 months ago | |
| Python | Python | |
| GNU General Public License v3.0 only | MIT License |
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nind-denoise
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GIMP-ML Development
I am currently trying to improve the denoiser on https://github.com/trougnouf/nind-denoise with a modified U-Net and new data and I would like to add it to gimp before I switch development to a raw approach (beginning of pixel pipeline, ie a darktable module). I was considering G'MIC but maybe this is the way too :)
pytorch-tutorial
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PyTorch - What does contiguous() do?
I was going through this example of a LSTM language model on github (link).What it does in general is pretty clear to me. But I'm still struggling to understand what calling contiguous() does, which occurs several times in the code.
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How to 'practice' pytorch after finishing its basic tutorial?
I tried to move straight to practicing implementing papers and trying to understand other people's codes but failed miserably. I feel like there was too much of a gap between the basic tutorial and being able to implement ideas into code....hence the question: Is there any resource/way to practice pytorch in general? I did find this and this, but I just wanted to hear what others have gone through to become better at PyTorch up to the point they can build stuff from their own ideas
- [P] Probabilistic Machine Learning: An Introduction, Kevin Murphy's 2021 e-textbook is out
What are some alternatives?
BJDD_CVPR21 - This is the official implementation of Beyond Joint Demosaicking and Denoising from CVPRW21.
mixture-of-experts - PyTorch Re-Implementation of "The Sparsely-Gated Mixture-of-Experts Layer" by Noam Shazeer et al. https://arxiv.org/abs/1701.06538
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
InceptionTime - InceptionTime: Finding AlexNet for Time Series Classification
ilo - [ICML 2021] Official implementation: Intermediate Layer Optimization for Inverse Problems using Deep Generative Models
Conv-TasNet - A PyTorch implementation of Conv-TasNet described in "TasNet: Surpassing Ideal Time-Frequency Masking for Speech Separation" with Permutation Invariant Training (PIT).
pytorch-grad-cam - Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
BigGAN-PyTorch - The author's officially unofficial PyTorch BigGAN implementation.
bonito - A PyTorch Basecaller for Oxford Nanopore Reads
OpenNMT-py - Open Source Neural Machine Translation and (Large) Language Models in PyTorch
pycox - Survival analysis with PyTorch
a-PyTorch-Tutorial-to-Image-Captioning - Show, Attend, and Tell | a PyTorch Tutorial to Image Captioning