Kornia
Pytorch
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Kornia | Pytorch | |
---|---|---|
11 | 334 | |
9,323 | 77,544 | |
2.1% | 2.1% | |
9.4 | 10.0 | |
4 days ago | 3 days ago | |
Python | Python | |
Apache License 2.0 | BSD 1-Clause 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.
Kornia
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[News] Kornia 0.6.6: ParametrizedLine API, load_image support for Apple Windows Developer, integration demos with Hugging Face and many more.
👉 https://github.com/kornia/kornia/releases/tag/v0.6.6
- [P] Kornia: Differential Computer Vision
- Kornia: Differential Computer Vision
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Hacker News top posts: May 10, 2022
Kornia: Differential Computer Vision\ (3 comments)
- Preprocessing for NN on GPU
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Top 5 Python libraries for Computer vision
Kornia - Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer vision problems. At its core, the package uses PyTorch as its main backend both for efficiency and to take advantage of the reverse-mode auto-differentiation to define and compute the gradient of complex functions.
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[D] CPU choice for machine learning server (Epyc vs. Threadripper)
Between "not being sure yet" about GPU operations in pre-processing and choosing high-end CPUs, I think you are overthinking the wrong alternative. Besides DALI, check whether you are using codecs besides nvidia/torchvision-supported jpeg and png, and if other GPU CV libraries meet your needs: torchvision kornia
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[P] Using PyTorch + NumPy? A bug that plagues thousands of open-source ML projects.
Use kornia.augmentation where this problem is solved doing the augmentations in batch outside the dataloader. https://github.com/kornia/kornia
Pytorch
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Tinygrad: Hacked 4090 driver to enable P2P
fyi should work on most 40xx[1]
[1] https://github.com/pytorch/pytorch/issues/119638#issuecommen...
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The Elements of Differentiable Programming
Sure, right here: https://github.com/pytorch/pytorch/blob/main/torch/autograd/...
Here's the documentation: https://pytorch.org/tutorials/intermediate/forward_ad_usage....
> When an input, which we call “primal”, is associated with a “direction” tensor, which we call “tangent”, the resultant new tensor object is called a “dual tensor” for its connection to dual numbers[0].
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Functions and operators for Dot and Matrix multiplication and Element-wise calculation in PyTorch
*My post explains Dot, Matrix and Element-wise multiplication in PyTorch.
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Dot vs Matrix vs Element-wise multiplication in PyTorch
In PyTorch with @, dot() or matmul():
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Building a GPT Model from the Ground Up!
import torch # we use PyTorch: https://pytorch.org data = torch.tensor(encode(text), dtype=torch.long) print(data.shape, data.dtype) print(data[:1000]) # the 1000 characters we looked at earlier will to the GPT look like this
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Open Source Ascendant: The Transformation of Software Development in 2024
AI's Open Embrace Artificial intelligence (AI) and machine learning (ML) are increasingly leveraging open-source frameworks like TensorFlow [https://www.tensorflow.org/] and PyTorch [https://pytorch.org/]. This democratization of AI tools is driving innovation and lowering entry barriers across industries.
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Best AI Tools for Students Learning Development and Engineering
Which label applies to a tool sometimes depends on what you do with it. For example, PyTorch or TensorFlow can be called a library, a toolkit, or a machine-learning framework.
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Element-wise vs Matrix vs Dot multiplication
In PyTorch with * or mul(). ` or mul()` can multiply 0D or more D tensors by element-wise multiplication:
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Bash Debugging
When I was at Facebook, I wrote a Python script to extract shell scripts from GitHub Actions workflows, so we could run them all through ShellCheck: https://github.com/pytorch/pytorch/blob/69e0bda9996865e319db...
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Releasing The Force Of Machine Learning: A Novice’s Guide 😃
PyTorch: An open-source deep learning framework that facilitates dynamic computational graphs, making it flexible and efficient for research and production.
What are some alternatives?
OpenCV - Open Source Computer Vision Library
Flux.jl - Relax! Flux is the ML library that doesn't make you tensor
Face Recognition - The world's simplest facial recognition api for Python and the command line
mediapipe - Cross-platform, customizable ML solutions for live and streaming media.
EasyOCR - Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
SimpleCV - The Open Source Framework for Machine Vision
flax - Flax is a neural network library for JAX that is designed for flexibility.
multi-object-tracker - Multi-object trackers in Python
tinygrad - You like pytorch? You like micrograd? You love tinygrad! ❤️ [Moved to: https://github.com/tinygrad/tinygrad]
gaps - A Genetic Algorithm-Based Solver for Jigsaw Puzzles :cyclone:
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more