Kornia
ivy
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| Kornia | ivy | |
|---|---|---|
| 11 | 17 | |
| 9,323 | 14,016 | |
| 2.1% | 0.5% | |
| 9.4 | 10.0 | |
| 5 days ago | 6 days ago | |
| Python | Python | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
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
ivy
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Keras 3.0
See also https://github.com/unifyai/ivy which I have not tried but seems along the lines of what you are describing, working with all the major frameworks
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Show HN: Carton – Run any ML model from any programming language
is this ancillary to what [these guys](https://github.com/unifyai/ivy) are trying to do?
- Ivy: All in one machine learning framework
- Ivy ML Transpiler and Framework
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[D] Keras 3.0 Announcement: Keras for TensorFlow, JAX, and PyTorch
https://unify.ai/ They are trying to do what Ivy is doing already.
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Ask for help: what is the best way to have code both support torch and numpy?
Check Ivy.
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CoreML Stable Diffusion
ROCm's great for data centers, but good luck finding anything about desktop GPUs on their site apart from this lone blog post: https://community.amd.com/t5/instinct-accelerators/exploring...
There's a good explanation of AMD's ROCm targets here: https://news.ycombinator.com/item?id=28200477
It's currently a PITA to get common Python libs like Numba to even talk to AMD cards (admittedly Numba won't talk to older Nvidia cards either and they deprecate ruthlessly; I had to downgrade 8 versions to get it working with a 5yo mobile workstation). YC-backed Ivy claims to be working on unifying ML frameworks in a hardware-agnostic way but I don't have enough experience to assess how well they're succeeding yet: https://lets-unify.ai
I was happy to see DiffusionBee does talk the GPU in my late-model intel Mac, though for some reason it only uses 50% of its power right now. I'm sure the situation will improve as Metal 3.0 and Vulkan get more established.
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DL Frameworks in a nutshell
Won't it all come together with https://lets-unify.ai/ ?
- Unified Machine Learning
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[Discussion] Opinions on unify AI
What do you think about unify AI https://lets-unify.ai.
What are some alternatives?
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