vision_transformer
beartype
vision_transformer | beartype | |
---|---|---|
7 | 18 | |
9,318 | 2,430 | |
2.5% | 2.8% | |
5.5 | 9.4 | |
about 2 months ago | 3 days ago | |
Jupyter Notebook | Python | |
Apache License 2.0 | 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.
vision_transformer
-
Can I use CLIP to tag my picture collection?
And one last thing, should I even be thinking of using CLIP for these tasks when Google has released a better model here: https://github.com/google-research/vision_transformer/blob/main/model_cards/lit.md
-
When the client's management is happy but their dev team is a pain
Google's vision transformers are type hinted.
-
Improving Search Quality for Non-English Queries with Fine-tuned Multilingual CLIP Models
We’re going to look at a model that Open AI has trained with a broad multilingual dataset: The xlm-roberta-base-ViT-B-32 CLIP model, which uses the ViT-B/32image encoder, and the XLM-RoBERTa multilingual language model. Both of these are pre-trained:
-
[R] How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers
JAX Code: https://github.com/google-research/vision_transformer
- [D] (Paper Overview) MLP-Mixer: An all-MLP Architecture for Vision
-
[P] Animesion: a framework, for anime (and related) character recognition. It uses Vision Transformers trained on a subset of Danbooru2018, that we rebranded as DAF:re, and can classify a given image into one of more than 3000 characters! Source code and checkpoints included.
For this project I used the pretrained models released by Google in Jax, using this particular PyTorch custom implementation. Those were pretrained on ImageNet21k with 14 M images among 21 K classes. Then yes I finetune on two datasets: one with 15 K images and 170 characters, and one with 3 K characters and almost 500 K images.
- Short term memory solutions for video tasks?
beartype
-
Writing Python Like Rust
https://github.com/beartype/beartype
I wish more people started using Beartype, it makes Python bearable
-
ChatGPT Git Hook Writes Your Commit Messages
I saw this on /r/Python the other day...
- When the client's management is happy but their dev team is a pain
-
Returning to snake's nest after a long journey, any major advances in python for science ?
As other folks have commented, type hints are now a big deal. For static typing the best checker is pyright. For runtime checking there is typeguard and beartype. These can be integrated with array libraries through jaxtyping. (Which also works for PyTorch/numpy/etc., despite the name.)
-
What are some features you wish Python had?
Maybe you're looking for https://github.com/beartype/beartype for runtime type enforcement; it's only at function calls, though, but probably a decent solution for codebases that are not completely typed for MyPy or pyright.
-
svg.py: Type-safe and powerful Python library to generate SVG files
It is though, if you add a type checker to your pipeline and use it without any escape hatches such as `Any` or `type: ignore`, you are essentially making the promise that your code is statically typed. But I say it is a matter of perspective because in my opinion runtime type checking should be avoided if we can get away with statically typed code, but there are type checkers that perform runtime type checking via annotations such as [Beartype](https://github.com/beartype/beartype) (with some trickery like assuming homogenous data structures as to not have to check every element of every structure). Anyway the definition of "type safe" is not 100% even in compiled languages.
- Python’s “Type Hints” are a bit of a disappointment to me
-
What's the best practice to validate parameter types at runtime in Python, with and without a third-party module?
There is the beartype project.
-
Statically typed Python
Personally I find working around mypy's quirks to be more effort than it's worth, so to offer another option: typeguard or beartype can be used to perform run-time type checking.
- Beartype: Unbearably fast runtime type checking in Python
What are some alternatives?
pytorch-image-models - PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNet-V3/V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
typeguard - Run-time type checker for Python
nerfstudio - A collaboration friendly studio for NeRFs
pydantic - Data validation using Python type hints
ImageNet21K - Official Pytorch Implementation of: "ImageNet-21K Pretraining for the Masses"(NeurIPS, 2021) paper
mypy - Optional static typing for Python
Fashion12K_german_queries
mypyc - Compile type annotated Python to fast C extensions
TorchSharp - A .NET library that provides access to the library that powers PyTorch.
toit - Program your microcontrollers in a fast and robust high-level language.
fashion-200k - Fashion 200K dataset used in paper "Automatic Spatially-aware Fashion Concept Discovery."
benchmarks - Some benchmarks of different languages