Imagenet

Open-source projects categorized as Imagenet
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Language: + Python + Jupyter Notebook + JavaScript + C++ + TypeScript
Topics: Deep Learning Pytorch image-classification Computer Vision Tensorflow
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Top 23 Imagenet Open-Source Projects

  • 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

    • Project mention: FLaNK AI Weekly 18 March 2024 | dev.to | 2024-03-18

  • Swin-Transformer

    This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".

    • Project mention: Samsung expected to report 80% profit plunge as losses mount at chip business | news.ycombinator.com | 2023-10-10

    > there is really nothing that "normal" AI requires that is bound to CUDA. pyTorch and Tensorflow are backend agnostic (ideally...).

    There are a lot of optimizations that CUDA has that are nowhere near supported in other software or even hardware. Custom cuda kernels also aren't as rare as one might think, they will often just be hidden unless you're looking at libraries. Our more well known example is going to be StyleGAN[0] but it isn't uncommon to see elsewhere, even in research code. Swin even has a cuda kernel[1]. Or find torch here[1] (which github reports that 4% of the code is cuda (and 42% C++ and 2% C)). These things are everywhere. I don't think pytorch and tensorflow could ever be agnostic, there will always be a difference just because you have to spend resources differently (developing kernels is time resource). We can draw evidence by looking at Intel MKL, which is still better than open source libraries and has been so for a long time.

    I really do want AMD to compete in this space. I'd even love a third player like Intel. We really do need competition here, but it would be naive to think that there's going to be a quick catchup here. AMD has a lot of work to do and posting a few bounties and starting a company (idk, called "micro grad"?) isn't going to solve the problem anytime soon.

    And fwiw, I'm willing to bet that most AI companies would rather run in house servers than from cloud service providers. The truth is that right now just publishing is extremely correlated to compute infrastructure (doesn't need to be but with all the noise we've just said "fuck the poor" because rejecting is easy) and anyone building products has costly infrastructure.

    [0] https://github.com/NVlabs/stylegan2-ada-pytorch/blob/d72cc7d...

    [1] https://github.com/microsoft/Swin-Transformer/blob/2cb103f2d...

    [2] https://github.com/pytorch/pytorch/tree/main/aten/src

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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  • segmentation_models.pytorch

    Segmentation models with pretrained backbones. PyTorch.

    • Project mention: Instance segmentation of small objects in grainy drone imagery | /r/computervision | 2023-12-09

    Also, I’d suggest considering switching to the segmentation-models library - it provides U-Net models with a variety of pretrained backbones of as encoders. The author also put out a PyTorch version. https://github.com/qubvel/segmentation_models.pytorch https://github.com/qubvel/segmentation_models

  • EfficientNet-PyTorch

    A PyTorch implementation of EfficientNet and EfficientNetV2 (coming soon!)

  • TensorLayer

    Deep Learning and Reinforcement Learning Library for Scientists and Engineers

  • ml5-library

    Friendly machine learning for the web! 🤖

  • super-gradients

    Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.

    • Project mention: Zero-Shot Prediction Plugin for FiftyOne | dev.to | 2024-03-13

    Most computer vision models are trained to predict on a preset list of label classes. In object detection, for instance, many of the most popular models like YOLOv8 and YOLO-NAS are pretrained with the classes from the MS COCO dataset. If you download the weights checkpoints for these models and run prediction on your dataset, you will generate object detection bounding boxes for the 80 COCO classes.

  • WorkOS

    The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

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  • Efficient-AI-Backbones

    Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.

  • efficientnet

    Implementation of EfficientNet model. Keras and TensorFlow Keras.

    • Project mention: Getting Started with Gemma Models | dev.to | 2024-04-15

    Examples of lightweight models include MobileNet, a computer vision model designed for mobile and embedded vision applications, EfficientDet, an object detection model, and EfficientNet, a CNN that uses compound scaling to enable better performance. All these are lightweight models from Google.

  • ml-cvnets

    CVNets: A library for training computer vision networks

    • Project mention: Apple Researchers Introduce ByteFormer: An AI Model That Consumes Only Bytes And Does Not Explicitly Model The Input Modality - MarkTechPost | /r/singularity | 2023-06-16

    https://github.com/apple/ml-cvnets/tree/main/examples/byteformer - Where the code will be located once uploaded

  • EfficientFormer

    EfficientFormerV2 [ICCV 2023] & EfficientFormer [NeurIPs 2022]

    • Project mention: A look at Apple’s new Transformer-powered predictive text model | news.ycombinator.com | 2023-09-16

    I'm pretty fatigued on constantly providing references and sources in this thread but an example of what they've made availably publicly:

    https://github.com/snap-research/EfficientFormer

  • pytorch2keras

    PyTorch to Keras model convertor

    • Project mention: Help Needed: Converting PlantNet-300k Pretrained Model Weights from Tar to h5 Format Help | /r/learnpython | 2023-06-09

    It's almost certainly a pickled pytorch model so you will first need to load it using pytorch and then write it out to h5 (legacy keras format) with https://github.com/gmalivenko/pytorch2keras.

  • MEAL-V2

    MEAL V2: Boosting Vanilla ResNet-50 to 80%+ Top-1 Accuracy on ImageNet without Tricks. In NeurIPS 2020 workshop.

  • natural-adv-examples

    A Harder ImageNet Test Set (CVPR 2021)

  • CvT

    This is an official implementation of CvT: Introducing Convolutions to Vision Transformers.

    • Project mention: has anyone here implemented Convolutional Vision Transformer (CvT)? | /r/pytorch | 2023-05-16

    Isn't https://github.com/microsoft/CvT the official code?

  • datumaro

    Dataset Management Framework, a Python library and a CLI tool to build, analyze and manage Computer Vision datasets.

  • GCVit

    [ICML 2023] Official PyTorch implementation of Global Context Vision Transformers

  • SegmentationCpp

    A c++ trainable semantic segmentation library based on libtorch (pytorch c++). Backbone: VGG, ResNet, ResNext. Architecture: FPN, U-Net, PAN, LinkNet, PSPNet, DeepLab-V3, DeepLab-V3+ by now.

  • assembled-cnn

    Tensorflow implementation of "Compounding the Performance Improvements of Assembled Techniques in a Convolutional Neural Network"

  • PyTorch-Model-Compare

    Compare neural networks by their feature similarity

  • tensorflow-image-models

    TensorFlow port of PyTorch Image Models (timm) - image models with pretrained weights.

  • FQ-ViT

    [IJCAI 2022] FQ-ViT: Post-Training Quantization for Fully Quantized Vision Transformer

  • node-efficientnet

    tensorflowJS implementation of EfficientNet 🚀

  • SaaSHub

    SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives

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NOTE: The open source projects on this list are ordered by number of github stars. The number of mentions indicates repo mentiontions in the last 12 Months or since we started tracking (Dec 2020).

Imagenet related posts

Index

What are some of the best open-source Imagenet projects? This list will help you:

Project Stars
1 pytorch-image-models 29,659
2 Swin-Transformer 12,917
3 segmentation_models.pytorch 8,773
4 EfficientNet-PyTorch 7,715
5 TensorLayer 7,275
6 ml5-library 6,349
7 super-gradients 4,322
8 Efficient-AI-Backbones 3,783
9 efficientnet 2,057
10 ml-cvnets 1,666
11 EfficientFormer 940
12 pytorch2keras 846
13 MEAL-V2 684
14 natural-adv-examples 570
15 CvT 514
16 datumaro 483
17 GCVit 414
18 SegmentationCpp 400
19 assembled-cnn 328
20 PyTorch-Model-Compare 307
21 tensorflow-image-models 280
22 FQ-ViT 263
23 node-efficientnet 250

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