Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
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Tf Faster Rcnn | 3,595 | 3 years ago | 215 | mit | Python | |||||
Tensorflow Faster RCNN for Object Detection | ||||||||||
Deepdetect | 2,492 | 3 months ago | 92 | other | C++ | |||||
Deep Learning API and Server in C++14 support for Caffe, PyTorch,TensorRT, Dlib, NCNN, Tensorflow, XGBoost and TSNE | ||||||||||
Tensorflow2.0 Examples | 1,692 | a year ago | 99 | mit | Jupyter Notebook | |||||
🙄 Difficult algorithm, Simple code. | ||||||||||
Torchdistill | 1,171 | 2 | 3 months ago | 24 | November 06, 2023 | mit | Python | |||
A coding-free framework built on PyTorch for reproducible deep learning studies. 🏆22 knowledge distillation methods presented at CVPR, ICLR, ECCV, NeurIPS, ICCV, etc are implemented so far. 🎁 Trained models, training logs and configurations are available for ensuring the reproducibiliy and benchmark. | ||||||||||
Tensornets | 968 | 2 | 2 | 3 years ago | 12 | March 31, 2020 | 15 | mit | Python | |
High level network definitions with pre-trained weights in TensorFlow | ||||||||||
Bmw Tensorflow Training Gui | 954 | 6 months ago | apache-2.0 | Python | ||||||
This repository allows you to get started with a gui based training a State-of-the-art Deep Learning model with little to no configuration needed! NoCode training with TensorFlow has never been so easy. | ||||||||||
Relation Networks For Object Detection | 911 | 6 years ago | 12 | mit | Python | |||||
Relation Networks for Object Detection | ||||||||||
Nncf | 725 | 6 | 3 months ago | 16 | November 16, 2023 | 46 | apache-2.0 | Python | ||
Neural Network Compression Framework for enhanced OpenVINO™ inference | ||||||||||
Random Erasing | 697 | 5 months ago | 11 | apache-2.0 | Python | |||||
Random Erasing Data Augmentation. Experiments on CIFAR10, CIFAR100 and Fashion-MNIST | ||||||||||
Dota Doai | 676 | a year ago | 14 | mit | Jupyter Notebook | |||||
This repo is the codebase for our team to participate in DOTA related competitions, including rotation and horizontal detection. |