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Data augmentation for Chestx-ray classification using GAN
Pytorch implementation of AnimeGAN for fast photo animation
Photorealistic Style Transfer via Wavelet Transforms
Zalo aI 2020: Traffic sign detection using Retinanet and image tiling
🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022
Pytorch implementation for "Decoupled attention network for text recognition".
Diseases Detection from NIH Chest X-ray data
Copy-paste augmentation for segmentation and detection tasks
scikit-learn cross validators for iterative stratification of multilabel data
RPM-Net: Robust Point Matching using Learned Features (CVPR2020)
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…
[IJCV-2021] FairMOT: On the Fairness of Detection and Re-Identification in Multi-Object Tracking
Helper code for the 2021 Kaggle NFL Helmet Assignment Task
Python package for point cloud registration using probabilistic model (Coherent Point Drift, GMMReg, SVR, GMMTree, FilterReg, Bayesian CPD)
A data augmentations library for audio, image, text, and video.
A booklet on machine learning systems design with exercises. NOT the repo for the book "Designing Machine Learning Systems"
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
A Data Platform for Medical AI that enables building high-quality datasets and algorithms with lean process and advanced annotation features.
Machine Learning Interviews from FAANG, Snapchat, LinkedIn. I have offers from Snapchat, Coupang, Stitchfix etc. Blog: mlengineer.io.
A tensorflow2 implementation of ResNeXt(ResNeXt50, ResNeXt101).
tensorflow 2.x version of ResNeSt,RegNet,DETR
EfficientDet (Scalable and Efficient Object Detection) implementation in Keras and Tensorflow
An Open Source Machine Learning Framework for Everyone
Keras model trained using semi-hard triplet Loss (tensorflow function) on MNIST
A roadmap connecting many of the most important concepts in machine learning, how to learn them and what tools to use to perform them.