BCNet Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers [BCNet, CVPR 2021] This is the official pytorch implementation of BCNet built on the open-source detectron2. Lei Ke, Yu-Wing Tai, Chi-Keung TangCVPR 2021 Two-stage instance segmentation with state-of-the-art performance. Image formation as composition of two overlapping layers. Bilayer decoupling for the occluder and occludee. Efficacy on both the FCOS and Faster R-CNN detectors. Under construction. Our code and pretrained model will be fully released in two months. Visualization of Occluded Objects Qualitative […]

Distribuuuu The pure and clear PyTorch Distributed Training Framework. Distribuuuu is a Distributed Classification Training Framework powered by native PyTorch. Please check tutorial for detailed Distributed Training tutorials: Single Node Single GPU Card Training [snsc.py] Single Node Multi-GPU Crads Training (with DataParallel) [snmc_dp.py] Multiple Nodes Multi-GPU Cards Training (with DistributedDataParallel) ImageNet training example [imagenet.py] For the complete training framework, please see distribuuuu. Requirements and Usage Dependency Install PyTorch>= 1.5 (has been tested on 1.5, 1.7.1 and 1.8) Install other dependencies: […]

ClearML ClearML – Auto-Magical Suite of tools to streamline your ML workflow. Experiment Manager, ML-Ops and Data-Management ClearML is a ML/DL development and production suite, it contains three main modules: Experiment Manager – Automagical experiment tracking, environments and results ML-Ops – Automation, Pipelines & Orchestration solution for ML/DL jobs (K8s / Cloud / bare-metal) Data-Management – Fully differentiable data management & version control solution on top of object-storage(S3/GS/Azure/NAS) ClearML Experiment Manager Adding only 2 lines to your code gets you […]

DSM The source code for paper Enhancing Unsupervised Video Representation Learning by Decoupling the Scene and the Motion 1. Introduction (scene-dominated to motion-dominated) Video datasets are usually scene-dominated, We propose to decouple the scene and the motion (DSM) with two simple operations, so that the model attention towards the motion information is better paid. The generated triplet is as below: What DSM learned? With DSM pretrain, the model learn to focus on motion region (Not necessarily actor) powerful without one […]

Hessian AWare Quantization HAWQ is an advanced quantization library written for PyTorch. HAWQ enables low-precision and mixed-precision uniform quantization, with direct hardware implementation through TVM. Installation PyTorch version >= 1.4.0 Python version >= 3.6 For training new models, you’ll also need NVIDIA GPUs and NCCL To install HAWQ and develop locally: git clone https://github.com/Zhen-Dong/HAWQ.git cd HAWQ pip install -r requirements.txt Getting Started Quantization-Aware Training An example to run uniform 8-bit quantization for resnet50 on ImageNet. export CUDA_VISIBLE_DEVICES=0 python quant_train.py -a […]

AALpy AALpy is a light-weight active automata learning library written in pure Python. By implementing a single method and a few lines of configuration, you can start learning automata. Whether you work with regular languages or you would like to learn models of reactive systems, AALpy supports a wide range of modeling formalisms, including deterministic, non-deterministic, and stochastic automata. You can use it to learn deterministic finite automata, Moore machines, and Mealy machines of deterministic systems. If the system that […]

Robotics Toolbox for Python. Synopsis This toolbox brings robotics-specific functionality to Python, and leveragesPython’s advantages of portability, ubiquity and support, and the capability ofthe open-source ecosystem for linear algebra (numpy, scipy), graphics(matplotlib, three.js, WebGL), interactive development (jupyter, jupyterlab,mybinder.org), and documentation (sphinx). The Toolbox provides tools for representing the kinematics and dynamics ofserial-link manipulators – you can easily create your own in Denavit-Hartenbergform, import a URDF file, or use over 30 supplied models for well-knowncontemporary robots from Franka-Emika, Kinova, Universal Robotics, […]

SnapMix SnapMix: Semantically Proportional Mixing for Augmenting Fine-grained Data (AAAI 2021) PyTorch implementation of SnapMix | paper Cite @inproceedings{huang2021snapmix, title={SnapMix: Semantically Proportional Mixing for Augmenting Fine-grained Data}, author={Shaoli Huang, Xinchao Wang, and Dacheng Tao}, year={2021}, booktitle={AAAI Conference on Artificial Intelligence}, } Setup Install Package Dependencies torch torchvision PyYAML easydict tqdm scikit-learn efficientnet_pytorch pandas opencv Datasets create a soft link to the dataset directory CUB dataset ln -s /your-path-to/CUB-dataset data/cub Car dataset ln -s /your-path-to/Car-dataset data/car Aircraft dataset ln -s /your-path-to/Aircraft-dataset […]

Ravens – Transporter Networks Ravens is a collection of simulated tasks in PyBullet for learning vision-based robotic manipulation, with emphasis on pick and place. It features a Gym-like API with 10 tabletop rearrangement tasks, each with (i) a scripted oracle that provides expert demonstrations (for imitation learning), and (ii) reward functions that provide partial credit (for reinforcement learning). (a) block-insertion: pick up the L-shaped red block and place it into the L-shaped fixture. (b) place-red-in-green: pick up the red blocks […]

Fisherman An Albion online fishing bot Discord Server for support and help with this bot! Fisherman is a free open source fishing bot written in python. Features: Customizable Open Source Auto-Catch Multiple Fishing Spots Fully external Works on any screen size Extremely optimal fish catching Uses MSS and OpenCV for effiecent object detection How To Use: If you aren’t using a realtek driver you will have to install VB Audio Cable. Sound has to be ran through VB Audio Cable […]