Segmentation

Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation

The implementation of Reducing Infromation Bottleneck for Weakly Supervised Semantic Segmentation, Jungbeom Lee, Jooyoung Choi, Jisoo Mok, and Sungroh Yoon, NeurIPS 2021. [[paper]] Abstract Weakly supervised semantic segmentation produces pixel-level localization from class labels; however, a classifier trained on such labels is likely to focus on a small discriminative region of the target object. We interpret this phenomenon using the information bottleneck principle: the final layer of a deep neural network, activated by the sigmoid or softmax activation functions, causes […]

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Function

Helper functions to make expert elicitation easier

Assists with the construction of probability distributions built from expert elicited data for use in monte carlo simulations. Usage Until this is packaged for pip, copy elicit_distibutions.py in your code. Then: elicited is just a helper tool when using numpy and scipy, so you’ll need these too. import numpy as np import scipy Lognormal See Occurance and Applications for examples of lognormal distributions in nature. Expert: I have assets at risk that would generate a wide range of losses. Elicitor: […]

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metrics

A fast implementation of bss_eval metrics for blind source separation

Do you have a zillion BSS audio files to process and it is taking days ?Is your simulation never ending ? Fear no more! fast_bss_eval is here to help you! fast_bss_eval is a fast implementation of the bss_eval metrics for theevaluation of blind source separation. Our implementation of the bss_evalmetrics has the following advantages compared to other existing ones. seemlessly works with both numpy arrays and pytorch tensors very fast can be even faster by using an iterative solver (add […]

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PyTorch

Open source Optical Character Recognition based on PyTorch

GeneralOCR is open source Optical Character Recognition based on PyTorch. It makes a fidelity and useful tool to implement SOTA models on OCR domain. You can use them to infer and train the model with your customized dataset. The solution architecture of this project is re-implemented from facebook Detectron and openmm-cv. Refer to the guideline of gen_ocr installation Configuration Model text detection Supported Algorithms: Text Detection Table 1: Text detection algorithms, papers and parameters configuration in SDK. Model text recognition […]

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Semantic

Learning to Regress Bodies from Images using Differentiable Semantic Rendering

Getting Started DSR has been implemented and tested on Ubuntu 18.04 withpython 3.6. Clone the repo: git clone https://github.com/saidwivedi/DSR.git Install the requirements using conda: # conda source install_conda.sh Preparation of Data For evaluation, you need to download the pretrained DSR model and SMPL body models. Run the command following command For both evaluation and training, we use data processing techinque similar to SPIN. Kindly refer to their repo for more details.

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Bridge

Cobalt Strike Sleep Python Bridge

This project is ‘bridge’ between the sleep and python language. It allows the control of a Cobalt Strike teamserver through python without the need for for the standard GUI client. NOTE: This project is very much in BETA. The goal is to provide a playground for testing and is in no way an officially support feature. Perhaps this could be something added in the future to the core product. The project was inspired by the work done by @BinaryFaultline and […]

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Python

Python’s property(): Add Managed Attributes to Your Classes

With Python’s property(), you can create managed attributes in your classes. You can use managed attributes, also known as properties, when you need to modify their internal implementation without changing the public API of the class. Providing stable APIs can help you avoid breaking your users’ code when they rely on your classes and objects. Properties are arguably the most popular way to create managed attributes quickly and in the purest Pythonic style. In this tutorial, you’ll learn how to: […]

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Robot

A number of 2D waypoints will be predefined in ROS based robots to navigate to the destination avoiding obstacles

2D waypoints will be predefined in ROS based robots to navigate to the destination avoiding obstacles. A package that will buffer move_base goals until instructed to navigate to all waypoints in sequence. Installation Install the binaries needed for the package. sudo apt-get install ros-melodic-follow-waypoints New features not documented on wiki: The code can be run in this way: rosrun follow_waypoints follow_waypoints.py A wait_duration parameter. This sets wait duration in between waypoints. The default value is set to 0.0 sec.

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Machine Learning

Dual Adaptive Sampling for Machine Learning Interatomic potential

Dual Adaptive Sampling for Machine Learning Interatomic potential. How to cite If you use this code in your research, please cite this using: Hongliang Yang, Yifan Zhu, Erting Dong, Yabei Wu, Jiong Yang, and Wenqing Zhang. Dual adaptive sampling and machine learning interatomic potentials for modeling materials with chemical bond hierarchy. Phys. Rev. B 104, 094310 (2021). Install Install pymtp You should first install the python interface for mtp: https://github.com/hlyang1992/pymtp Install das You can download the code by

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OBJECT DETECTION

Complementary Trilateral Decoder for Fast and Accurate Salient Object Detection

The PyTorch code for ACM MM2021 paper “Complementary Trilateral Decoder for Fast and Accurate Salient Object Detection” Python 3.6 Pytorch 1.4+ OpenCV 4.0 Numpy TensorboardX Apex Download the SOD datasets and unzip them into data folder. We implement our method by PyTorch and conduct experiments on a NVIDIA 1080Ti GPU. We adopt pre-trained ResNet-18 and ResNet-50 as backbone networks, which are saved in res folder. We train our method on DUTS-TR and test our method on other datasets. After training, […]

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