Data Scientists

An open-source package for creating experiments in behavioral science

PsychoPy PsychoPy is an open-source package for creating experiments in behavioral science. It aims to provide a single package that is: precise enough for psychophysics easy enough for teaching flexible enough for everything else able to run experiments in a local Python script or online in JavaScript To meet these goals PsychoPy provides a choice of interface – you can use asimple graphical user interface called Builder, or write your experiments inPython code. The entire application and library are written […]

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Python

Python News: What’s New From July 2021?

The release of Python 3.10 is just around the corner, and, as we reported in May, the new interpreter will be getting several improvements to error messages. The work on improved errors continues in Python 3.11. Yes, that’s right! Even though Python 3.10 won’t be released until October, work on Python 3.11 is already under way! Fine-Grained Error Locations in Tracebacks Pablo Galindo, the release manager for Python 3.10 and 3.11, shared in a July 16, 2021 tweet that he […]

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Video

A fantastic work in Video-level Anomaly Detection

This is my codes that can visualize the psnr image in testing videos. Future Frame Prediction for Anomaly Detection – A New Baseline This is a fantastic work in Video-level Anomaly Detection, published in CVPR2018. ShanghaiTech svip-lab has given their work in [Github]. Moreover, this work also have an interesting video in [YouTube]. And we can see that when anomaly examples happened, PSNR images will have a low response. Such is an example in avenue dataset. Testing images through PSNR […]

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Analysis

Domain Connectivity Analysis Tool In Python

DomainCAT (Domain Connectivity Analysis Tool) “See Connections Between Domains Right Meow” The Domain Connectivity Analysis Tool is used to analyze aggregate connectivity patterns across a set of domains during security investigations This project was a collaborative effort between myself and Matthew Pahl Introduction When analyzing pivots during threat hunting, most people approach it from the perspective of “what can a singlepivot tell you?” But often actors will set their domains up to use commodity hosting infrastructure, so the number ofentities […]

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Video

Real world Anomaly Detection in Surveillance Videos

This repository is a re-implementation of “Real-world Anomaly Detection in Surveillance Videos” with pytorch. As a result of our re-implementation, we achieved a much higher AUC than the original implementation. Datasets Download following data link and unzip under your $DATA_ROOT_DIR./workspace/DATA/UCF-Crime/all_rgbs Directory tree DATA/ UCF-Crime/ ../all_rgbs ../~.npy ../all_flows ../~.npy train_anomaly.txt train_normal.txt test_anomaly.txt test_normal.txt train-test script python main.py Reslut METHOD DATASET AUC Original paper(C3D two stream) UCF-Crimes 75.41 RTFM (I3D RGB) UCF-Crimes 84.03 Ours Re-implementation (I3D two stream) UCF-Crimes 84.45 Visualization Acknowledgment […]

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Discord

Discord optional detailed weather bot

Discord opsiyonel detaylı hava durumu botu önümüzdeki Perşembe ──► önümüzdeki Çarşamba ┌─────────┐┌─────────┐┌─────────┐┌─────────┐ │ Perşembe││ Cuma ││Cumartesi││ Pazar │ ├─────────┤├─────────┤├─────────┤├─────────┤ │°C: 16.7││°C: 5.82││°C: 4.45││°C: 2.39│ │ Clouds ││ Snow ││ Snow ││ Snow │ │hPa: 1009││hPa: 1018││hPa: 1018││hPa: 1019│ │Nem: 34││Nem: 54││Nem: 54││Nem: 99│ └─────────┘└─────────┘└─────────┘└─────────┘ ┌─────────┐┌─────────┐┌─────────┐ │Pazartesi││ Salı ││ Çarşamba│ ├─────────┤├─────────┤├─────────┤ │°C: 3.24││°C: 9.02││°C: 15.87│ │ Snow ││ Rain ││ Clouds │ │hPa: 1024││hPa: 1022││hPa: 1018│ │Nem: 97││Nem: 75││Nem: 49│ └─────────┘└─────────┘└─────────┘ önümüzdeki 7 günlük hava durumu tahminleri Olay Detaylı Bilgi Örnek […]

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Segmentation

Hypercorrelation Squeeze for Few-Shot Segmentation

Hypercorrelation Squeeze for Few-Shot Segmentation This is the implementation of the paper “Hypercorrelation Squeeze for Few-Shot Segmentation” by Juhong Min, Dahyun Kang, and Minsu Cho. Implemented on Python 3.7 and Pytorch 1.5.1. For more information, check out project [website] and the paper on [arXiv]. Requirements Python 3.7 PyTorch 1.5.1 cuda 10.1 tensorboard 1.14 Conda environment settings: conda create -n hsnet python=3.7 conda activate hsnet conda install pytorch=1.5.1 torchvision cudatoolkit=10.1 -c pytorch conda install -c conda-forge tensorflow pip install tensorboardX Preparing […]

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Semi-supervised

Semi-supervised Semantic Segmentation with Directional Context-aware Consistency

Semi-supervised Semantic Segmentation with Directional Context-aware Consistency (CAC) Xin Lai*, Zhuotao Tian*, Li Jiang, Shu Liu, Hengshuang Zhao, Liwei Wang, Jiaya Jia This is the official PyTorch implementation of our paper Semi-supervised Semantic Segmentation with Directional Context-aware Consistency that has been accepted to 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2021). [Paper] Our method achives the state-of-the-art performance on semi-supervised semantic segmentation. Based on CCT, this Repository also supports efficient distributed training with multiple GPUs. Environment The […]

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Scripts

Generate direct m3u playlist for all the channels subscribed in the Tata Sky portal

A script to generate the m3u playlist containing direct streamable file (.mpd or MPEG-DASH or DASH) based on the channels that the user has subscribed on the Tata Sky portal. You just have to login using your password or otp that’s it A working brain Knowledge of basic python A working Tata Sky account Channels that you want to watch, already subscribed (I’m sorry, no freebies) You can simply use the android app in your mobile phone or TV, login […]

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JAX

A Gaussian process (GP) library built in JAX (with objax)

Newt Newt is a Gaussian process (GP) library built in JAX (with objax), built and actively maintained by Will Wilkinson. Newt provides a unifying view of approximate Bayesian inference for GPs, and allows for the combination of many models (e.g. GPs, sparse GPs, Markov GPs, sparse Markov GPs) with the inference method of your choice (VI, EP, Laplace, Linearisation). For a full list of the methods implemented scroll down to the bottom of this page. Installation In the top directory […]

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