An extremely basic API client for the Wyscout API for Python

wyscoutapi is an extremely basic API client for the Wyscout API (v2 & v3). Usage Install with pip install wyscoutapi. To connect to the Wyscout v3 api: import wyscoutapi client = wyscoutapi.WyscoutAPI( username=’myusername’, password=’mypassword’, ) client.player(329061) To use the v2 legacy API, or alter the rate-limit(defaults to 12 requests per second): import wyscoutapi client = wyscoutapi.WyscoutAPI( username=’myusername’, password=’mypassword’,

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Robust fine-tuning of zero-shot models

This repository contains code for the paper Robust fine-tuning of zero-shot models by Mitchell Wortsman*, Gabriel Ilharco*, Mike Li, Jong Wook Kim, Hannaneh Hajishirzi, Ali Farhadi, Hongseok Namkoong, Ludwig Schmidt. Abstract Large pre-trained models such as CLIP offer consistent accuracy across a range of data distributions when performing zero-shot inference (i.e., without fine-tuning on a specific dataset). Although existing fine-tuning approaches substantially improve accuracy in-distribution, they also reduce out-of-distribution robustness. We address this tension by introducing a simple and effective […]

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An implemented version of Face Detection using OpenCV and Mediapipe

Project Description: In this project, we will be using the live video feed from the camera to detect Faces. It will also detect some specific points such as ears, nose, lips and eyes. Requirements: Following modules need to be installed for it to work properly: OpenCV: OpenCV is a huge open-source library for computer vision, machine learning, and image processing. OpenCV supports a wide variety of programming languages like Python, C++, Java, etc. It can process images and videos to […]

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Graph Self-Attention Network for Learning Spatial-Temporal Interaction Representation in Autonomous Driving

Code for paper Graph Self-Attention Network for Learning Spatial-Temporal Interaction Representation in Autonomous Driving, which was published on IEEE Internet of Things Journal. @article{ye2021gsan, title={GSAN: Graph Self-Attention Network for Learning Spatial-Temporal Interaction Representation in Autonomous Driving}, author={Ye, Luyao and Wang, Zezhong and Chen, Xinhong and Wang, Jianping and Wu, Kui and Lu, Kejie}, journal={IEEE Internet of Things Journal}, year={2021}, publisher={IEEE} }    

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Integrating Oxylabs’ Residential Proxies with AIOHTTP

Requirements for the Integration For the integration to work you’ll need to install aiohttp library, use Python 3.6 version or higher and Residential Proxies. If you don’t have aiohttp library, you can install it by using pip command: You can get Residential Proxies here: https://oxylabs.io/products/residential-proxy-pool Proxy Authentication There are 2 ways to authenticate proxies with aiohttp.The first way is to authorize and pass credentials along with the proxy URL using aiohttp.BasicAuth:

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Kaggle G2Net Gravitational Wave Detection : 2nd place solution

Solution writeup: https://www.kaggle.com/c/g2net-gravitational-wave-detection/discussion/275341 Instructions 1. Download data You have to download the competition dataset from competition website,and place the files in input/ directory. ┣ input/ ┃ ┣ training_labels.csv ┃ ┣ sample_submission.csv ┃ ┣ train/ ┃ ┣ test/ ┃ ┣ configs.py ┣ … (Optional:) Add your hardware configurations

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Supercharge your NFTs with new behaviours and superpowers

Supercharge your NFTs with new behaviours and superpowers! WrapX is a collection of Wrappers (currently one – WrapXSet) to decorate your NTFs adding new capabilities NFTs exist outside any chain, smart contracts are just projections/representations/slices which sometimes are limiting their full potential This means that wrappers allow multiple legitimate representations of NFTs Wrappers are means to supercharge NFT actions and capabilities NB: WrapX is currently EXPERIMENTAL and NOT AUDITED/REVIEWED. Do Your Own Research and Use At Your Own Risk. Use-cases […]

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