Deep Learning, NLP, NMT, AI, ML
Cube = { verts = {{0,0,0},{0,0,1},{0,1,0}…}, faces = {}, cols = {}, fcols = {}, } Download export_lua.py. In Blender, go to Edit > Preference > Addon > Install and choose export_lua.py. Tick the checkbox in the addon pannel to activate it. The option for exporting to LUA is located in File > Export > Export LUA.
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This repository provides a minimal example of NVIDIA’s Isaac Gym, to assist other researchers like me to quickly understand the code structure, to be able to design fully customised large-scale reinforcement learning experiments. The example is based on the official implementation from the Isaac Gym’s Benchmark Experiments, for which we have followed a similar implementation on Cartpole, but with a minimal number of lines of code aiming for maximal readability, and without using any third-party RL frameworks. Note: The current […]
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A huggingface transformers implementation of Transformer Memory as a Differentiable Search Index, Yi Tay, Vinh Q. Tran, Mostafa Dehghani, Jianmo Ni, Dara Bahri, Harsh Mehta, Zhen Qin, Kai Hui, Zhe Zhao, Jai Gupta, Tal Schuster, William W. Cohen, Donald Metzler Requirements: python=3.8 transformers=4.17.0 datasets=1.18.3 wandb Note: This is not the official repository. Goal of this repository Reproduce the results of DSI Large, Naive String Docid, NQ10K. According to Table 3 in the original paper, we should have [email protected]=0.347,[email protected]=0.605 Step1: Create […]
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Goal Create translation bot that will be translating messages between Ukrainian and Czech in popular messaging platforms. Results API For the translation we will use UFAL API – https://lindat.cz/translation/ Messaging Platforms Popularity There are various websites with statistics: It looks that Telegram is popular in Ukraine. API Telegram WhatsApp Messenger Viber Status: GitHub View Github
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Defense your python project/separated file by hiding it using encryption with remaining functionality and output ❕ This tool will be useful if you want to share your Python project/separated file without revealing its source code. All contents of the files are encrypted and cannot be read by a person, while this does not affect the functionality and the output of the code. 🛠 Usage: > cd ../SourceCodeDefencer >> python run_defencer.py ./path_target_project” readability=”32″> >> cd ../SourceCodeDefencer >> python run_defencer.py ./path_target_project ℹ️ℹ️ℹ️ […]
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this repo consists of several challenge ideas for a CTF, all based around web challenges. All can be run in docker containers, where the git and cert challenge run in the same container (docker-cert-and-git-poc). The first challenge consists of a “sql based cookie injection”, using flask as a webserver and mysql as the database. challenge 1 The second challenge resolves around git. challenge 2 The third challenge is about authenticating with a client cert with a certain “Subject” field in […]
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Code for GSF learning in offline Procgen. Note: The repo is under construction right now, some experiments might still be changed/ added. Since the dataset is very large due to operating on pixel observations, we provide a way to generate it from pre-trained PPO checkpoints instead of hosting 1Tb+ of data. Instructions Clone the repo Either train a PPO agent from scratch on 200 levels (see here: here), or download provided PPO checkpoints (same repo link). TLDR, you can run […]
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This is git add -p on steroids for patches. Given a my.patch you can run ./split-patch.py my.patch You can choose in which bucket to put each hunk. In any moment, you can quite and my.patch will contain unassigned hunks while all the other hunks will be moved to $BUCKET_NAME.patch. GitHub View Github
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Junjie Ye, Changhong Fu, Guangze Zheng, Danda Pani Paudel, and Guang Chen. Unsupervised Domain Adaptation for Nighttime Aerial Tracking. In CVPR, pages 1-10, 2022. Overview UDAT is an unsupervised domain adaptation framework for visual object tracking. This repo contains its Python implementation. Paper (coming soon) | NAT2021 benchmark Testing UDAT 1. Preprocessing Before training, we need to preprocess the unlabelled training data to generate training pairs. Download the proposed NAT2021-train set Customize the directory of the train set in lowlight_enhancement.py […]
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When you look at an image, you see the objects and people in it. However, when you read an image programmatically with Python or any other language, the computer sees an array of numbers. In this tutorial, you’ll learn how to manipulate images and perform basic image processing using the Python Pillow library. Pillow and its predecessor, PIL, are the original Python libraries for dealing with images. Even though there are other Python libraries for image processing, Pillow remains an […]
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