Deep Learning, NLP, NMT, AI, ML
Extensions for Python Markdown. Extension documentation is found here: https://facelessuser.github.io/pymdown-extensions/. License is MIT except for a few exceptions. See LICENSE for more info. GitHub https://github.com/facelessuser/pymdown-extensions
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Markdown is a light text markup format and a processor to convert that to HTML. The originator describes it as follows: Markdown is a text-to-HTML conversion tool for web writers. Markdown allows you to write using an easy-to-read, easy-to-write plain text format, then convert it to structurally valid XHTML (or HTML). — http://daringfireball.net/projects/markdown/ This (markdown2) is a fast and complete Python implementation of Markdown. It was written to closely match the behaviour of the original Perl-implemented Markdown.pl. Markdown2 also comes […]
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A Climate Data Management System (CDMS) is an integrated computer-based system that facilitates the effective archival, management, analysis, delivery and utilization of a wide range of integrated climate data (WMO 2014). pyopencdms aims to build a common Python API supporting multiple Climate Data Management Systems (CDMS) that use different underlying database engines. The image below shows the CliDE, Climsoft, MCH, MIDAS and other CDMSs being accessed through a single common API. In addition we will add support for the WIGOS […]
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Vignette Vignette is a Python library to create and manage thumbnails following the FreeDesktop standard. Thumbnails are stored in a shared directory so other apps following the standard can reuse them without having to generate their own thumbnails. Vignette can typically be used in file managers, image browsers, etc. Thumbnails are not limited to image files on disk but can be generated for other file types, for example videos or documents but also for any URL, for example a web […]
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This tool is able parse LIN Description Files, retrieve signal names and frames from them, as well as encoding messages using frame definitions and decoding them. Disclaimer The tool has been written according the LIN standards 1.3, 2.0, 2.1 and 2.2A, but due to errors in the documentation there’s no guarantee that the library will be able to parse your LDF. In such cases if possible first verify the LDF with a commercial tool such as Vector LDF Explorer or […]
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By Rui Liu, Hanming Deng, Yangyi Huang, Xiaoyu Shi, Lewei Lu, Wenxiu Sun, Xiaogang Wang, Jifeng Dai, Hongsheng Li. This repo is the official Pytorch implementation of FuseFormer: Fusing Fine-Grained Information in Transformers for Video Inpainting. Introduction Usage Prerequisites Install git clone https://github.com/ruiliu-ai/FuseFormer.git cd FuseFormer pip install -r requirements.txt Training Dataset preparation Download datasets (YouTube-VOS and DAVIS) into the data folder. mkdir data Training script python train.py -c configs/youtube-vos.json Test Download pre-trained model into checkpoints folder. mkdir checkpoints Test script […]
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Python solver for a rubik’s cube This program makes a 3D representation of a rubiks cube and solves it step by step. Usage To use this program you need to execute the following commands For 3D visualizations: python visualizer.py For statistics: python stats.py Requirements To use this program you need to install python 3.8.10 or later (although it will probably work on python 3.7) You will also need a recent version of numpy and vpython 7 or later, those can […]
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[arxiv] 1. Introduction This repo is the CMT model which impelement with pytorch, no reference source code so this is a non-official version. 2. Enveriments python 3.7+ pytorch 1.7.1 pillow apex opencv-python You can see this repo to find how to install the apex 3. DataSet Trainig /data/home/imagenet/train/xxx.jpeg, 0 /data/home/imagenet/train/xxx.jpeg, 1 … /data/home/imagenet/train/xxx.jpeg, 999 Testing /data/home/imagenet/test/xxx.jpeg, 0 /data/home/imagenet/test/xxx.jpeg, 1 … /data/home/imagenet/test/xxx.jpeg, 999 4. Training & Inference
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Unofficial pytorch implementation of paper “One-Shot Free-View Neural Talking-Head Synthesis for Video Conferencing” Driving | FOMM | Ours: Free-View: Train: python run.py –config config/vox-256.yaml –device_ids 0,1,2,3,4,5,6,7 Demo: python demo.py –config config/vox-256.yaml –checkpoint path/to/checkpoint –source_image path/to/source –driving_video path/to/driving –relative –adapt_scale –find_best_frame free-view (e.g. yaw=20, pitch=roll=0): python demo.py –config config/vox-256.yaml –checkpoint
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Code for paper “nnFormer: Interleaved Transformer for Volumetric Segmentation “. Please read our preprint at the following link: paper_address. Parts of codes are borrowed from nn-UNet. Installation 1、System requirements This software was originally designed and run on a system running Ubuntu 18.01, with Python 3.6, PyTorch 1.8.1, and CUDA 10.1. For a full list of software packages and version numbers, see the Conda environment file environment.yml. This software leverages graphical processing units (GPUs) to accelerate neural network training and evaluation; […]
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