Life Dynamics for python
run command must be like this: /usr/bin/python3 /home/nmakagonov/Daphny/daphny_counter/Daphny_counter.py -o /home/nmakagonov/Daphny/out.txt –path /media/nmakagonov/DiskD/NN_DATA/daphniacounter/DataForTraining/DataForTraining/MediumPopulation/medium_normal_RawImage/ -st 300 -sp 500where -o :path to the output text file where the counting result will be saved –path path to the directory with daphny-images -st number of the first frame for analysis -sp number of the last frame for analysis GitHub View Github
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Deep Level Set for Box-supervised Instance Segmentation in Aerial Images
Wentong Li, Yijie Chen, Wenyu Liu, Jianke Zhu* Any questions or discussions are welcomed! Installation Please refer to INSTALL.md for environment installation. This code is based on MMdetection and AerialDetection. Getting Started Please see GETTING_STARTED.md for the dataset preparation and basic usage. Visualization Instance segmentation results only under the supervision of box annotations on iSAID dataset. To Do COCO dataset Medical images Text images Citation
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The Neurips 2021 paper Searching Parameterized AP Loss for Object Detection
By Chenxin Tao,Zizhang Li,Xizhou Zhu,Gao Huang,Yong Liu,Jifeng Dai This is the official implementation of the Neurips 2021 paper Searching Parameterized AP Loss for Object Detection. Introduction TL; DR. Parameterized AP Loss aims to better align the network training and evaluation in object detection. It builds a unified formula for classification and localization tasks via parameterized functions, where the optimal parameters are searched automatically. Introduction. In evaluation of object detectors, Average Precision (AP) captures the performance of localization and classification sub-tasks […]
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Face Stylization based on the paper “AgileGAN: Stylizing Portraits by Inversion-Consistent Transfer Learning”
English | 简体中文 Introduction This repo is an efficient toolkit for Face Stylization based on the paper “AgileGAN: Stylizing Portraits by Inversion-Consistent Transfer Learning”. We note that since the training code of AgileGAN is not released yet, this repo merely adopts the pipeline from AgileGAN and combines other helpful practices in this literature. This project is based on MMCV and MMGEN, star and fork is welcomed 🤗! Results from FaceStylor trained by MMGEN Requirements CUDA 10.0 / CUDA 10.1 Python […]
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SpaCy3Urdu: run command to setup assets(dataset from UD)
Project setup run command to setup assets(dataset from UD) It uses project.yml file and download the data from UD GitHub repository. Download vectors Download fasttext vectors wget https://dl.fbaipublicfiles.com/fasttext/vectors-crawl/cc.ur.300.vec.gz Use these vectors to prune it so that model size is reduced. I’m currently using 100000 vectors for training the model. mkdir vectors python -m spacy init vectors ur cc.ur.300.vec.gz ./vectors –truncate 100000 –name ur_model.vectors Train the model Now run the command to train the tagger and parser for Urdu language.
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Python library to visualize circular plasmid maps
Plasmidviewer is a Python library to visualize plasmid maps from GenBank.This library provides only the function to visualize circular plasmids and doesn’t provide functions to edit nucleotides and sequence features.If you want to do such operations, please use QUEEN, which I have recently developed.(In fact, this library is implemented based on the visualization function of QUEEN) Installation You can install this library using the following single command:pip install git+https://github.com/ponnhide/plasmidviewer.git Example code
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A 16×16 clone of Minecraft Classic, written in Python with the Ursina Engine
A 16×16 clone of Minecraft Classic, written in Python with the Ursina Engine Features:Trees, Water(But there’s no gravity, so if you break a block next to water, expect to see some floating water), Random Terrain Generation(with Perlin Noise), Inventory(With 4 items:Grass, Stone, Copper and Diamond) and Shaders(with the prefabricated lit_with_shadows_shader of Ursina) Yet to be implemented: Infinite worlds, Caves, Multiplayer and Crafting(Perhaps in the very distant future?) Required Modules: Ursina(pip install ursina) and perlin_noise(pip install perlin-noise) Stone Texture from https://www.youtube.com/channel/UCvTkXfdV-oQRUYMM2R3p9zQ […]
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