Yingbing Li's repositories
maptalks.js
A light and plugable JavaScript library for integrated 2D/3D maps.
COVID-19
Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE
COVID-19-Epidemic-Data-Set
The COVID-19 Epidemic Data Set provides data on the global multi-scale new coronavirus epidemic from 31st December 2019 to the end of the outbreak, and aims to provide authoritative, open and multi-scale new coronavirus (COVID-19) epidemic information for researchers. The COVID-19 epidemic dataset consists of three different scales, namely, the global scale, the national scale (provincial) and the national scale (the municipal). Among them, the epidemic attribute information includes global epidemic data, domestic epidemic data (provincial) and domestic epidemic data (local and municipal), each with 6 statistical texts: new confirmed cases, new cured cases, new deaths, total confirmed cases, total cured cases and total deaths. COVID-19疫情数据集提供自2019年12月31日至疫情结束逐日的全球多尺度新型冠状病毒疫情数据,旨在为广大科研工作者提供权威的、开放的和多尺度的新型冠状病毒(COVID-19)疫情信息。 COVID-19疫情数据集包括三种不同的尺度,即全球尺度、全国尺度(省级)和全国尺度(地级市)。其中,疫情属性信息包括全球疫情数据、国内疫情数据(省级)和国内疫情数据(地市级),每份数据含6个统计文本:新增确诊病例、新增治愈病例、新增死亡病例、总确诊病例、总治愈病例和总死亡病例。
COVID-19-TweetIDs
The repository contains an ongoing collection of tweets IDs associated with the novel coronavirus COVID-19 (SARS-CoV-2), which commenced on January 28, 2020.
DataMining
数据分析与挖掘
django_project
# django_dbms_project My project Natural Disaster Management System involves distribution of foods, cloths properly to natural disaster caused places. India’s size and diversity makes it one of the the most disaster-prone countries in Asia. Large coastal areas in the south suffer from cyclones, while the northern mountainous areas suffer from landslides and floods, and droughts regularly affect the country’s central region. Every year, these result in a huge loss of lives, damage infrastructure, and disrupt vital services. The country’s National Disaster Management Agency (NDMA) has just announced plans to build a national disaster database by 2020, which it hopes will help minimise the impact. With this natural disaster project we are able to give overall funds received to the government of Karnataka. We are to give store all the user information those able who are donating money for floods caused places.our database able to predict the cost management, proper distribution of foods medicines, cloths etc. Finally our database able to give overall money spent to all disaster caused places. In project user can also give feedback for supplied food and cloths that they have received good quality of products. Our web app will also gives the information about migrated people so that government can easily transfer funds, medicines, foods to the people. A major hurdle during the design of the project was displaying the web page of the Natural Disaster Management System. In our project we are using Django python web framework for web designing. Django is works on the principle of don’t repeat your yourself. For this database we are building dynamic web app. Since we are using python we are also able to plot graph pie charts and we are also using FusionChart. We are also using pandas for arranging data. Our web app consists of several forms for user requirements so that user can submit there feedback. #_________________________________________________________# COMMANDS 1.pip install -r required.txt 2.Install MongoDb Compass and run in localhost 3.go to downloaded folder 4.python manage.py makemigrations 5.python manage.py migrate 6.python manage.py createsuperuser 7.python manage.py collectstaic 8.python manage.py runserver https://127.0.0.1:8000/ #__________________________________________________________#
geoda
GeoDa: An introduction to spatial data analysis
GPSTk
The goal of the GPSTk project is to provide an open source library and suite of applications to the satellite navigation community--to free researchers to focus on research, not lower level coding.
landslide
Research project on building and evaluating deep learning models for landslides detection on satellite images
natural_disaster_pred
Using CNNs and Sentinel-2 satellite data to predict landslides
obj2gltf
Convert OBJ assets to glTF
spdep
Spatial Dependence: Weighting Schemes and Statistics
TY-R-Forecast
Deep learning models for typhoon rainfall forecasting
TyphoonSearchSys
NMEFC——台风相似路径系统
visualize-data-with-python
A Jupyter notebook using some standard techniques for data science and data engineering to analyze data for the 2017 flooding in Houston, TX.
yolov3
YOLOv3 in PyTorch > ONNX > CoreML > TFLite
yolov5
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
YOLOv6
YOLOv6: a single-stage object detection framework dedicated to industrial applications.