BEFORE EVERYTHING IS PUBLISHED ON FIGSHARE, PLEASE FIND THEM HERE:
- VM (1 - raw data; 2 - processed dataset):
- Z:\data\energyaccess\US_Power_Plants_RAW_NAIP.tar
Z:\data\energyaccess\US_Power_Plants_RAW_LS8.tar - Z:\data\energyaccess\dataplus2017\USPowerPlantDataset\USPowerPlantDataset_DATA\
- Z:\data\energyaccess\US_Power_Plants_RAW_NAIP.tar
- GPU (dataset only): /home/hyperion/dataplus/dataplus2017/USPowerPlantDataset/USPowerPlantDataset_DATA/
Either of the following holds the COMPLETE multi-band imagery & electrification map of Bihar, India.
- VM (1 - compressed; 2 - extracted for test and review):
- Z:\data\energyaccess\archive\IndianVillagesDataset_DATA.zip
- Z:\data\energyaccess\dataplus2017\IndianVillagesDataset\IndianVillagesDataset_DATA\
- Z:\data\energyaccess\archive\IndianVillagesDataset_DATA.zip
- GPU : NA
This section introduces the organization of each set of products, including data and code.
* More info: for data, please see the dataset documentation here, for code the creation demo here.
- /USPowerPlantDataset_DATA
- /uspp_naip - naip_ID_StateName_FuelCategory.tif
- /uspp_landsat - ls8_ID_StateName_FuelCategory.tif
- /exceptions
// none of accepted annotations marks it as containing a power plants
- /annotations
// polygons in .txt, and rasterized annotations in binary and confidence maps .png
- accepted_ann_json.txt
// accepted annotations condensed
- /binary - bilabels_ID.png
- /confidence - conflabels_ID.png
- accepted_ann_json.txt
- uspp_metadata.geojson
// power plants metadata
- README.md
// data explanations
- /USPowerPlantDataset_RAW
- US_Power_Plants_RAW_NAIP.tar.gz
- US_Power_Plants_RAW_LS8.tar.gz
- /USPowerPlantDataset_CREATION
- *A SUBSET OF USPowerPlantDataset_DATA* (ID=300~500)
- egrid2014_data_v2_PLNT14.xlsx
// a subset of the egrid document
- P1DATAPREP_cropPowerPlants.py
// prepares data - download
- P1DATAPREP_fixLs.m
// prepares data - preprocess
- P2ANNOGEN_getAllAcceptedCondensed.py
// fetches annotations
- P3DATAPROC_make.py
// constructs dataset
- P3DATAPROC_report.py
// displays data distribution
- P4TESTCLSFR_classify_sample.py
// tests classifiers
- README.md
// documentation
* More info: for data, please see data description here, for code the creation summary here.
- /IndianVillagesDataset_DATA
// size: 45,220
- imagery/
// 48-band imagery by village bounding boxes
- Naming: StateName(type)-VillageName-6DigitCensusID.tif *
- masks/
// binary masks of village bounding polygons
- Naming: StateName(type)-VillageName-6DigitCensusID.tif *
- ElectrificationMap_Bihar.geojson
// electrification map (of Bihar); i.e. ground truth from garv & village boundaries
- imagery/
- /creation
- /india_geojsons
// Indian administrative divisions .geojson
- makeIrriElecMetrics.js
// exports composite imagery from GEE
- /Scrape_code_and_files
// download village info from garv.gov.in
- /csv_scrape
// uses the download button
- /id_scrape
// uses the village IDs
- /csv_scrape
- /curr_data_files
// current data
- combine.py
- combine_garv_csv.py
- control.py
- geojson2shp.py
- visShapeFile.py
- readme.txt
// creation code documentation
- /india_geojsons
- /processing
- merge_crop.py
// merges or crops given image(s)
- getImgList.py
// generates districts_img_list.txt
- genSamples.m
// generate sample images
- readme.txt
// documentation for merge_crop.py
- merge_crop.py