Comments (2)
@mnitin59 Thanks for catching this. Fixed this bug in #16.
I added that bit of code as an afterthought, just to check the correlation between total population per cluster and cluster wealth. I realized I hadn't cleaned it properly. The graph is also properly labelled now.
Also added the OSM files here in the data directory. Let us know if you have any additional questions. Thanks!
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To generate report.csv
, you'll need to uncomment the following section and download the images.
Note, you'll need to obtain an API key and a secret key to download Google Static Maps images. More information on that here. Unfortunately, we cannot redistribute the images under the Google Static Maps Terms of Services.
Please take note of the cost of obtaining images; downloading 1000 images costs around ~$1.6.
# Uncomment to download data
os.environ['GEO_AI_API_KEY'] = "INSERT API KEY HERE"
os.environ['GEO_AI_SECRET_KEY'] = "INSERT SECRET KEY HERE"
import data_download
data_download.get_satellite_images_with_labels(nightlights_bins_file, satellite_images_dir)
from ph-poverty-mapping.
Related Issues (17)
- Add project scaffold
- Regarding 03_lights_model HOT 1
- Transformation of VIIRS DNB data to .csv file ('nightlights.csv') HOT 17
- Update README
- Pop_sum and spatial join for nightlights.csv HOT 3
- PHHR70DT/PHHR70FL.DTA no longner exists HOT 1
- boundaries CSV files HOT 4
- 00_dhs_prep.ipynb Code error HOT 3
- dhs csv data HOT 2
- Hardware and Software Requirements HOT 2
- Best Model HOT 2
- dhs_regions HOT 6
- Add instructions and scripts for downloading and pre-processing DHS dataset HOT 3
- Add nighttime lights data, feature embeddings (csv format) to data directory HOT 9
- Add Philippine shapefile to data directory
- Fix nested cross validation script
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