Key | Value |
---|---|
FileName | ./usr/share/doc/python3-gdal/examples/validate_cloud_optimized_geotiff.py.gz |
FileSize | 2983 |
MD5 | 0DF0630A3A8BA083D8A952E2FAB6054A |
SHA-1 | 1F7368D0F5D3A967A53CBF49D245DB8DE1D2EFA4 |
SHA-256 | 8846CB94990B9B2F0BB8672536A360685BDE7AE89E8147DBD4E729236825B06D |
SSDEEP | 48:X3sELN0VyjuCkWXvA3IzgocgDhIK6GhDiSjP8HuUA1NyACDUhSRbA4At8ESe809W:HsWNrjDXvA3IzgR6hrP8OU2NhCDUARrn |
TLSH | T12B515C7320E2A06324B7CEB8F39049625A77E6622D95C680F0A1F1344E59D3889E5F6F |
hashlookup:parent-total | 1 |
hashlookup:trust | 55 |
The searched file hash is included in 1 parent files which include package known and seen by metalookup. A sample is included below:
Key | Value |
---|---|
FileSize | 526972 |
MD5 | B4E9C1D74366C268B898C02D7B5BA1B2 |
PackageDescription | Python 3 bindings to the Geospatial Data Abstraction Library GDAL is a translator library for raster geospatial data formats. As a library, it presents a single abstract data model to the calling application for all supported formats. The related OGR library (which lives within the GDAL source tree) provides a similar capability for simple features vector data. . GDAL supports 40+ popular data formats, including commonly used ones (GeoTIFF, JPEG, PNG and more) as well as the ones used in GIS and remote sensing software packages (ERDAS Imagine, ESRI Arc/Info, ENVI, PCI Geomatics). Also supported many remote sensing and scientific data distribution formats such as HDF, EOS FAST, NOAA L1B, NetCDF, FITS. . OGR library supports popular vector formats like ESRI Shapefile, TIGER data, S57, MapInfo File, DGN, GML and more. . This package contains Python 3 bindings for the GDAL/OGR library. |
PackageMaintainer | Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com> |
PackageName | python3-gdal |
PackageSection | python |
PackageVersion | 3.0.4+dfsg-1build3 |
SHA-1 | FC36DC0732717D32FCB3B3EC29A2E5FFD251DCEF |
SHA-256 | 74A087A9E98BEE4FD78B8837080776AC54F0848FECA5A4A9BBB50A8682D34731 |