Key | Value |
---|---|
FileName | ./usr/share/doc/python3-gdal/examples/validate_jp2.py.gz |
FileSize | 11350 |
MD5 | 50FB6E634B78C116D5FDCCF33954D6BA |
SHA-1 | 1054A906559F2BD8F67BB37D54DAF51255DF5B2C |
SHA-256 | F16DE849619999A277B3A182735F1A98C423C49249EB4E846C8A3E552C0C51A3 |
SSDEEP | 192:yBQskPfR6/JTDgSYuJuFVoypAA09iDlne4bcRJAr3sFK2aHBCDA0Sujrj9SkvLgY:ybjIqVjMIHorD2akB1XckvcnY |
TLSH | T10E32BE74D334135B3A7AC6F28918171C7441DC9E8A20BD3DBD1496819135AAA4FFF8DE |
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 | 576856 |
MD5 | DBBBDD8493EEEA6B4842A1FBE88EE2AA |
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 | 3.1.3+dfsg-1ubuntu2 |
SHA-1 | B73047EDA22A06E4F815523EDF77754DE58305E6 |
SHA-256 | F1A7CE03FD835C5552B3ECAE4F75979775EC45353615174541C4385A2D1DBDCA |