| Name | rio-tiler JSON |
| Version |
6.4.7
JSON |
| download |
| home_page | None |
| Summary | User friendly Rasterio plugin to read raster datasets. |
| upload_time | 2024-04-18 09:20:29 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.8 |
| license | BSD 3-Clause License
Copyright (c) 2021, cogeotiff
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
1. Redistributions of source code must retain the above copyright notice, this
list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.
3. Neither the name of the copyright holder nor the names of its
contributors may be used to endorse or promote products derived from
this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. |
| keywords |
cogeo
cloud optimized geotiff
stac
rasterio
slippy-map
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# rio-tiler
<p align="center">
<img src="https://user-images.githubusercontent.com/10407788/88133997-77560f00-cbb1-11ea-874c-a8f1d123a9df.jpg" style="max-width: 800px;" alt="rio-tiler"></a>
</p>
<p align="center">
<em>User friendly Rasterio plugin to read raster datasets.</em>
</p>
<p align="center">
<a href="https://github.com/cogeotiff/rio-tiler/actions?query=workflow%3ACI" target="_blank">
<img src="https://github.com/cogeotiff/rio-tiler/workflows/CI/badge.svg" alt="Test">
</a>
<a href="https://codecov.io/gh/cogeotiff/rio-tiler" target="_blank">
<img src="https://codecov.io/gh/cogeotiff/rio-tiler/branch/main/graph/badge.svg" alt="Coverage">
</a>
<a href="https://pypi.org/project/rio-tiler" target="_blank">
<img src="https://img.shields.io/pypi/v/rio-tiler?color=%2334D058&label=pypi%20package" alt="Package version">
</a>
<a href="https://anaconda.org/conda-forge/rio-tiler" target="_blank">
<img src="https://img.shields.io/conda/v/conda-forge/rio-tiler.svg" alt="Conda Forge">
</a>
<a href="https://pypistats.org/packages/rio-tiler" target="_blank">
<img src="https://img.shields.io/pypi/dm/rio-tiler.svg" alt="Downloads">
</a>
<a href="https://github.com/cogeotiff/rio-tiler/blob/main/LICENSE" target="_blank">
<img src="https://img.shields.io/github/license/cogeotiff/rio-tiler.svg" alt="Downloads">
</a>
<a href="https://mybinder.org/v2/gh/cogeotiff/rio-tiler/main?filepath=docs%2Fexamples%2F" target="_blank" alt="Binder">
<img src="https://mybinder.org/badge_logo.svg" alt="Binder">
</a>
</p>
---
**Documentation**: <a href="https://cogeotiff.github.io/rio-tiler/" target="_blank">https://cogeotiff.github.io/rio-tiler/</a>
**Source Code**: <a href="https://github.com/cogeotiff/rio-tiler" target="_blank">https://github.com/cogeotiff/rio-tiler</a>
---
## Description
`rio-tiler` was initially designed to create [slippy map
tiles](https://en.wikipedia.org/wiki/Tiled_web_map) from large raster data
sources and render these tiles dynamically on a web map. Since `rio-tiler` v2.0, we added many more helper methods to read
data and metadata from any raster source supported by Rasterio/GDAL.
This includes local and remote files via HTTP, AWS S3, Google Cloud Storage,
etc.
At the low level, `rio-tiler` is *just* a wrapper around the [rasterio](https://github.com/rasterio/rasterio) and [GDAL](https://github.com/osgeo/gdal) libraries.
## Features
- Read any dataset supported by GDAL/Rasterio
```python
from rio_tiler.io import Reader
with Reader("my.tif") as image:
print(image.dataset) # rasterio opened dataset
img = image.read() # similar to rasterio.open("my.tif").read() but returns a rio_tiler.models.ImageData object
```
- User friendly `tile`, `part`, `feature`, `point` reading methods
```python
from rio_tiler.io import Reader
with Reader("my.tif") as image:
img = image.tile(x, y, z) # read mercator tile z-x-y
img = image.part(bbox) # read the data intersecting a bounding box
img = image.feature(geojson_feature) # read the data intersecting a geojson feature
img = image.point(lon,lat) # get pixel values for a lon/lat coordinates
```
- Enable property assignment (e.g nodata) on data reading
```python
from rio_tiler.io import Reader
with Reader("my.tif") as image:
img = image.tile(x, y, z, nodata=-9999) # read mercator tile z-x-y
```
- [STAC](https://github.com/radiantearth/stac-spec) support
```python
from rio_tiler.io import STACReader
with STACReader("item.json") as stac:
print(stac.assets) # available asset
img = stac.tile( # read tile for asset1 and indexes 1,2,3
x,
y,
z,
assets="asset1",
indexes=(1, 2, 3), # same as asset_indexes={"asset1": (1, 2, 3)},
)
# Merging data from different assets
img = stac.tile( # create an image from assets 1,2,3 using their first band
x,
y,
z,
assets=("asset1", "asset2", "asset3",),
asset_indexes={"asset1": 1, "asset2": 1, "asset3": 1},
)
```
- [Xarray](https://xarray.dev) support **(>=4.0)**
```python
import xarray
from rio_tiler.io import XarrayReader
ds = xarray.open_dataset(
"https://pangeo.blob.core.windows.net/pangeo-public/daymet-rio-tiler/na-wgs84.zarr/",
engine="zarr",
decode_coords="all",
consolidated=True,
)
da = ds["tmax"]
with XarrayReader(da) as dst:
print(dst.info())
img = dst.tile(1, 1, 2)
```
*Note: The XarrayReader needs optional dependencies to be installed `pip install rio-tiler["xarray"]`.*
- Non-Geo Image support **(>=4.0)**
```python
from rio_tiler.io import ImageReader
with ImageReader("image.jpeg") as src:
im = src.tile(0, 0, src.maxzoom) # read top-left `tile`
im = src.part((0, 100, 100, 0)) # read top-left 100x100 pixels
pt = src.point(0, 0) # read pixel value
```
*Note: `ImageReader` is also compatible with proper geo-referenced raster datasets.*
- [Mosaic](https://cogeotiff.github.io/rio-tiler/mosaic/) (merging or stacking)
```python
from rio_tiler.io import Reader
from rio_tiler.mosaic import mosaic_reader
def reader(file, x, y, z, **kwargs):
with Reader(file) as image:
return image.tile(x, y, z, **kwargs)
img, assets = mosaic_reader(["image1.tif", "image2.tif"], reader, x, y, z)
```
- Native support for multiple TileMatrixSet via [morecantile](https://developmentseed.org/morecantile/)
```python
import morecantile
from rio_tiler.io import Reader
# Use EPSG:4326 (WGS84) grid
wgs84_grid = morecantile.tms.get("WorldCRS84Quad")
with Reader("my.tif", tms=wgs84_grid) as src:
img = src.tile(1, 1, 1)
```
## Install
You can install `rio-tiler` using pip
```bash
$ pip install -U pip
$ pip install -U rio-tiler
```
or install from source:
```bash
$ git clone https://github.com/cogeotiff/rio-tiler.git
$ cd rio-tiler
$ pip install -U pip
$ pip install -e .
```
## Plugins
#### [**rio-tiler-pds**][rio-tiler-pds]
[rio-tiler-pds]: https://github.com/cogeotiff/rio-tiler-pds
`rio-tiler` v1 included several helpers for reading popular public datasets (e.g. Sentinel 2, Sentinel 1, Landsat 8, CBERS) from cloud providers. This functionality is now in a [separate plugin][rio-tiler-pds], enabling easier access to more public datasets.
#### [**rio-tiler-mvt**][rio-tiler-mvt]
Create Mapbox Vector Tiles from raster sources
[rio-tiler-mvt]: https://github.com/cogeotiff/rio-tiler-mvt
## Implementations
[**titiler**][titiler]: A lightweight Cloud Optimized GeoTIFF dynamic tile server.
[**cogeo-mosaic**][cogeo-mosaic]: Create mosaics of Cloud Optimized GeoTIFF based on the [mosaicJSON][mosaicjson_spec] specification.
[titiler]: https://github.com/developmentseed/titiler
[cogeo-mosaic]: https://github.com/developmentseed/cogeo-mosaic
[mosaicjson_spec]: https://github.com/developmentseed/mosaicjson-spec
## Contribution & Development
See [CONTRIBUTING.md](https://github.com/cogeotiff/rio-tiler/blob/main/CONTRIBUTING.md)
## Authors
The `rio-tiler` project was begun at Mapbox and was transferred to the `cogeotiff` Github organization in January 2019.
See [AUTHORS.txt](https://github.com/cogeotiff/rio-tiler/blob/main/AUTHORS.txt) for a listing of individual contributors.
## Changes
See [CHANGES.md](https://github.com/cogeotiff/rio-tiler/blob/main/CHANGES.md).
## License
See [LICENSE](https://github.com/cogeotiff/rio-tiler/blob/main/LICENSE)
Raw data
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"description": "# rio-tiler\n\n<p align=\"center\">\n <img src=\"https://user-images.githubusercontent.com/10407788/88133997-77560f00-cbb1-11ea-874c-a8f1d123a9df.jpg\" style=\"max-width: 800px;\" alt=\"rio-tiler\"></a>\n</p>\n<p align=\"center\">\n <em>User friendly Rasterio plugin to read raster datasets.</em>\n</p>\n<p align=\"center\">\n <a href=\"https://github.com/cogeotiff/rio-tiler/actions?query=workflow%3ACI\" target=\"_blank\">\n <img src=\"https://github.com/cogeotiff/rio-tiler/workflows/CI/badge.svg\" alt=\"Test\">\n </a>\n <a href=\"https://codecov.io/gh/cogeotiff/rio-tiler\" target=\"_blank\">\n <img src=\"https://codecov.io/gh/cogeotiff/rio-tiler/branch/main/graph/badge.svg\" alt=\"Coverage\">\n </a>\n <a href=\"https://pypi.org/project/rio-tiler\" target=\"_blank\">\n <img src=\"https://img.shields.io/pypi/v/rio-tiler?color=%2334D058&label=pypi%20package\" alt=\"Package version\">\n </a>\n <a href=\"https://anaconda.org/conda-forge/rio-tiler\" target=\"_blank\">\n <img src=\"https://img.shields.io/conda/v/conda-forge/rio-tiler.svg\" alt=\"Conda Forge\">\n </a>\n <a href=\"https://pypistats.org/packages/rio-tiler\" target=\"_blank\">\n <img src=\"https://img.shields.io/pypi/dm/rio-tiler.svg\" alt=\"Downloads\">\n </a>\n <a href=\"https://github.com/cogeotiff/rio-tiler/blob/main/LICENSE\" target=\"_blank\">\n <img src=\"https://img.shields.io/github/license/cogeotiff/rio-tiler.svg\" alt=\"Downloads\">\n </a>\n <a href=\"https://mybinder.org/v2/gh/cogeotiff/rio-tiler/main?filepath=docs%2Fexamples%2F\" target=\"_blank\" alt=\"Binder\">\n <img src=\"https://mybinder.org/badge_logo.svg\" alt=\"Binder\">\n </a>\n</p>\n\n---\n\n**Documentation**: <a href=\"https://cogeotiff.github.io/rio-tiler/\" target=\"_blank\">https://cogeotiff.github.io/rio-tiler/</a>\n\n**Source Code**: <a href=\"https://github.com/cogeotiff/rio-tiler\" target=\"_blank\">https://github.com/cogeotiff/rio-tiler</a>\n\n---\n\n## Description\n\n`rio-tiler` was initially designed to create [slippy map\ntiles](https://en.wikipedia.org/wiki/Tiled_web_map) from large raster data\nsources and render these tiles dynamically on a web map. Since `rio-tiler` v2.0, we added many more helper methods to read\ndata and metadata from any raster source supported by Rasterio/GDAL.\nThis includes local and remote files via HTTP, AWS S3, Google Cloud Storage,\netc.\n\nAt the low level, `rio-tiler` is *just* a wrapper around the [rasterio](https://github.com/rasterio/rasterio) and [GDAL](https://github.com/osgeo/gdal) libraries.\n\n## Features\n\n- Read any dataset supported by GDAL/Rasterio\n\n ```python\n from rio_tiler.io import Reader\n\n with Reader(\"my.tif\") as image:\n print(image.dataset) # rasterio opened dataset\n img = image.read() # similar to rasterio.open(\"my.tif\").read() but returns a rio_tiler.models.ImageData object\n ```\n\n- User friendly `tile`, `part`, `feature`, `point` reading methods\n\n ```python\n from rio_tiler.io import Reader\n\n with Reader(\"my.tif\") as image:\n img = image.tile(x, y, z) # read mercator tile z-x-y\n img = image.part(bbox) # read the data intersecting a bounding box\n img = image.feature(geojson_feature) # read the data intersecting a geojson feature\n img = image.point(lon,lat) # get pixel values for a lon/lat coordinates\n ```\n\n- Enable property assignment (e.g nodata) on data reading\n\n ```python\n from rio_tiler.io import Reader\n\n with Reader(\"my.tif\") as image:\n img = image.tile(x, y, z, nodata=-9999) # read mercator tile z-x-y\n ```\n\n- [STAC](https://github.com/radiantearth/stac-spec) support\n\n ```python\n from rio_tiler.io import STACReader\n\n with STACReader(\"item.json\") as stac:\n print(stac.assets) # available asset\n img = stac.tile( # read tile for asset1 and indexes 1,2,3\n x,\n y,\n z,\n assets=\"asset1\",\n indexes=(1, 2, 3), # same as asset_indexes={\"asset1\": (1, 2, 3)},\n )\n\n # Merging data from different assets\n img = stac.tile( # create an image from assets 1,2,3 using their first band\n x,\n y,\n z,\n assets=(\"asset1\", \"asset2\", \"asset3\",),\n asset_indexes={\"asset1\": 1, \"asset2\": 1, \"asset3\": 1},\n )\n ```\n\n- [Xarray](https://xarray.dev) support **(>=4.0)**\n\n ```python\n import xarray\n from rio_tiler.io import XarrayReader\n\n ds = xarray.open_dataset(\n \"https://pangeo.blob.core.windows.net/pangeo-public/daymet-rio-tiler/na-wgs84.zarr/\",\n engine=\"zarr\",\n decode_coords=\"all\",\n consolidated=True,\n )\n da = ds[\"tmax\"]\n with XarrayReader(da) as dst:\n print(dst.info())\n img = dst.tile(1, 1, 2)\n ```\n *Note: The XarrayReader needs optional dependencies to be installed `pip install rio-tiler[\"xarray\"]`.*\n\n- Non-Geo Image support **(>=4.0)**\n\n ```python\n from rio_tiler.io import ImageReader\n\n with ImageReader(\"image.jpeg\") as src:\n im = src.tile(0, 0, src.maxzoom) # read top-left `tile`\n im = src.part((0, 100, 100, 0)) # read top-left 100x100 pixels\n pt = src.point(0, 0) # read pixel value\n ```\n\n *Note: `ImageReader` is also compatible with proper geo-referenced raster datasets.*\n\n- [Mosaic](https://cogeotiff.github.io/rio-tiler/mosaic/) (merging or stacking)\n\n ```python\n from rio_tiler.io import Reader\n from rio_tiler.mosaic import mosaic_reader\n\n def reader(file, x, y, z, **kwargs):\n with Reader(file) as image:\n return image.tile(x, y, z, **kwargs)\n\n img, assets = mosaic_reader([\"image1.tif\", \"image2.tif\"], reader, x, y, z)\n ```\n\n- Native support for multiple TileMatrixSet via [morecantile](https://developmentseed.org/morecantile/)\n\n ```python\n import morecantile\n from rio_tiler.io import Reader\n\n # Use EPSG:4326 (WGS84) grid\n wgs84_grid = morecantile.tms.get(\"WorldCRS84Quad\")\n with Reader(\"my.tif\", tms=wgs84_grid) as src:\n img = src.tile(1, 1, 1)\n ```\n\n## Install\n\nYou can install `rio-tiler` using pip\n\n```bash\n$ pip install -U pip\n$ pip install -U rio-tiler\n```\n\nor install from source:\n\n```bash\n$ git clone https://github.com/cogeotiff/rio-tiler.git\n$ cd rio-tiler\n$ pip install -U pip\n$ pip install -e .\n```\n\n## Plugins\n\n#### [**rio-tiler-pds**][rio-tiler-pds]\n\n[rio-tiler-pds]: https://github.com/cogeotiff/rio-tiler-pds\n\n`rio-tiler` v1 included several helpers for reading popular public datasets (e.g. Sentinel 2, Sentinel 1, Landsat 8, CBERS) from cloud providers. This functionality is now in a [separate plugin][rio-tiler-pds], enabling easier access to more public datasets.\n\n#### [**rio-tiler-mvt**][rio-tiler-mvt]\n\nCreate Mapbox Vector Tiles from raster sources\n\n[rio-tiler-mvt]: https://github.com/cogeotiff/rio-tiler-mvt\n\n## Implementations\n\n[**titiler**][titiler]: A lightweight Cloud Optimized GeoTIFF dynamic tile server.\n\n[**cogeo-mosaic**][cogeo-mosaic]: Create mosaics of Cloud Optimized GeoTIFF based on the [mosaicJSON][mosaicjson_spec] specification.\n\n[titiler]: https://github.com/developmentseed/titiler\n[cogeo-mosaic]: https://github.com/developmentseed/cogeo-mosaic\n[mosaicjson_spec]: https://github.com/developmentseed/mosaicjson-spec\n\n## Contribution & Development\n\nSee [CONTRIBUTING.md](https://github.com/cogeotiff/rio-tiler/blob/main/CONTRIBUTING.md)\n\n## Authors\n\nThe `rio-tiler` project was begun at Mapbox and was transferred to the `cogeotiff` Github organization in January 2019.\n\nSee [AUTHORS.txt](https://github.com/cogeotiff/rio-tiler/blob/main/AUTHORS.txt) for a listing of individual contributors.\n\n## Changes\n\nSee [CHANGES.md](https://github.com/cogeotiff/rio-tiler/blob/main/CHANGES.md).\n\n## License\n\nSee [LICENSE](https://github.com/cogeotiff/rio-tiler/blob/main/LICENSE)\n",
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