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working_directory: ~/rio-tiler-pds + steps: + - checkout + - run: + name: install dependencies + command: pip install tox codecov pre-commit --user + - run: + name: run tox + command: ~/.local/bin/tox + - run: + name: run pre-commit + command: | + if [[ "$CIRCLE_JOB" == "python-3.7" ]]; then + ~/.local/bin/pre-commit run --all-files + fi + - run: + name: upload coverage report + command: | + if [[ "$UPLOAD_COVERAGE" == 1 ]]; then + ~/.local/bin/coverage xml + ~/.local/bin/codecov + fi + when: always + +jobs: + "python-3.6": + <<: *common + docker: + - image: circleci/python:3.6.5 + environment: + - TOXENV=py36 + - UPLOAD_COVERAGE=1 + + "python-3.7": + <<: *common + docker: + - image: circleci/python:3.7.2 + environment: + - TOXENV=py37 + + deploy: + docker: + - image: circleci/python:3.7.2 + environment: + - TOXENV=release + working_directory: ~/rio-tiler-pds + steps: + - checkout + - run: + command: pip install -e . --user + - run: + name: verify git tag vs. version + command: | + VERSION=$(python -c 'import rio_tiler_pds; print(rio_tiler_pds.version)') + if [ "$VERSION" = "$CIRCLE_TAG" ]; then exit 0; else exit 3; fi + - run: + name: install dependencies + command: pip install tox --user + - run: + name: init .pypirc + command: | + echo -e "[pypi]" >> ~/.pypirc + echo -e "username = $PYPI_USER" >> ~/.pypirc + echo -e "password = $PYPI_PASSWORD" >> ~/.pypirc + - run: + name: run tox + command: ~/.local/bin/tox + +workflows: + version: 2 + build_and_deploy: + jobs: + - "python-3.6" + - "python-3.7": + filters: # required since `deploy` has tag filters AND requires `build` + tags: + only: /.*/ + - deploy: + requires: + - "python-3.7" + filters: + tags: + only: /^[0-9]+.*/ + branches: + ignore: /.*/ diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..085ebce --- /dev/null +++ b/.gitignore @@ -0,0 +1,108 @@ +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class + +# C extensions +*.so + +# Distribution / packaging +.Python +env/ +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +*.egg-info/ +.installed.cfg +*.egg + +# PyInstaller +# Usually these files are written by a python script from a template +# before PyInstaller builds the exe, so as to inject date/other infos into it. +*.manifest +*.spec + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*.cover +.hypothesis/ + +# Translations +*.mo +*.pot + +# Django stuff: +*.log +local_settings.py + +# Flask stuff: +instance/ +.webassets-cache + +# Scrapy stuff: +.scrapy + +# Sphinx documentation +docs/_build/ + +# PyBuilder +target/ + +# Jupyter Notebook +.ipynb_checkpoints + +# pyenv +.python-version + +# celery beat schedule file +celerybeat-schedule + +# SageMath parsed files +*.sage.py + +# dotenv +.env + +# virtualenv +.venv +venv/ +ENV/ + +# Spyder project settings +.spyderproject +.spyproject + +# Rope project settings +.ropeproject + +# mkdocs documentation +/site + +# mypy +.mypy_cache/ + + +.pytest_cache + +.benchmarks/ +tests/benchmarks/data/* +tests/fixtures/mask* diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml new file mode 100644 index 0000000..cc13e4a --- /dev/null +++ b/.pre-commit-config.yaml @@ -0,0 +1,44 @@ +repos: + - + repo: https://github.com/pre-commit/mirrors-isort + rev: v4.3.21 + hooks: + - id: isort + language_version: python3.7 + - + repo: 'https://github.com/psf/black' + rev: stable + hooks: + - id: black + args: ['--safe'] + language_version: python3.7 + - + repo: 'https://github.com/pre-commit/pre-commit-hooks' + rev: v2.4.0 + hooks: + - id: flake8 + language_version: python3.7 + args: [ + # E501 let black handle all line length decisions + # W503 black conflicts with "line break before operator" rule + # E203 black conflicts with "whitespace before ':'" rule + '--ignore=E501,W503,E203'] + - + repo: 'https://github.com/chewse/pre-commit-mirrors-pydocstyle' + # 2.1.1 + rev: 22d3ccf6cf91ffce3b16caa946c155778f0cb20f + hooks: + - id: pydocstyle + language_version: python3.7 + args: [ + # Check for docstring presence only + '--select=D1', + # Don't require docstrings for tests + '--match=(?!test).*\.py'] + + - + repo: https://github.com/pre-commit/mirrors-mypy + rev: 'v0.770' + hooks: + - id: mypy + args: [--no-strict-optional, --ignore-missing-imports] \ No newline at end of file diff --git a/AUTHORS.txt b/AUTHORS.txt new file mode 100644 index 0000000..d4fa413 --- /dev/null +++ b/AUTHORS.txt @@ -0,0 +1,7 @@ +Authors +------- + +* Vincent Sarago +* Sean Gillies + +See also https://github.com/cogeotiff/rio-tiler-pds/graphs/contributors. diff --git a/CHANGES.txt b/CHANGES.txt new file mode 100644 index 0000000..3536781 --- /dev/null +++ b/CHANGES.txt @@ -0,0 +1,4 @@ +0.0.1(TBD) +------------------ + +- Initial release. diff --git a/LICENSE.txt b/LICENSE.txt new file mode 100644 index 0000000..6f6c8d0 --- /dev/null +++ b/LICENSE.txt @@ -0,0 +1,29 @@ +BSD 3-Clause License + +Copyright (c) 2017, Mapbox +All rights reserved. + +Redistribution and use in source and binary forms, with or without +modification, are permitted provided that the following conditions are met: + +* Redistributions of source code must retain the above copyright notice, this + list of conditions and the following disclaimer. + +* 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. + +* 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. diff --git a/README.md b/README.md new file mode 100644 index 0000000..10cf3d2 --- /dev/null +++ b/README.md @@ -0,0 +1,151 @@ +# Rio-tiler-pds + +Rio-tiler plugin to read mercator tiles from Public datasets. + +[![Packaging status](https://badge.fury.io/py/rio-tiler-pds.svg)](https://badge.fury.io/py/rio-tiler-pds) +[![CircleCI](https://circleci.com/gh/cogeotiff/rio-tiler-pds.svg?style=svg)](https://circleci.com/gh/cogeotiff/rio-tiler-pds) +[![codecov](https://codecov.io/gh/cogeotiff/rio-tiler-pds/branch/master/graph/badge.svg)](https://codecov.io/gh/cogeotiff/rio-tiler-pds) + +Additional support is provided for the following satellite missions hosted on **AWS Public Dataset**: + +- [Sentinel2](https://registry.opendata.aws/sentinel-2/) (**requester-pays**) (please read [this](https://github.com/cogeotiff/rio-tiler#Partial-reading-on-Cloud-hosted-dataset)) +- [Sentinel1](https://registry.opendata.aws/sentinel-1/) (**requester-pays**) +- [Landsat8](https://aws.amazon.com/fr/public-datasets/landsat) +- [CBERS](https://registry.opendata.aws/cbers/) (**requester-pays**) + +## Install + +You can install rio-tiler-pds using pip + +```bash +$ pip install -U pip +$ pip install rio-tiler-pds +``` + +or install from source: + +```bash +$ git clone https://github.com/cogeotiff/rio-tiler-pds.git +$ cd rio-tiler-pds +$ pip install -U pip +$ pip install -e . +``` + +## Overview + +Create tiles using one of these rio_tiler submodules: `sentinel2`, `sentinel1`, `landsat8`, `cbers`. + +The mission specific modules make it easier to extract tiles from AWS S3 buckets (i.e. only a scene ID is required); They can also be used to return metadata. + +Each tilling modules have a method to return image metadata (e.g bounds). + +## Usage + +#### Read a tile from a file over the internet + +#### Read Sentinel2 tile + +```python +from rio_tiler_pds sentinel2 + +tile, mask = sentinel2.tile('S2A_L1C_20170729_19UDP_0', 77, 89, 8) +print(tile.shape) +> (3, 256, 256) +``` + +#### Use Landsat submodule + +```python +from rio_tiler_pds import landsat8 + +landsat8.bounds('LC08_L1TP_016037_20170813_20170814_01_RT') +> {'bounds': [-81.30836, 32.10539, -78.82045, 34.22818], +> 'sceneid': 'LC08_L1TP_016037_20170813_20170814_01_RT'} +``` + +Get metadata of a Landsat scene (i.e. percentiles (pc) min/max values, histograms, and bounds in WGS84) . + +```python +from rio_tiler_pds import landsat8 + +landsat8.metadata('LC08_L1TP_016037_20170813_20170814_01_RT', pmin=5, pmax=95) +{ + 'sceneid': 'LC08_L1TP_016037_20170813_20170814_01_RT', + 'bounds':(-81.30844102941015, 32.105321365706104, -78.82036599673634, 34.22863519772504), + 'statistics': { + '1': { + 'pc': [1251.297607421875, 5142.0126953125], + 'min': -1114.7020263671875, + 'max': 11930.634765625, + 'std': 1346.6463388957156, + 'histogram': [ + [1716, 257951, 174296, 36184, 20828, 11783, 6862, 2941, 635, 99], + [-1114.7020263671875, 189.83164978027344, 1494.3653564453125, 2798.89892578125, 4103.4326171875, 5407.96630859375, 6712.5, 8017.03369140625, 9321.5673828125, 10626.1015625, 11930.634765625] + ] + }, + ... + ... + '11': { + 'pc': [278.3393859863281, 293.4466247558594], + 'min': 147.27650451660156, + 'max': 297.4621276855469, + 'std': 7.660112832018338, + 'histogram': [ + [207, 201, 204, 271, 350, 944, 1268, 2383, 43085, 453084], + [147.27650451660156, 162.29507446289062, 177.31362915039062, 192.33218383789062, 207.3507537841797, 222.36932373046875, 237.38787841796875, 252.40643310546875, 267.42498779296875, 282.4435729980469, 297.4621276855469] + ] + } + } +} +``` + +The primary purpose for calculating minimum and maximum values of an image is to rescale pixel values from their original range (e.g. 0 to 65,535) to the range used by computer screens (i.e. 0 and 255) through a linear transformation. +This will make images look good on display. + +## Requester-pays Buckets + +On AWS, `sentinel2`, `sentinel1`, and `cbers` dataset are stored in a `requester-pays` bucket, meaning the cost of GET, LIST requests will be charged to the users. For rio-tiler to work with those buckets, you'll need to set `AWS_REQUEST_PAYER="requester"` in your environement. + +## Partial reading on Cloud hosted dataset + +Rio-tiler perform partial reading on local or distant dataset, which is why it will perform best on Cloud Optimized GeoTIFF (COG). +It's important to note that **Sentinel-2 scenes hosted on AWS are not in Cloud Optimized format but in JPEG2000**. +When performing partial reading of JPEG2000 dataset GDAL (rasterio backend library) will need to make a lot of **GET requests** and transfer a lot of data. + +Ref: [Do you really want people using your data](https://medium.com/@_VincentS_/do-you-really-want-people-using-your-data-ec94cd94dc3f) blog post. + + +## Contribution & Development + +Issues and pull requests are more than welcome. + +**dev install** + +```bash +$ git clone https://github.com/cogeotiff/rio-tiler-pds.git +$ cd rio-tiler-pds +$ pip install -e .[dev] +``` + +**Python3.7 only** + +This repo is set to use `pre-commit` to run *isort*, *flake8*, *pydocstring*, *black* ("uncompromising Python code formatter") and mypy when committing new code. + +```bash +$ pre-commit install +``` + +## License + +See [LICENSE.txt](https://github.com/cogeotiff/rio-tiler-pds/blob/master/LICENSE.txt) + +## Authors + +The rio-tiler project was begun at Mapbox and has been transferred in January 2019. + +See [AUTHORS.txt](https://github.com/cogeotiff/rio-tiler-pds/blob/master/AUTHORS.txt) for a listing of individual contributors. + +## Changes + +See [CHANGES.txt](https://github.com/cogeotiff/rio-tiler-pds/blob/master/CHANGES.txt). + diff --git a/codecov.yml b/codecov.yml new file mode 100644 index 0000000..c61977e --- /dev/null +++ b/codecov.yml @@ -0,0 +1,8 @@ +comment: off + +coverage: + status: + project: + default: + target: auto + threshold: 5 diff --git a/requirements.txt b/requirements.txt new file mode 100644 index 0000000..8d123ae --- /dev/null +++ b/requirements.txt @@ -0,0 +1,3 @@ + +rio-tiler~=2.0b1 +rio-toa diff --git a/rio_tiler_pds/__init__.py b/rio_tiler_pds/__init__.py new file mode 100644 index 0000000..d3ae2b0 --- /dev/null +++ b/rio_tiler_pds/__init__.py @@ -0,0 +1,5 @@ +"""rio-tiler-pds.""" + +import pkg_resources + +version = pkg_resources.get_distribution(__package__).version diff --git a/rio_tiler_pds/cbers.py b/rio_tiler_pds/cbers.py new file mode 100644 index 0000000..2b1a45c --- /dev/null +++ b/rio_tiler_pds/cbers.py @@ -0,0 +1,236 @@ +"""rio_tiler.cbers: cbers processing.""" + +import re +from typing import Any, Dict, Sequence, Tuple, Union + +import numpy +import rasterio +from rasterio.warp import transform_bounds + +from rio_tiler import constants, reader +from rio_tiler.errors import InvalidBandName, InvalidCBERSSceneId, TileOutsideBounds +from rio_tiler.utils import tile_exists + + +def cbers_parser(sceneid: str) -> Dict: + """Parse CBERS scene id. + + Attributes + ---------- + sceneid : str + CBERS sceneid. + + Returns + ------- + out : dict + dictionary with metadata constructed from the sceneid. + + """ + if not re.match(r"^CBERS_4_\w+_[0-9]{8}_[0-9]{3}_[0-9]{3}_L[0-9]$", sceneid): + raise InvalidCBERSSceneId("Could not match {}".format(sceneid)) + + cbers_pattern = ( + r"(?P\w+)_" + r"(?P[0-9]{1})" + r"_" + r"(?P\w+)" + r"_" + r"(?P[0-9]{4})" + r"(?P[0-9]{2})" + r"(?P[0-9]{2})" + r"_" + r"(?P[0-9]{3})" + r"_" + r"(?P[0-9]{3})" + r"_" + r"(?PL[0-9]{1})$" + ) + + meta: Dict[str, Any] = re.match(cbers_pattern, sceneid, re.IGNORECASE).groupdict() + meta["scene"] = sceneid + + instrument = meta["instrument"] + instrument_params = { + "MUX": { + "reference_band": "6", + "bands": ("5", "6", "7", "8"), + "rgb": ("7", "6", "5"), + }, + "AWFI": { + "reference_band": "14", + "bands": ("13", "14", "15", "16"), + "rgb": ("15", "14", "13"), + }, + "PAN10M": { + "reference_band": "4", + "bands": ("2", "3", "4"), + "rgb": ("3", "4", "2"), + }, + "PAN5M": {"reference_band": "1", "bands": ("1"), "rgb": ("1", "1", "1")}, + } + meta["reference_band"] = instrument_params[instrument]["reference_band"] + meta["bands"] = instrument_params[instrument]["bands"] + meta["rgb"] = instrument_params[instrument]["rgb"] + + meta["scheme"] = "s3" + meta["bucket"] = "cbers-pds" + meta["prefix"] = "CBERS4/{instrument}/{path}/{row}/{scene}".format(**meta) + + return meta + + +def bounds(sceneid: str) -> Dict: + """ + Retrieve image bounds. + + Attributes + ---------- + sceneid : str + CBERS sceneid. + + Returns + ------- + out : dict + dictionary with image bounds. + + """ + scene_params = cbers_parser(sceneid) + cbers_prefix = "{scheme}://{bucket}/{prefix}/{scene}".format(**scene_params) + + with rasterio.open( + "{}_BAND{}.tif".format(cbers_prefix, scene_params["reference_band"]) + ) as src: + bounds = transform_bounds( + src.crs, constants.WGS84_CRS, *src.bounds, densify_pts=21 + ) + + return dict(sceneid=sceneid, bounds=bounds) + + +def metadata( + sceneid: str, + pmin: float = 2.0, + pmax: float = 98.0, + hist_options: Dict = {}, + **kwargs: Any, +) -> Dict: + """ + Return band bounds and statistics. + + Attributes + ---------- + sceneid : str + CBERS sceneid. + pmin : int, optional, (default: 2) + Histogram minimum cut. + pmax : int, optional, (default: 98) + Histogram maximum cut. + hist_options : dict, optional + Options to forward to numpy.histogram function. + e.g: {bins=20, range=(0, 1000)} + kwargs : optional + These are passed to 'rio_tiler.reader.preview' + + Returns + ------- + out : dict + Dictionary with bounds and bands statistics. + + """ + scene_params = cbers_parser(sceneid) + cbers_prefix = "{scheme}://{bucket}/{prefix}/{scene}".format(**scene_params) + + bands = scene_params["bands"] + addresses = [f"{cbers_prefix}_BAND{band}.tif" for band in bands] + + responses = reader.multi_metadata( + addresses, + indexes=[1], + nodata=0, + percentiles=(pmin, pmax), + hist_options=hist_options, + **kwargs, + ) + + info: Dict[str, Any] = dict(sceneid=sceneid) + info["instrument"] = scene_params["instrument"] + info["band_descriptions"] = [(ix + 1, b) for ix, b in enumerate(bands)] + + info["bounds"] = [ + r["bounds"] + for b, r in zip(bands, responses) + if b == scene_params["reference_band"] + ][0] + info["statistics"] = {b: d["statistics"][1] for b, d in zip(bands, responses)} + return info + + +def tile( + sceneid: str, + tile_x: int, + tile_y: int, + tile_z: int, + bands: Union[Sequence[str], str] = None, + tilesize: int = 256, + **kwargs: Dict, +) -> Tuple[numpy.ndarray, numpy.ndarray]: + """ + Create mercator tile from CBERS data. + + Attributes + ---------- + sceneid : str + CBERS sceneid. + tile_x : int + Mercator tile X index. + tile_y : int + Mercator tile Y index. + tile_z : int + Mercator tile ZOOM level. + bands : tuple or list or str, optional + Bands index for the RGB combination. If None uses default + defined for the instrument + tilesize : int, optional + Output image size. Default is 256 + kwargs: dict, optional + These will be passed to the 'rio_tiler.reader.tile' function. + + Returns + ------- + data : numpy ndarray + mask: numpy array + + """ + if isinstance(bands, str): + bands = (bands,) + + scene_params = cbers_parser(sceneid) + + if not bands: + bands = scene_params["rgb"] + + for band in bands: + if band not in scene_params["bands"]: + raise InvalidBandName( + "{} is not a valid band name for {} CBERS instrument".format( + band, scene_params["instrument"] + ) + ) + + cbers_prefix = "{scheme}://{bucket}/{prefix}/{scene}".format(**scene_params) + with rasterio.open( + "{}_BAND{}.tif".format(cbers_prefix, scene_params["reference_band"]) + ) as src_dst: + bounds = transform_bounds( + src_dst.crs, constants.WGS84_CRS, *src_dst.bounds, densify_pts=21 + ) + + if not tile_exists(bounds, tile_z, tile_x, tile_y): + raise TileOutsideBounds( + "Tile {}/{}/{} is outside image bounds".format(tile_z, tile_x, tile_y) + ) + + addresses = [f"{cbers_prefix}_BAND{band}.tif" for band in bands] + return reader.multi_tile( + addresses, tile_x, tile_y, tile_z, tilesize=tilesize, nodata=0 + ) diff --git a/rio_tiler_pds/landsat8.py b/rio_tiler_pds/landsat8.py new file mode 100644 index 0000000..eaa6f17 --- /dev/null +++ b/rio_tiler_pds/landsat8.py @@ -0,0 +1,357 @@ +"""rio_tiler.io.landsat8: Landsat-8 processing.""" + +import datetime +import os +import re +from concurrent import futures +from typing import Any, Dict, Sequence, Tuple, Union +from urllib.request import urlopen + +import numpy +import rasterio +from rasterio.warp import transform_bounds +from rio_toa import brightness_temp, reflectance, toa_utils + +from rio_tiler import constants, reader +from rio_tiler.errors import InvalidBandName, InvalidLandsatSceneId, TileOutsideBounds +from rio_tiler.utils import _stats as raster_stats +from rio_tiler.utils import pansharpening_brovey, tile_exists + +LANDSAT_BANDS = ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "QA"] + + +def landsat_parser(sceneid: str) -> Dict: + """ + Parse Landsat-8 scene id. + + Author @perrygeo - http://www.perrygeo.com + + Attributes + ---------- + sceneid : str + Landsat sceneid. + + Returns + ------- + out : dict + dictionary with metadata constructed from the sceneid. + + """ + pre_collection = r"(L[COTEM]8\d{6}\d{7}[A-Z]{3}\d{2})" + collection_1 = r"(L[COTEM]08_L\d{1}[A-Z]{2}_\d{6}_\d{8}_\d{8}_\d{2}_(T1|T2|RT))" + if not re.match("^{}|{}$".format(pre_collection, collection_1), sceneid): + raise InvalidLandsatSceneId("Could not match {}".format(sceneid)) + + precollection_pattern = ( + r"^L" + r"(?P\w{1})" + r"(?P\w{1})" + r"(?P[0-9]{3})" + r"(?P[0-9]{3})" + r"(?P[0-9]{4})" + r"(?P[0-9]{3})" + r"(?P\w{3})" + r"(?P[0-9]{2})$" + ) + + collection_pattern = ( + r"^L" + r"(?P\w{1})" + r"(?P\w{2})" + r"_" + r"(?P\w{4})" + r"_" + r"(?P[0-9]{3})" + r"(?P[0-9]{3})" + r"_" + r"(?P[0-9]{4})" + r"(?P[0-9]{2})" + r"(?P[0-9]{2})" + r"_" + r"(?P[0-9]{4})" + r"(?P[0-9]{2})" + r"(?P[0-9]{2})" + r"_" + r"(?P\w{2})" + r"_" + r"(?P\w{2})$" + ) + + for pattern in [collection_pattern, precollection_pattern]: + match = re.match(pattern, sceneid, re.IGNORECASE) + if match: + meta: Dict[str, Any] = match.groupdict() + break + + meta["scene"] = sceneid + if meta.get("acquisitionJulianDay"): + date = datetime.datetime( + int(meta["acquisitionYear"]), 1, 1 + ) + datetime.timedelta(int(meta["acquisitionJulianDay"]) - 1) + + meta["date"] = date.strftime("%Y-%m-%d") + else: + meta["date"] = "{}-{}-{}".format( + meta["acquisitionYear"], meta["acquisitionMonth"], meta["acquisitionDay"] + ) + + collection = meta.get("collectionNumber", "") + if collection != "": + collection = "c{}".format(int(collection)) + + meta["scheme"] = "s3" + meta["bucket"] = "landsat-pds" + meta["prefix"] = os.path.join(collection, "L8", meta["path"], meta["row"], sceneid) + + return meta + + +def _landsat_get_mtl(sceneid: str) -> Dict: + """ + Get Landsat-8 MTL metadata. + + Attributes + ---------- + sceneid : str + Landsat sceneid. For scenes after May 2017, + sceneid have to be LANDSAT_PRODUCT_ID. + + Returns + ------- + out : dict + returns a JSON like object with the metadata. + + """ + scene_params = landsat_parser(sceneid) + meta_file = "http://{bucket}.s3.amazonaws.com/{prefix}/{scene}_MTL.txt".format( + **scene_params + ) + metadata = str(urlopen(meta_file).read().decode()) + return toa_utils._parse_mtl_txt(metadata) + + +def _convert(arr: numpy.ndarray, band: str, metadata: Dict) -> numpy.ndarray: + """Convert DN to TOA or Temp.""" + if band in ["1", "2", "3", "4", "5", "6", "7", "8", "9"]: # OLI + multi_reflect = metadata["RADIOMETRIC_RESCALING"].get( + f"REFLECTANCE_MULT_BAND_{band}" + ) + add_reflect = metadata["RADIOMETRIC_RESCALING"].get( + f"REFLECTANCE_ADD_BAND_{band}" + ) + sun_elev = metadata["IMAGE_ATTRIBUTES"]["SUN_ELEVATION"] + + arr = 10000 * reflectance.reflectance( + arr, multi_reflect, add_reflect, sun_elev, src_nodata=0 + ) + + elif band in ["10", "11"]: # TIRS + multi_rad = metadata["RADIOMETRIC_RESCALING"].get(f"RADIANCE_MULT_BAND_{band}") + add_rad = metadata["RADIOMETRIC_RESCALING"].get(f"RADIANCE_ADD_BAND_{band}") + k1 = metadata["TIRS_THERMAL_CONSTANTS"].get(f"K1_CONSTANT_BAND_{band}") + k2 = metadata["TIRS_THERMAL_CONSTANTS"].get(f"K2_CONSTANT_BAND_{band}") + + arr = brightness_temp.brightness_temp(arr, multi_rad, add_rad, k1, k2) + + # TODO + # elif band == "QA": + + return arr + + +def bounds(sceneid: str) -> Dict: + """ + Retrieve image bounds. + + Attributes + ---------- + sceneid : str + Landsat sceneid. For scenes after May 2017, + sceneid have to be LANDSAT_PRODUCT_ID. + + Returns + ------- + out : dict + dictionary with image bounds. + + """ + meta: Dict = _landsat_get_mtl(sceneid)["L1_METADATA_FILE"] + + return dict( + sceneid=sceneid, + bounds=toa_utils._get_bounds_from_metadata(meta["PRODUCT_METADATA"]), + ) + + +def metadata( + sceneid: str, + pmin: float = 2.0, + pmax: float = 98.0, + hist_options: Dict = {}, + **kwargs: Any, +) -> Dict: + """ + Retrieve image bounds and band statistics. + + Attributes + ---------- + sceneid : str + Landsat sceneid. For scenes after May 2017, + sceneid have to be LANDSAT_PRODUCT_ID. + pmin : int, optional, (default: 2) + Histogram minimum cut. + pmax : int, optional, (default: 98) + Histogram maximum cut. + hist_options : dict, optional + Options to forward to numpy.histogram function. + e.g: {bins=20, range=(0, 1000)} + kwargs : optional + These are passed to 'rio_tiler.reader.preview' + + Returns + ------- + out : dict + Dictionary with bounds and bands statistics. + + """ + scene_params = landsat_parser(sceneid) + meta: Dict = _landsat_get_mtl(sceneid)["L1_METADATA_FILE"] + + landsat_prefix = "{scheme}://{bucket}/{prefix}/{scene}".format(**scene_params) + + def worker(band: str): + asset = f"{landsat_prefix}_B{band}.TIF" + + if band == "QA": + nodata = 1 + resamp = "nearest" + else: + nodata = 0 + resamp = "bilinear" + + with rasterio.open(asset) as src_dst: + bounds = transform_bounds( + src_dst.crs, constants.WGS84_CRS, *src_dst.bounds, densify_pts=21 + ) + data, mask = reader.preview( + src_dst, nodata=nodata, resampling_method=resamp, **kwargs + ) + + if band != "QA": + data = data.astype("float32", casting="unsafe") + data = _convert(data, band, meta) + + data = numpy.ma.array(data) + data.mask = mask == 0 + + statistics = raster_stats(data, percentiles=(pmin, pmax), **hist_options) + return dict(bounds=bounds, statistics=statistics) + + with futures.ThreadPoolExecutor(max_workers=constants.MAX_THREADS) as executor: + responses = list(executor.map(worker, LANDSAT_BANDS)) + + info: Dict[str, Any] = dict(sceneid=sceneid) + info["band_descriptions"] = [(ix + 1, b) for ix, b in enumerate(LANDSAT_BANDS)] + info["bounds"] = [ + r["bounds"] for b, r in zip(LANDSAT_BANDS, responses) if b == "8" + ][0] + + info["statistics"] = {b: d["statistics"] for b, d in zip(LANDSAT_BANDS, responses)} + return info + + +def tile( + sceneid: str, + tile_x: int, + tile_y: int, + tile_z: int, + bands: Union[Sequence[str], str] = ["4", "3", "2"], + tilesize: int = 256, + pan: bool = False, + **kwargs: Any, +) -> Tuple[numpy.ndarray, numpy.ndarray]: + """ + Create mercator tile from Landsat-8 data. + + Attributes + ---------- + sceneid : str + Landsat sceneid. For scenes after May 2017, + sceneid have to be LANDSAT_PRODUCT_ID. + tile_x : int + Mercator tile X index. + tile_y : int + Mercator tile Y index. + tile_z : int + Mercator tile ZOOM level. + bands : tuple, str, optional (default: ("4", "3", "2")) + Bands index for the RGB combination. + tilesize : int, optional (default: 256) + Output image size. + pan : boolean, optional (default: False) + If True, apply pan-sharpening. + kwargs: dict, optional + These will be passed to the 'rio_tiler.utils._tile_read' function. + + Returns + ------- + data : numpy ndarray + mask: numpy array + + """ + if isinstance(bands, str): + bands = (bands,) + + for band in bands: + if band not in LANDSAT_BANDS: + raise InvalidBandName("{} is not a valid Landsat band name".format(band)) + + scene_params = landsat_parser(sceneid) + + meta: Dict = _landsat_get_mtl(sceneid)["L1_METADATA_FILE"] + + landsat_prefix = "{scheme}://{bucket}/{prefix}/{scene}".format(**scene_params) + + bounds = toa_utils._get_bounds_from_metadata(meta["PRODUCT_METADATA"]) + if not tile_exists(bounds, tile_z, tile_x, tile_y): + raise TileOutsideBounds( + "Tile {}/{}/{} is outside image bounds".format(tile_z, tile_x, tile_y) + ) + + def worker(band: str): + asset = f"{landsat_prefix}_B{band}.TIF" + + if band == "QA": + nodata = 1 + resamp = "nearest" + else: + nodata = 0 + resamp = "bilinear" + + with rasterio.open(asset) as src_dst: + tile, mask = reader.tile( + src_dst, + tile_x, + tile_y, + tile_z, + tilesize=tilesize, + nodata=nodata, + resampling_method=resamp, + ) + + return tile, mask + + with futures.ThreadPoolExecutor(max_workers=constants.MAX_THREADS) as executor: + data, masks = zip(*list(executor.map(worker, bands))) + data = numpy.concatenate(data) + mask = numpy.all(masks, axis=0).astype(numpy.uint8) * 255 + + if pan: + pan_data, mask = worker("8") + data = pansharpening_brovey(data, pan_data, 0.2, pan_data.dtype) + + if bands[0] != "QA" or len(bands) != 1: + for bdx, band in enumerate(bands): + data[bdx] = _convert(data[bdx], band, meta) + + return data, mask diff --git a/rio_tiler_pds/sentinel1.py b/rio_tiler_pds/sentinel1.py new file mode 100644 index 0000000..9b0166d --- /dev/null +++ b/rio_tiler_pds/sentinel1.py @@ -0,0 +1,276 @@ +"""rio_tiler.io.sentinel1: Sentinel-1 processing.""" + +import json +import os +import re +from concurrent import futures +from typing import Any, Dict, Sequence, Tuple, Union + +import numpy +import rasterio +from boto3.session import Session as boto3_session +from rasterio import transform +from rasterio.vrt import WarpedVRT + +from rio_tiler import constants, reader +from rio_tiler.errors import InvalidBandName, InvalidSentinelSceneId + +REGION = os.environ.get("AWS_REGION", "eu-central-1") +SENTINEL_BANDS = ["vv", "vh"] + + +def _aws_get_object( + bucket: str, + key: str, + request_pays: bool = True, + client: boto3_session.client = None, +) -> bytes: + """AWS s3 get object content.""" + if not client: + session = boto3_session(region_name=REGION) + client = session.client("s3") + + params = {"Bucket": bucket, "Key": key} + if request_pays: + params["RequestPayer"] = "requester" + + response = client.get_object(**params) + + return response["Body"].read() + + +def sentinel1_parser(sceneid: str) -> Dict: + """ + Parse Sentinel-1 scene id. + + Attributes + ---------- + sceneid : str + Sentinel-1 sceneid. + + Returns + ------- + out : dict + dictionary with metadata constructed from the sceneid. + + """ + if not re.match( + "^S1[AB]_(IW)|(EW)_[A-Z]{3}[FHM]_[0-9][SA][A-Z]{2}_[0-9]{8}T[0-9]{6}_[0-9]{8}T[0-9]{6}_[0-9A-Z]{6}_[0-9A-Z]{6}_[0-9A-Z]{4}$", + sceneid, + ): + raise InvalidSentinelSceneId("Could not match {}".format(sceneid)) + + sentinel_pattern = ( + r"^S" + r"(?P\w{1})" + r"(?P[AB]{1})" + r"_" + r"(?P[A-Z]{2})" + r"_" + r"(?P[A-Z]{3})" + r"(?P[FHM])" + r"_" + r"(?P[0-9])" + r"(?P[SA])" + r"(?P(SH)|(SV)|(DH)|(DV)|(HH)|(HV)|(VV)|(VH))" + r"_" + r"(?P[0-9]{8}T[0-9]{6})" + r"_" + r"(?P[0-9]{8}T[0-9]{6})" + r"_" + r"(?P[0-9]{6})" + r"_" + r"(?P[0-9A-Z]{6})" + r"_" + r"(?P[0-9A-Z]{4})$" + ) + + meta: Dict[str, Any] = re.match( + sentinel_pattern, sceneid, re.IGNORECASE + ).groupdict() + + meta["scene"] = sceneid + year = meta["startDateTime"][0:4] + month = meta["startDateTime"][4:6].strip("0") + day = meta["startDateTime"][6:8].strip("0") + + meta["scheme"] = "s3" + meta["bucket"] = "sentinel-s1-l1c" + meta["prefix"] = os.path.join( + meta["product"], year, month, day, meta["beam"], meta["polarisation"], sceneid + ) + + return meta + + +def _get_bounds(scene_info: Dict) -> Tuple[float, float, float, float]: + bucket, prefix = scene_info["bucket"], scene_info["prefix"] + product_info = json.loads(_aws_get_object(bucket, f"{prefix}/productInfo.json")) + + xyz = list(zip(*product_info["footprint"]["coordinates"][0])) + return min(xyz[0]), min(xyz[1]), max(xyz[0]), max(xyz[1]) + + +def bounds(sceneid: str) -> Dict: + """ + Retrieve image bounds. + + Attributes + ---------- + sceneid : str + Sentinel-1 sceneid. + + Returns + ------- + out : dict + dictionary with image bounds. + + """ + scene_params = sentinel1_parser(sceneid) + return dict(sceneid=sceneid, bounds=_get_bounds(scene_params)) + + +def metadata( + sceneid: str, + pmin: float = 2.0, + pmax: float = 98.0, + bands: Union[Sequence[str], str] = None, + hist_options: Dict = {}, + **kwargs, +) -> Dict: + """ + Retrieve image bounds and band statistics. + + Attributes + ---------- + sceneid : str + Sentinel-1 sceneid. + pmin : float, optional, (default: 2.) + Histogram minimum cut. + pmax : float, optional, (default: 98.) + Histogram maximum cut. + bands: tuple, str, required + Bands name (e.g vv, vh). + kwargs : optional + These are passed to 'rio_tiler.utils._stats' + e.g: bins=20, range=(0, 1000) + + Returns + ------- + out : dict + Dictionary with image bounds and bands statistics. + + """ + if not bands: + raise InvalidBandName("bands is required") + + if isinstance(bands, str): + bands = (bands,) + + for band in bands: + if band not in SENTINEL_BANDS: + raise InvalidBandName("{} is not a valid Sentinel band name".format(band)) + + scene_params = sentinel1_parser(sceneid) + sentinel_prefix = "{scheme}://{bucket}/{prefix}/measurement".format(**scene_params) + + def worker(band: str): + asset = "{}/{}-{}.tiff".format( + sentinel_prefix, scene_params["beam"].lower(), band + ) + with rasterio.open(asset) as src_dst: + with WarpedVRT( + src_dst, + src_crs=src_dst.gcps[1], + src_transform=transform.from_gcps(src_dst.gcps[0]), + src_nodata=0, + ) as vrt_dst: + return reader.metadata( + vrt_dst, + percentiles=(pmin, pmax), + hist_options=hist_options, + **kwargs, + ) + + with futures.ThreadPoolExecutor(max_workers=constants.MAX_THREADS) as executor: + responses = list(executor.map(worker, bands)) + + info = dict( + sceneid=sceneid, + bounds=responses[0]["bounds"], + band_descriptions=[(ix + 1, b) for ix, b in enumerate(bands)], + ) + + info["statistics"] = { + b: v for b, d in zip(bands, responses) for _, v in d["statistics"].items() + } + return info + + +def tile( + sceneid: str, + tile_x: int, + tile_y: int, + tile_z: int, + bands: Union[Sequence[str], str] = None, + tilesize: int = 256, + **kwargs: Any, +) -> Tuple[numpy.ndarray, numpy.ndarray]: + """ + Create mercator tile from Sentinel-1 data. + + Attributes + ---------- + sceneid : str + Sentinel-2 sceneid. + tile_x : int + Mercator tile X index. + tile_y : int + Mercator tile Y index. + tile_z : int + Mercator tile ZOOM level. + bands: tuple, str, required + Bands name (e.g vv, vh). + tilesize : int, optional (default: 256) + Output image size. + + Returns + ------- + data : numpy ndarray + mask: numpy array + + """ + if not bands: + raise InvalidBandName("bands is required") + + if isinstance(bands, str): + bands = (bands,) + + for band in bands: + if band not in SENTINEL_BANDS: + raise InvalidBandName("{} is not a valid Sentinel band name".format(band)) + + scene_params = sentinel1_parser(sceneid) + sentinel_prefix = "{scheme}://{bucket}/{prefix}/measurement".format(**scene_params) + + def worker(band: str): + asset = "{}/{}-{}.tiff".format( + sentinel_prefix, scene_params["beam"].lower(), band + ) + with rasterio.open(asset) as src_dst: + with WarpedVRT( + src_dst, + src_crs=src_dst.gcps[1], + src_transform=transform.from_gcps(src_dst.gcps[0]), + src_nodata=0, + ) as vrt_dst: + return reader.tile( + vrt_dst, tile_x, tile_y, tile_z, tilesize=tilesize, **kwargs + ) + + with futures.ThreadPoolExecutor(max_workers=constants.MAX_THREADS) as executor: + data, masks = zip(*list(executor.map(worker, bands))) + data = numpy.concatenate(data) + mask = numpy.all(masks, axis=0).astype(numpy.uint8) * 255 + + return data, mask diff --git a/rio_tiler_pds/sentinel2.py b/rio_tiler_pds/sentinel2.py new file mode 100644 index 0000000..2916b5e --- /dev/null +++ b/rio_tiler_pds/sentinel2.py @@ -0,0 +1,276 @@ +"""rio_tiler.reader.sentinel2: Sentinel-2 processing.""" + +import itertools +import os +import re +from collections import OrderedDict +from typing import Any, Dict, Sequence, Tuple, Union + +import numpy +import rasterio +from rasterio.warp import transform_bounds + +from rio_tiler import constants, reader +from rio_tiler.errors import InvalidBandName, InvalidSentinelSceneId, TileOutsideBounds +from rio_tiler.utils import tile_exists + +SENTINEL_L1_BANDS = OrderedDict( + [ + ("10", ["02", "03", "04", "08"]), + ("20", ["05", "06", "07", "11", "12", "8A"]), + ("60", ["01", "09", "10"]), + ] +) + +SENTINEL_L2_BANDS = OrderedDict( + [ + ("10", ["02", "03", "04", "08"]), + ("20", ["02", "03", "04", "05", "06", "07", "08", "11", "12", "8A"]), + ( + "60", + ["01", "02", "03", "04", "05", "06", "07", "08", "09", "11", "12", "8A"], + ), + ] +) + +SENTINEL_L2_PRODUCTS = OrderedDict( + [ + ("10", ["AOT", "WVP"]), + ("20", ["AOT", "SCL", "WVP"]), + ("60", ["AOT", "SCL", "WVP"]), + ] +) + + +def sentinel2_parser(sceneid: str) -> Dict: + """ + Parse Sentinel-2 scene id. + + Attributes + ---------- + sceneid : str + Sentinel-2 sceneid. + + Returns + ------- + out : dict + dictionary with metadata constructed from the sceneid. + + """ + + if not re.match("^S2[AB]_L[0-2][A-C]_[0-9]{8}_[0-9]{2}[A-Z]{3}_[0-9]$", sceneid): + raise InvalidSentinelSceneId("Could not match {}".format(sceneid)) + + sentinel_pattern = ( + r"^S" + r"(?P\w{1})" + r"(?P[AB]{1})" + r"_" + r"(?PL[0-2][ABC])" + r"_" + r"(?P[0-9]{4})" + r"(?P[0-9]{2})" + r"(?P[0-9]{2})" + r"_" + r"(?P[0-9]{2})" + r"(?P\w{1})" + r"(?P\w{2})" + r"_" + r"(?P[0-9]{1})$" + ) + + meta: Dict[str, Any] = re.match( + sentinel_pattern, sceneid, re.IGNORECASE + ).groupdict() + meta["scene"] = sceneid + + utm_zone = meta["utm"].lstrip("0") + grid_square = meta["sq"] + latitude_band = meta["lat"] + year = meta["acquisitionYear"] + month = meta["acquisitionMonth"].lstrip("0") + day = meta["acquisitionDay"].lstrip("0") + img_num = meta["num"] + + meta["scheme"] = "s3" + meta["bucket"] = "sentinel-s2-" + meta["processingLevel"].lower() + meta["prefix"] = os.path.join( + "tiles", utm_zone, latitude_band, grid_square, year, month, day, img_num + ) + + if meta["processingLevel"] == "L1C": + meta["preview_file"] = "preview.jp2" + meta["preview_prefix"] = "" + meta["bands"] = list( + itertools.chain.from_iterable( + [bands for _, bands in SENTINEL_L1_BANDS.items()] + ) + ) + meta["valid_bands"] = meta["bands"] + else: + meta["preview_file"] = "R60m/TCI.jp2" + meta["preview_prefix"] = "R60m" + meta["bands"] = SENTINEL_L2_BANDS["60"] + meta["valid_bands"] = meta["bands"] + SENTINEL_L2_PRODUCTS["60"] + + return meta + + +def _l2_prefixed_band(band: str) -> str: + """Return L2A prefixed bands name.""" + if band in SENTINEL_L2_BANDS["60"]: + for res, bands in SENTINEL_L2_BANDS.items(): + if band in bands: + return "R{}m/B{}".format(res, band) + elif band in SENTINEL_L2_PRODUCTS["60"]: + for res, bands in SENTINEL_L2_PRODUCTS.items(): + if band in bands: + return "R{}m/{}".format(res, band) + + raise InvalidBandName("{} is not a valid Sentinel band name".format(band)) + + +def bounds(sceneid: str) -> Dict: + """ + Retrieve image bounds. + + Attributes + ---------- + sceneid : str + Sentinel-2 sceneid. + + Returns + ------- + out : dict + dictionary with image bounds. + + """ + scene_params = sentinel2_parser(sceneid) + preview_file = "{scheme}://{bucket}/{prefix}/{preview_file}".format(**scene_params) + with rasterio.open(preview_file) as src_dst: + bounds = transform_bounds( + src_dst.crs, constants.WGS84_CRS, *src_dst.bounds, densify_pts=21 + ) + + return dict(sceneid=sceneid, bounds=bounds) + + +def metadata( + sceneid: str, + pmin: float = 2.0, + pmax: float = 98.0, + hist_options: Dict = {}, + **kwargs: Any, +) -> Dict: + """ + Retrieve image bounds and band statistics. + + Attributes + ---------- + sceneid : str + Sentinel-2 sceneid. + pmin : float, optional, (default: 2.) + Histogram minimum cut. + pmax : float, optional, (default: 98.) + Histogram maximum cut. + hist_options : dict, optional + Options to forward to numpy.histogram function. + e.g: {bins=20, range=(0, 1000)} + kwargs : optional + These are passed to 'rio_tiler.reader.preview' + + Returns + ------- + out : dict + Dictionary with image bounds and bands statistics. + + """ + scene_params = sentinel2_parser(sceneid) + sentinel_prefix = "{scheme}://{bucket}/{prefix}/{preview_prefix}".format( + **scene_params + ) + bands = scene_params["bands"] + + addresses = [f"{sentinel_prefix}/B{band}.jp2" for band in bands] + + responses = reader.multi_metadata( + addresses, + indexes=[1], + nodata=0, + percentiles=(pmin, pmax), + hist_options=hist_options, + **kwargs, + ) + info: Dict[str, Any] = dict(sceneid=sceneid) + info["band_descriptions"] = [(ix + 1, b) for ix, b in enumerate(bands)] + info["bounds"] = responses[0]["bounds"] + info["statistics"] = { + b: v for b, d in zip(bands, responses) for k, v in d["statistics"].items() + } + return info + + +def tile( + sceneid: str, + tile_x: int, + tile_y: int, + tile_z: int, + bands: Union[Sequence[str], str] = ("04", "03", "02"), + tilesize: int = 256, + **kwargs: Dict, +) -> Tuple[numpy.ndarray, numpy.ndarray]: + """ + Create mercator tile from Sentinel-2 data. + + Attributes + ---------- + sceneid : str + Sentinel-2 sceneid. + tile_x : int + Mercator tile X index. + tile_y : int + Mercator tile Y index. + tile_z : int + Mercator tile ZOOM level. + bands : tuple, str, optional (default: ('04', '03', '02')) + Bands index for the RGB combination. + tilesize : int, optional (default: 256) + Output image size. + kwargs: dict, optional + These will be passed to the 'rio_tiler.utils._tile_read' function. + + Returns + ------- + data : numpy ndarray + mask: numpy array + + """ + if isinstance(bands, str): + bands = (bands,) + + scene_params = sentinel2_parser(sceneid) + for band in bands: + if band not in scene_params["valid_bands"]: + raise InvalidBandName("{} is not a valid Sentinel band name".format(band)) + + sentinel_prefix = "{scheme}://{bucket}/{prefix}".format(**scene_params) + + preview_file = os.path.join(sentinel_prefix, scene_params["preview_file"]) + with rasterio.open(preview_file) as src: + bounds = transform_bounds( + src.crs, constants.WGS84_CRS, *src.bounds, densify_pts=21 + ) + if not tile_exists(bounds, tile_z, tile_x, tile_y): + raise TileOutsideBounds( + "Tile {}/{}/{} is outside image bounds".format(tile_z, tile_x, tile_y) + ) + + if scene_params["processingLevel"] == "L2A": + bands = [_l2_prefixed_band(b) for b in bands] + else: + bands = ["B{}".format(b) for b in bands] + + addresses = [f"{sentinel_prefix}/{band}.jp2" for band in bands] + return reader.multi_tile( + addresses, tile_x, tile_y, tile_z, tilesize=tilesize, nodata=0 + ) diff --git a/setup.py b/setup.py new file mode 100644 index 0000000..fef25b9 --- /dev/null +++ b/setup.py @@ -0,0 +1,44 @@ +"""Setup for rio-tiler-pds.""" + +from setuptools import find_packages, setup + +with open("README.md") as f: + readme = f.read() + +# Runtime requirements. +inst_reqs = [ + "rio-tiler~=2.0b1", + "rio-toa", +] + +extra_reqs = { + "test": ["pytest", "pytest-cov"], + "dev": ["pytest", "pytest-cov", "pre-commit",], +} + +setup( + name="rio-tiler-pds", + version="0.0.1", + python_requires=">=3", + description=u"""Get mercator tile from CloudOptimized GeoTIFF and other cloud hosted raster such as CBERS-4, Sentinel-2, Sentinel-1 and Landsat-8 AWS PDS""", + long_description=readme, + long_description_content_type="text/markdown", + classifiers=[ + "Intended Audience :: Information Technology", + "Intended Audience :: Science/Research", + "License :: OSI Approved :: BSD License", + "Programming Language :: Python :: 3.7", + "Programming Language :: Python :: 3.6", + "Topic :: Scientific/Engineering :: GIS", + ], + keywords="COG cogeo raster aws map tiler gdal rasterio", + author=u"Vincent Sarago", + author_email="vincent@developmentseed.org", + url="https://github.com/cogeotiff/rio-tiler-pds", + license="BSD", + packages=find_packages(exclude=["ez_setup", "examples", "tests"]), + include_package_data=True, + zip_safe=False, + install_requires=inst_reqs, + extras_require=extra_reqs, +) diff --git a/tests/__init__.py b/tests/__init__.py new file mode 100644 index 0000000..80f3212 --- /dev/null +++ b/tests/__init__.py @@ -0,0 +1 @@ +"""rio-tiler tests suite.""" diff --git a/tests/fixtures/cbers-pds/CBERS4/AWFI/146/129/CBERS_4_AWFI_20170420_146_129_L2/CBERS_4_AWFI_20170420_146_129_L2_BAND13.tif b/tests/fixtures/cbers-pds/CBERS4/AWFI/146/129/CBERS_4_AWFI_20170420_146_129_L2/CBERS_4_AWFI_20170420_146_129_L2_BAND13.tif new file mode 100644 index 0000000000000000000000000000000000000000..59795285e2faf6fdf0eff5f0dc9e3bcd7a5e0aa7 GIT binary patch literal 232836 zcmeFa2bfjG_U&7<3c-Mw6%%6CV*rBja~BY|9;C)y;f{39 zRdmjRGq#%YV!v%aW=lHa#EysOH&bd2S^smAunY+ugyO>76Y z?|js`C;rR+y|cYLg3m8vp9(qU6Z?F?c6M%gSC-GWvpuOGxXNr-;s8?$ysO0aOKfKi 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