diff --git a/rest/Pipfile b/rest/Pipfile index 7b8e308c..96297d0f 100644 --- a/rest/Pipfile +++ b/rest/Pipfile @@ -22,9 +22,13 @@ openeo-pg-parser = {editable = true,git = "https://github.com/Ardweaden/openeo-p requests = "==2.27.1" flask-cors = "==3.0.10" honeycomb-beeline = "==3.2.0" -pg-to-evalscript = "==0.2.6" +pg-to-evalscript = "==0.2.8" sentinelhub = "==3.6.3" isodate = "==0.6.1" pyjwt = {extras = ["crypto"], version = "==2.3.0"} -cryptography = "==3.4.8" +cryptography = "==36.0.1" placebo = "==0.9.0" +rioxarray = "*" +zarr = "*" +netcdf4 = "*" +pip-tools = "==6.1.0" diff --git a/rest/Pipfile.lock b/rest/Pipfile.lock index 6548eb18..51191fd4 100644 --- a/rest/Pipfile.lock +++ b/rest/Pipfile.lock @@ -1,7 +1,7 @@ { "_meta": { "hash": { - "sha256": "65882995caee35fa1296bbf8ff8964b1243444a9c04a2f23644759463b970522" + "sha256": "74cc999abd077d3e6f626772ecec2f996c3fc6a0afd10dd32ac71b5e63de92d9" }, "pipfile-spec": 6, "requires": { @@ -18,19 +18,33 @@ "default": { "aenum": { "hashes": 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"sha256:f87ec75864c37c4c6cb908d282e1969e79763e0d9becdfe9fe5473b7bb1e5f09", + "sha256:fbec11614dba0424ca72f4e8ba3c420dba07b4a7c206c8c8e4e73f2e98f4c559", + "sha256:fd69666217b62fa5d7c6aa88e507493a34dec4fa20c5bd925e4bc12fce586639" ], "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3, 3.4'", - "version": "==1.14.1" + "version": "==1.15.0" }, "wsgi-request-logger": { "hashes": [ diff --git a/rest/app.py b/rest/app.py index 187adec4..a15c04c8 100644 --- a/rest/app.py +++ b/rest/app.py @@ -40,6 +40,7 @@ get_batch_job_status, create_or_get_estimate_values_from_db, ) +from post_processing.post_processing import parse_sh_gtiff_to_format from processing.utils import inject_variables_in_process_graph, overwrite_spatial_extent_without_parameters from processing.openeo_process_errors import OpenEOProcessError from authentication.authentication import authentication_provider @@ -593,6 +594,13 @@ def add_job_to_queue(job_id): metadata_filename = "metadata.json" bucket.put_file_to_bucket("", prefix=job["batch_request_id"], file_name=metadata_filename) + # START OF POST_PROCESSING + # post-process gtiffs to appropriate formats + + parse_sh_gtiff_to_format(job, bucket) + + # END OF POST_PROCESSING + results = bucket.get_data_from_bucket(prefix=job["batch_request_id"]) log(INFO, f"Fetched all results: {str(results)}") diff --git a/rest/authentication/authentication.py b/rest/authentication/authentication.py index c9f75c97..22764cdf 100644 --- a/rest/authentication/authentication.py +++ b/rest/authentication/authentication.py @@ -21,6 +21,8 @@ from authentication.user import OIDCUser, SHUser from authentication.utils import decode_sh_access_token +from openeoerrors import TokenInvalid + class AuthScheme(Enum): BASIC = "basic" diff --git a/rest/buckets/results_bucket.py b/rest/buckets/results_bucket.py index 63e5f501..a0e423a5 100644 --- a/rest/buckets/results_bucket.py +++ b/rest/buckets/results_bucket.py @@ -17,6 +17,11 @@ def put_file_to_bucket(self, content_as_string, prefix=None, file_name="file"): self.client.put_object(Bucket=self.bucket_name, Key=file_path, Body=content_as_string) + def upload_file_to_bucket(self, local_file_path, prefix=None, file_name="file"): + s3_file_path = prefix + "/" + file_name if prefix else file_name + + self.client.upload_file(local_file_path, self.bucket_name, s3_file_path) + def get_data_from_bucket(self, prefix=None): continuation_token = None results = [] diff --git a/rest/output_formats/NetCDF.json b/rest/output_formats/NetCDF.json new file mode 100644 index 00000000..1facb24b --- /dev/null +++ b/rest/output_formats/NetCDF.json @@ -0,0 +1,17 @@ +{ + "gis_data_types": [ + "raster" + ], + "parameters": { + "datatype": { + "type": "string", + "description": "The values data type.", + "enum": [ + "byte", + "uint16", + "float32" + ], + "default": "float32" + } + } +} \ No newline at end of file diff --git a/rest/output_formats/ZARR.json b/rest/output_formats/ZARR.json new file mode 100644 index 00000000..1facb24b --- /dev/null +++ b/rest/output_formats/ZARR.json @@ -0,0 +1,17 @@ +{ + "gis_data_types": [ + "raster" + ], + "parameters": { + "datatype": { + "type": "string", + "description": "The values data type.", + "enum": [ + "byte", + "uint16", + "float32" + ], + "default": "float32" + } + } +} \ No newline at end of file diff --git a/rest/post_processing/__init__.py b/rest/post_processing/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/rest/post_processing/const.py b/rest/post_processing/const.py new file mode 100644 index 00000000..d841120a --- /dev/null +++ b/rest/post_processing/const.py @@ -0,0 +1,10 @@ +from sentinelhub import MimeType +from processing.const import CustomMimeType + +TMP_FOLDER = "/tmp/" + +parsed_output_file_name = { + MimeType.TIFF: {"name": "output", "ext": ".tif"}, + CustomMimeType.ZARR: {"name": "output", "ext": ".zarr"}, + CustomMimeType.NETCDF: {"name": "output", "ext": ".nc"}, +} diff --git a/rest/post_processing/gtiff_parser.py b/rest/post_processing/gtiff_parser.py new file mode 100644 index 00000000..3bdc6c1a --- /dev/null +++ b/rest/post_processing/gtiff_parser.py @@ -0,0 +1,110 @@ +import os +import shutil +import rioxarray +from dateutil import parser +import pandas as pd +import xarray as xr +import requests +from sentinelhub import MimeType + +from processing.const import CustomMimeType +from openeoerrors import Internal + +# assume it's only 1 time and 1 bands dimension +def check_dimensions(time_dimensions, bands_dimensions): + if len(time_dimensions) == 0: + raise Internal("No time dimensions exist. Only 1 time dimension is supported.") + + if len(time_dimensions) > 1: + raise Internal("More than 1 time dimension exist. Only 1 time dimension is supported.") + + if len(bands_dimensions) == 0: + raise Internal("No bands dimensions exist. Only 1 bands dimension is supported.") + + if len(bands_dimensions) > 1: + raise Internal("More than 1 bands dimension exist. Only 1 bands dimension is supported.") + + +def get_timestamps_arrays(datacube_time_as_bands, time_dimensions, bands_dimensions, output_format): + num_of_img_bands = len(datacube_time_as_bands["band"]) + num_of_bands_dimension = len(bands_dimensions[0]["labels"]) + + list_of_timestamps = [] + list_of_timestamp_arrays = [] + + for i in range(0, num_of_img_bands, num_of_bands_dimension): + date = time_dimensions[0]["labels"][int(i / num_of_bands_dimension)] + timestamp_array = datacube_time_as_bands[i : i + num_of_bands_dimension] + + if output_format in [CustomMimeType.NETCDF, CustomMimeType.ZARR]: + pandas_time = pd.to_datetime(parser.parse(date)) + timestamp_array = timestamp_array.assign_coords(band=bands_dimensions[0]["labels"]) + timestamp_array = timestamp_array.assign_coords(t=pandas_time) + timestamp_array = timestamp_array.expand_dims(dim="t") + + list_of_timestamps.append(date) + list_of_timestamp_arrays.append(timestamp_array) + + return list_of_timestamps, list_of_timestamp_arrays + + +def save_as_gtiff(list_of_timestamps, list_of_timestamp_arrays, output_dir, output_name): + output_file_paths = [] + for array, date in zip(list_of_timestamp_arrays, list_of_timestamps): + file_name = f"{output_name['name']}_{date}{output_name['ext']}" + file_path = os.path.join(output_dir, file_name) + output_file_paths.append(file_path) + + array.rio.to_raster( + file_path, + tiled=True, # GDAL: By default striped TIFF files are created. This option can be used to force creation of tiled TIFF files. + windowed=True, # rioxarray: read & write one window at a time + ) + return output_file_paths + + +def save_as_netcdf(list_of_timestamp_arrays, output_dir, output_name): + datacube_with_time_dimension = xr.combine_by_coords(list_of_timestamp_arrays) + output_file_path = os.path.join(output_dir, f"{output_name['name']}{output_name['ext']}") + datacube_with_time_dimension.to_netcdf(output_file_path) + return [output_file_path] + + +def save_as_zarr(list_of_timestamp_arrays, output_dir, output_name): + datacube_with_time_dimension = xr.combine_by_coords(list_of_timestamp_arrays) + output_file_path = os.path.join(output_dir, f"{output_name['name']}{output_name['ext']}") + datacube_with_time_dimension.to_zarr(output_file_path) + # zip the zarr folder to avoid listing a bunch of files + shutil.make_archive(output_file_path, "zip", output_file_path) + output_file_path = f"{output_file_path}.zip" + return [output_file_path] + + +def parse_multitemporal_gtiff_to_format(input_tiff, input_metadata, output_dir, output_name, output_format): + datacube_time_as_bands = rioxarray.open_rasterio(input_tiff) + datacube_metadata = requests.get(input_metadata).json() + + time_dimensions = [dim for dim in datacube_metadata["outputDimensions"] if dim["type"] == "temporal"] + bands_dimensions = [dim for dim in datacube_metadata["outputDimensions"] if dim["type"] == "bands"] + + # mock a bands dimension (with 1 band) if it's not present in the data + # e.g. save_result process right after ndvi process which doesn't have a target band set + if len(bands_dimensions) == 0: + bands_dimensions = [{"name": "bands", "type": "bands", "labels": ["results"]}] + + check_dimensions(time_dimensions, bands_dimensions) + + list_of_timestamps, list_of_timestamp_arrays = get_timestamps_arrays( + datacube_time_as_bands, time_dimensions, bands_dimensions, output_format + ) + + if output_format == MimeType.TIFF: + return save_as_gtiff(list_of_timestamps, list_of_timestamp_arrays, output_dir, output_name) + + if output_format == CustomMimeType.NETCDF: + return save_as_netcdf(list_of_timestamp_arrays, output_dir, output_name) + + if output_format == CustomMimeType.ZARR: + return save_as_zarr(list_of_timestamp_arrays, output_dir, output_name) + + raise Internal(f"Parsing to format {output_format} is not supported") diff --git a/rest/post_processing/post_processing.py b/rest/post_processing/post_processing.py new file mode 100644 index 00000000..411d126d --- /dev/null +++ b/rest/post_processing/post_processing.py @@ -0,0 +1,73 @@ +import os +import json +import shutil + +from processing.const import ShBatchResponseOutput, ProcessingRequestTypes +from processing.processing import new_process +from post_processing.gtiff_parser import parse_multitemporal_gtiff_to_format +from post_processing.const import TMP_FOLDER, parsed_output_file_name + + +def check_if_already_parsed(results, output_format): + for result in results: + if ( + parsed_output_file_name[output_format]["name"] in result["Key"] + and parsed_output_file_name[output_format]["ext"] in result["Key"] + ): + return True + + return False + + +def generate_subfolder_groups(batch_request_id, bucket, results): + subfolder_groups = {} + for result in results: + for output in [ShBatchResponseOutput.DATA, ShBatchResponseOutput.METADATA]: + if output.value in result["Key"]: + url = bucket.generate_presigned_url(object_key=result["Key"]) + subfolder_name = ( + result["Key"].replace(f"{batch_request_id}", "").replace("/", "").split(output.value)[0] + ) + if subfolder_name not in subfolder_groups: + subfolder_groups[subfolder_name] = {} + subfolder_groups[subfolder_name][output.value] = url + + return subfolder_groups + + +def upload_output_to_bucket(local_file_paths, bucket): + for path in local_file_paths: + s3_path = path[len(f"{TMP_FOLDER}") :] + bucket.upload_file_to_bucket(path, None, s3_path) + + +def parse_sh_gtiff_to_format(job, bucket): + batch_request_id = job["batch_request_id"] + results = bucket.get_data_from_bucket(prefix=batch_request_id) + + process = new_process(json.loads(job["process"]), request_type=ProcessingRequestTypes.BATCH) + output_format = process.get_mimetype() + + if check_if_already_parsed(results, output_format): + return + + subfolder_groups = generate_subfolder_groups(batch_request_id, bucket, results) + + for subfolder_id, subfolder_group in subfolder_groups.items(): + input_tiff = subfolder_group[ShBatchResponseOutput.DATA.value] + input_metadata = subfolder_group[ShBatchResponseOutput.METADATA.value] + + # preventively remove directory and create it again + batch_request_dir = f"{TMP_FOLDER}{batch_request_id}" + batch_subfolder = f"{batch_request_dir}/{subfolder_id}/" + if os.path.exists(batch_request_dir): + shutil.rmtree(batch_request_dir) + os.makedirs(batch_subfolder) + + output_file_paths = parse_multitemporal_gtiff_to_format( + input_tiff, input_metadata, batch_subfolder, parsed_output_file_name[output_format], output_format + ) + upload_output_to_bucket(output_file_paths, bucket) + + # remove folder after the folder/file has been uploaded + shutil.rmtree(batch_request_dir) diff --git a/rest/processing/const.py b/rest/processing/const.py index 591da129..5d60906b 100644 --- a/rest/processing/const.py +++ b/rest/processing/const.py @@ -1,6 +1,27 @@ from enum import Enum +import mimetypes +from sentinelhub import MimeType -from sentinelhub import MimeType, SentinelHubBatch + +class ShBatchResponseOutput(Enum): + DATA = "default" + METADATA = "userdata" + + +# Driver needs a way to save the originally requested format in the Process class so that +# the post-processing can parse geotiff from Sentinel Hub to the correct format. +# inspired by sentinelhub.py MimeType class +# https://github.com/sentinel-hub/sentinelhub-py/blob/master/sentinelhub/constants.py#L261 +class CustomMimeType(Enum): + ZARR = "zarr" + NETCDF = "netcdf" + + # This method is needed because mimetype.get_string() is called in construct_output() in rest/processing/sentinel_hub.py + def get_string(self) -> str: + # Need to get geotiff from Sentinel Hub (parsing to the correct format is done in post-processing) + if self is CustomMimeType.ZARR or self is CustomMimeType.NETCDF: + return MimeType.TIFF.get_string() + return mimetypes.types_map["." + self.value] class SampleType(Enum): @@ -24,12 +45,16 @@ def from_gdal_datatype(gdal_datatype): MimeType.PNG: SampleType.UINT8, MimeType.JPG: SampleType.UINT8, MimeType.TIFF: SampleType.FLOAT32, + CustomMimeType.ZARR: SampleType.FLOAT32, + CustomMimeType.NETCDF: SampleType.FLOAT32, } supported_sample_types = { MimeType.PNG: [SampleType.UINT8, SampleType.UINT16], MimeType.JPG: [SampleType.UINT8], MimeType.TIFF: [SampleType.UINT8, SampleType.UINT16, SampleType.FLOAT32], + CustomMimeType.ZARR: [SampleType.UINT8, SampleType.UINT16, SampleType.FLOAT32], + CustomMimeType.NETCDF: [SampleType.UINT8, SampleType.UINT16, SampleType.FLOAT32], } sample_types_to_bytes = { @@ -53,6 +78,8 @@ def get_unsupported_mimetype_message(self): supported_mime_types = { ProcessingRequestTypes.BATCH: { "gtiff": MimeType.TIFF, + "zarr": CustomMimeType.ZARR, + "netcdf": CustomMimeType.NETCDF, }, ProcessingRequestTypes.SYNC: { "gtiff": MimeType.TIFF, @@ -62,6 +89,6 @@ def get_unsupported_mimetype_message(self): } supported_mime_types_error_msg = { - ProcessingRequestTypes.BATCH: "Currently only GTIFF is supported.'", - ProcessingRequestTypes.SYNC: "Currently supported formats are GTIFF, PNG or JPEG", + ProcessingRequestTypes.BATCH: "Currently supported formats are GTIFF, NETCDF and ZARR.", + ProcessingRequestTypes.SYNC: "Currently supported formats are GTIFF, PNG and JPEG.", } diff --git a/rest/processing/sentinel_hub.py b/rest/processing/sentinel_hub.py index 1cd03631..6f05d9a1 100644 --- a/rest/processing/sentinel_hub.py +++ b/rest/processing/sentinel_hub.py @@ -8,6 +8,7 @@ from buckets import BUCKET_NAMES from processing.processing_api_request import ProcessingAPIRequest +from processing.const import ShBatchResponseOutput class SentinelHub: @@ -111,7 +112,10 @@ def construct_data_processing(self, resampling_method): def construct_output(self, width, height, mimetype): output = { - "responses": [{"identifier": "default", "format": {"type": mimetype.get_string()}}], + "responses": [ + {"identifier": ShBatchResponseOutput.DATA.value, "format": {"type": mimetype.get_string()}}, + {"identifier": ShBatchResponseOutput.METADATA.value, "format": {"type": "application/json"}}, + ], } if width is not None: output["width"] = width