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PEP8 compliance, change from raster to vector from vector to raster, …
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…fixed download size with 0.5MB tile size
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@jordancaraballo
jordancaraballo committed Feb 4, 2025
1 parent a01afe2 commit 676481c
Showing 1 changed file with 78 additions and 39 deletions.
117 changes: 78 additions & 39 deletions model/CCDCPipeline.py
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Original file line number Diff line number Diff line change
@@ -1,18 +1,21 @@
import glob
import re
import json
from datetime import datetime as dt
import ee
import rioxarray as rxr
import geedim
import rioxarray as rxr
from shapely import box
from pathlib import Path
from pyCCDC.model.ccdcUtil import toYearFraction, buildCcdImage, getMultiSynthetic
from shapely.ops import transform
from pyproj import Transformer, CRS
from datetime import datetime as dt
from pyCCDC.model.ccdcUtil import \
toYearFraction, buildCcdImage, getMultiSynthetic


class CCDCPipeline:
"""
A class to process and generate CCDC (Continuous Change Detection and Classification) images.
A class to process and generate CCDC
(Continuous Change Detection and Classification) images.
This class provides functionality to:
1. Initialize the pipeline with input and output directories.
Expand All @@ -23,14 +26,17 @@ class CCDCPipeline:
Attributes:
input_dir (str): Directory containing input raster files.
Raster file names should follow the pattern: QB02_YYYYMMDD_?1BS_*.tif
Raster file names should follow the
pattern: QB02_YYYYMMDD_?1BS_*.tif
output_dir (str): Directory to save output CCDC images.
Methods:
__init__(self, input_dir, output_dir): Initialize the CCDCPipeline.
_get_gee_credential(account, key): Static method to get GEE credentials.
_get_gee_credential(account, key): Static method to
get GEE credentials.
_get_coords(self, file): Extract coordinates from a raster file.
gen_single_image(self, date_str, coords, outfile=None): Generate a single CCDC image.
gen_single_image(self, date_str, coords, outfile=None):
Generate a single CCDC image.
run(self): Run the pipeline to process all input scenes.
"""
def __init__(self, input_dir, output_dir):
Expand All @@ -43,41 +49,58 @@ def _get_gee_credential(account, key):
return ee.ServiceAccountCredentials(account, key)
except Exception as e:
print(f"Error creating GEE credentials: {str(e)}")
raise
raise

def _get_coords(self, file):
def _getCoords(self, file):
"""
Extract coordinates from a raster file and convert them to EPSG:4326 projection.
Extract coordinates from a raster file and convert
them to EPSG:4326 projection.
Args:
file (str): Path to the raster file.
Returns:
list: A list of coordinate pairs [longitude, latitude] defining the bounding box of the raster.
list: A list of coordinate pairs [longitude, latitude]
defining the bounding box of the raster.
Note: This function assumes the input file is a valid raster file readable by rioxarray.
Note: This function assumes the input file is a valid
raster file readable by rioxarray.
"""
# Open the raster file
raster = rxr.open_rasterio(file)
raster_epsg = raster.rio.crs.to_epsg()

# Reproject the raster to EPSG:4326 (WGS84) coordinate system
raster_reproj = raster.rio.reproject("EPSG:4326")
# Create a bounding box from the raster's extent
poly = box(*raster.rio.bounds())

# Get the projection of the raster
epsg = raster.rio.crs.to_epsg()
# Define the source and target CRS
source_crs = CRS.from_epsg(raster_epsg) # WGS 84
target_crs = CRS.from_epsg(4326) # Web Mercator

# Create a bounding box from the raster's extent
poly = box(*raster_reproj.rio.bounds())
# Create a transformer
transformer = Transformer.from_crs(
source_crs, target_crs, always_xy=True)

# Reproject the raster to EPSG:4326 (WGS84) coordinate system
poly_reproj = transform(transformer.transform, poly)

# Extract the coordinates of the bounding box
# Convert each coordinate pair to [longitude, latitude] format
coords = [[i[0], i[1]] for i in list(poly.exterior.coords)]

return coords, epsg

def gen_single_image(self, date_str, coords, outfile=None):
# TODO: Implement user-specified GEE account authentication.
# Currently using local credentials for testing purposes.
coords = [[i[0], i[1]] for i in list(poly_reproj.exterior.coords)]

return coords, raster_epsg

def gen_single_image(
self,
date_str,
coords,
outfile=None,
scale=30,
max_tile_size=0.5,
image_dtype='uint16'
):
# TODO: Implement user-specified GEE account authentication.
# Currently using local credentials for testing purposes.
with open("/explore/nobackup/projects/ilab/gee/gee_config.json") as fh:
config = json.load(fh)
gee_account = config.get('gee_account')
Expand All @@ -90,22 +113,33 @@ def gen_single_image(self, date_str, coords, outfile=None):
except Exception as e:
print(f"Error initializing GEE: {str(e)}")
raise

date_object = dt.strptime(date_str, '%Y-%m-%d').date()
formatted_date = toYearFraction(date_object)

roi = ee.Geometry.Polygon(coords=[coords])
segments = (ee.ImageCollection('projects/CCDC/v3').filterBounds(roi).mosaic())
segments = (
ee.ImageCollection('projects/CCDC/v3').filterBounds(roi).mosaic())

bands = ['BLUE', 'GREEN', 'RED', 'NIR']
segs = ["S1", "S2", "S3", "S4", "S5", "S6", "S7", "S8", "S9", "S10"]
n_segments = len(segs)
ccd_image = buildCcdImage(segments, n_segments, bands)
out_image = getMultiSynthetic(ccd_image, formatted_date, bands, segs, 1)
out_image = getMultiSynthetic(
ccd_image, formatted_date, bands, segs, 1)

proj = "EPSG:4326"
im = geedim.MaskedImage(out_image, mask=False)
im.download(outfile, crs=proj, scale=30, region=roi, max_tile_size=2, overwrite=True)
im.download(
outfile,
crs=proj,
scale=scale,
region=roi,
max_tile_size=max_tile_size,
overwrite=True,
dtype=image_dtype,
)
return

def post_proc(self, file, crs):
raster = rxr.open_rasterio(file)
Expand All @@ -115,36 +149,41 @@ def post_proc(self, file, crs):
raster.rio.to_raster(file)

def run(self, toa_file=None):
# Process a specific ToA file if provided, otherwise process all .tif files in the input directory
# Process a specific ToA file if provided, otherwise
# process all .tif files in the input directory
if toa_file:
toa_path = Path(toa_file)
if toa_path.exists():
wv_list = [toa_path]
else:
raise FileNotFoundError(f"The specified file '{toa_path}' does not exist.")
raise FileNotFoundError(
f"The specified file '{toa_path}' does not exist.")
else:
dir_path = Path(self.input_dir)
wv_list = list(dir_path.glob("*.tif"))
if not wv_list:
raise FileNotFoundError(f"No .tif files found in the input directory: {dir_path}")
raise FileNotFoundError(
f"No .tif files found in the input directory: {dir_path}")

out_list = []
for fpath in wv_list:
#base_fn = fpath.name
for fpath in wv_list:
# base_fn = fpath.name

# Assuming raster file name follows the pattern: QB02_YYYYMMDD_?1BS_*.tif
# Assuming raster file name follows the
# pattern: QB02_YYYYMMDD_?1BS_*.tif
date_str = fpath.stem.split('_')[1]

# Validate date string format
if not re.match(r'^\d{8}$', date_str):
raise ValueError("Date string must be in the format YYYYMMDD")
# Convert date string to YYYY-MM-DD format for gen_single_image function
# Convert date string to YYYY-MM-DD format
# for gen_single_image function
date_str = f"{date_str[:4]}-{date_str[4:6]}-{date_str[6:]}"

#Extract bounding box
# Extract bounding box
coords, epsg = self._get_coords(str(fpath))

#Output file path
# Output file path
out_fn = fpath.stem + '_ccdc' + fpath.suffix
out_fpath = Path(self.output_dir) / out_fn
out_list.append(out_fpath)
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