samgis / src /prediction_api /predictor.py
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# Press the green button in the gutter to run the script.
import json
from src.utilities.constants import ROOT
from src.utilities.utilities import setup_logging
local_logger = setup_logging()
def base_predict(bbox, point_coords, point_crs="EPSG:4326", zoom=16, model_name:str="vit_h", root_folder:str=ROOT) -> str:
from samgeo import SamGeo, tms_to_geotiff
image = f"{root_folder}/satellite.tif"
local_logger.info("start tms_to_geotiff")
# bbox: image input coordinate
tms_to_geotiff(output=image, bbox=bbox, zoom=zoom, source="Satellite", overwrite=True)
local_logger.info(f"geotiff created, start to initialize samgeo instance (read model {model_name} from {root_folder})...")
predictor = SamGeo(
model_type=model_name,
checkpoint_dir=root_folder,
automatic=False,
sam_kwargs=None,
)
local_logger.info(f"initialized samgeo instance, start to set_image {image}...")
predictor.set_image(image)
output_name = f"{root_folder}/output.tif"
local_logger.info(f"done set_image, start prediction...")
predictor.predict(point_coords, point_labels=len(point_coords), point_crs=point_crs, output=output_name)
local_logger.info(f"done prediction, start tiff to geojson conversion...")
# geotiff to geojson
vector = f"{root_folder}/feats.geojson"
predictor.tiff_to_geojson(output_name, vector, bidx=1)
local_logger.info(f"start reading geojson...")
with open(vector) as out_gdf:
out_gdf_str = json.load(out_gdf)
local_logger.info(f"number of fields in geojson output:{len(out_gdf_str)}.")
return out_gdf_str