Is there a way to crop by image coordinates?

[rbudhu]

Hello! If I understand correctly, the current /crop endpoint only allows cropping by geocoordinates (lat/lon)? Is there another endpoint that allows cropping by image x,y (lines,sample)?

[vincentsarago]

👋 @rbudhu

Good question! No there is not but here is how you could add one:

from fastapi import FastAPI, Path, Query, Depends

from titiler.core.factory import TilerFactory, img_endpoint_params
from titiler.core.utils import Timer
from titiler.core.resources.enums import ImageType

from rasterio import windows


app = FastAPI(description="A lightweight Cloud Optimized GeoTIFF tile server")

# Create a Default set of endpoint using the TilerFactory
cog = TilerFactory()

# Register a custom `/window` endpoint
@cog.router.get(
    # https://rasterio.readthedocs.io/en/latest/topics/windowed-rw.html?highlight=window#windows
    # simple path parameters to define a rasterio window
    r"/window/{col_off},{row_off},{width},{height}.{format}",
    **img_endpoint_params,
)
def window(
    col_off: int = Path(..., description="Column offset"),
    row_off: int = Path(..., description="Row offset"),
    width: int = Path(..., description="Width"),
    height: int = Path(..., description="Height"),
    format: ImageType = Query(..., description="Output image type."),
    src_path=Depends(cog.path_dependency),
    layer_params=Depends(cog.layer_dependency),
    dataset_params=Depends(cog.dataset_dependency),
    postprocess_params=Depends(cog.process_dependency),
    colormap=Depends(cog.colormap_dependency),
    render_params=Depends(cog.render_dependency),
):
    """Read a window."""
    timings = []
    headers: Dict[str, str] = {}

    with Timer() as t:
        with rasterio.Env(**self.gdal_config):
            with self.reader(src_path) as src_dst:
                # https://github.com/cogeotiff/rio-tiler/blob/master/rio_tiler/io/cogeo.py#L600-L605
                data = src_dst.read(
                    window=windows.Window(col_off, row_off, width, height),
                    **dataset_params,
                )
                dst_colormap = getattr(src_dst, "colormap", None)
    timings.append(("dataread", round(t.elapsed * 1000, 2)))

    with Timer() as t:
        image = data.post_process(**postprocess_params)
    timings.append(("postprocess", round(t.elapsed * 1000, 2)))

    with Timer() as t:
        content = image.render(
            img_format=format.driver,
            colormap=colormap or dst_colormap,
            **format.profile,
            **render_params,
        )
    timings.append(("format", round(t.elapsed * 1000, 2)))

    if OptionalHeader.server_timing in self.optional_headers:
        headers["Server-Timing"] = ", ".join(
            [f"{name};dur={time}" for (name, time) in timings]
        )

    return Response(content, media_type=format.mediatype, headers=headers)


app.include_router(cog.router, tags=["Cloud Optimized GeoTIFF"])

[rbudhu]

Awesome! Thank you!