roboflow--supervision/docs/detection/tools/inference_slicer.md

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InferenceSlicer

GeoTIFF Datasets

Install the optional GeoTIFF dependencies before running this example:

pip install "supervision[geotiff]"
wget -O RGB.byte.tif https://raw.githubusercontent.com/rasterio/rasterio/main/tests/data/RGB.byte.tif

InferenceSlicer can read an open rasterio dataset window-by-window. This keeps large GeoTIFFs out of memory while passing each tile to the callback as an (H, W, C) NumPy array.

import numpy as np
import rasterio
import supervision as sv


def callback(tile: np.ndarray) -> sv.Detections:
    h, w = tile.shape[:2]
    return sv.Detections(
        xyxy=np.array([[w * 0.25, h * 0.25, w * 0.75, h * 0.75]], dtype=float),
        confidence=np.array([0.9]),
        class_id=np.array([0]),
    )


slicer = sv.InferenceSlicer(
    callback=callback,
    slice_wh=(256, 256),
    overlap_wh=(64, 64),
    overlap_filter=sv.OverlapFilter.NONE,
)

with rasterio.open("RGB.byte.tif") as dataset:
    detections = slicer(dataset)

print(len(detections))

GeoTIFF inputs must use a projected coordinate reference system. Reproject geographic rasters before passing them to InferenceSlicer.

WindowedRasterDataset

:::supervision.detection.tools.inference_slicer.WindowedRasterDataset

:::supervision.detection.tools.inference_slicer.InferenceSlicer