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I am doing an object detection project using detectron2, which requires datasets to be in COCO format. This format needs images as png and polygons in a JSON file. However, spatial images (e.g. satellites or drones) are georeferenced (tif format), and the annotations/labels also have geographical coordinates (shp/geojson format). Getting a regular image from a tif file is pretty straightforward using rasterio and numpy, but getting the annotations in the correct coordinate system has been difficult because they need to point to the position of the polygons in the png, not the georeferenced image.

As an example, say I have a 300*300 px satellite image bounded by these coordinates: 75W 10N, 70W 5N. The coordinates of the polygons will be within the region of the geographical box. Once I transform the geo-image to a normal image, it will lose its geographical reference, so the coordinates of the polygons should be in (0, 300), (0, 300).

Is there a way to translate the polygons from geographical coordinates to positional coordinates in an image so that I can make a dataset in COCO format?

  • Does [this](https://www.researchgate.net/post/How_to_find_the_coordinates_of_every_pixel_in_a_satellite_image_knowing_the_coordinates_of_some_pixels) answer your question? – Laassairi Abdellah May 15 '23 at 17:32

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