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@@ -8,28 +8,28 @@ It will be manual work, but maybe we can semi-automatize it.
### How it works

The process has three steps:
1. Putting the tiles onto an SVG-canvas using a python script.
1. Putting the tiles onto an SVG-canvas using the `gis-svg-stitcher.py` script.
You may want to try around with the settings (scaling, rotation, etc) of the CLI tool until you get a useful SVG.
2. Manual Editing of the SVG.
There are errors in the GPS data and FLIR data.
Correct them manually using Inkscape or similar Vector Graphics software.
3. Converting the SVG canvas into a GeoTIFF
3. Converting the SVG canvas into a GeoTIFF using the `convert-svg-to-geotiff.py` script.
The script produces 16-bit greyscale PNG-Files, representing the temperature, and exports the SVG into a big PNG image.
This PNG image gets then projected and converted into a GeoTIFF, using temperature information from the grey-scale value of the PNG

The two python scripts:
#### The two python scripts:

* `gis-svg-stitcher.py` for putting the tiles onto an SVG canvas
Example usage:
```
python3 gis-svg-stitcher.py relative_path_to_the_imagefiles --scale=15 --base_rotation=115 --rotation_corr_left=28
python3 gis-svg-stitcher.py relative_path/to/the/image_files --scale=15 --base_rotation=115 --rotation_corr_left=28
```
It produces a file called `map.svg`

* `convert-svg-to-geotiff.py` for converting the (edited) SVG canvas
Example usage:
```
python3 convert-svg-to-geotiff.py relative_path_to_the_imagefiles/map.svg output.tiff
python3 convert-svg-to-geotiff.py relative_path/to/the/image_files/map.svg output.tiff
```




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