Vein segmentation of pre-segmented grapevine leaves using the radial Euler Characteristic Transform

For grapevine leaves pre-segmented from a background, code for a UNet model to segment venation using the Euler Characteristic Transform (ECT). Training data is derived from the `data` folder found in the following repository, and is included in this download: https://zenodo.org/records/17143420. Blade and vein outlines are used to extract leaves and create a pre-segmented leaf on a background in a 512x512 png image for training. From the extracted contour of the leaf, an aligned radial ECT is created as a second channel to predict the vein mask. The corresponding vein ECT is also used as an auxillary during training for predicting the vein mask. Inference is intended for nearly 25,000 pre-segmented grapevine leaves stored as 512x512 RGBA images segmented in the alpha channel. These images for inference are not included in this download, and the folder `FINAL_MASKS` can be downloaded and placed in the project folder from here: https://zenodo.org/records/16883403.