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README.md

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+# OIV Leaf Disc Phenotyping
+
+Companion repository for the article 
+"Phenotyping grapevine resistance to downy mildew: deep learning as a promising tool to assess sporulation and necrosis" found [Here](https://link.springer.com/article/10.1186/s13007-024-01220-4?utm_source=rct_congratemailt&utm_medium=email&utm_campaign=oa_20240613&utm_content=10.1186/s13007-024-01220-4)
+
+## Folder Structure
+
+### checkpoints
+Contains checkpoint files for leaf disc detector and OIV 452-1 scorer.
+
+### data
+Contains all datasets data in CSV format
+
+### images
+Contains all images in three different folders:
+- leaf_discs contains full leaf discs
+- leaf_patches contains extracted patches
+- plates contains full plate images
+
+### src
+Contains source code under two formats:
+- *.py files contain base functionality and classes
+- *.ipynb files contain code to reproduce the article data
+
+## Notebooks
+
+### leaf_patch_extractor.ipynb
+This notebook shows the process that goes from plate images to leaf patches
+
+### leaf_patch_annotation.ipynb
+Generates an user interface to annotate leaf patches
+
+### leaf_patch_oiv_predictor.ipynb
+Step by sterp tutorial to predict OIV 452-1 scores from extracted leaf patches
+
+### leaf_patch_gen_diff.ipynb
+Notebook that details the procedure to compare model predictions to human scores
+
+### repo_manager.ipynb
+Utility notebook to create this repository