readme updated

README.md

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 ---
 license: cc-by-4.0
+tags:
+  - yolov5
+  - yolo
+  - digital-humanities
+  - object-detection
+  - computer-vision
+  - document-layout-analysis
 ---
+
+# What's YOLOv5
+
+YOLOv5 is an open-source object detection model released by [Ultralytics](https://ultralytics.com/), on [Github](https://github.com/ultralytics/yolov5).
+
+# DataCatalogue (or DataCat)
+
+(DataCatalogue)[https://github.com/DataCatalogue] is a research projet jointly led by Inria, the Bibliothèque nationale de France (National Library of France) and the Institut national d'histoire de l'art (National Institute of Art History).
+
+It aims at restructuring OCR-ed auction sale catalogs kept in France national collections into TEI-XML, using machine learning solutions.
+
+# DataCat Yolov5
+
+We trained a YOLOv5 model on custom data to perform document layout analysis on auction sale catalogs. 
+
+The training set consists of **581 images**, annotated with **two classes**:
+* *title* (585 instances)
+* *entry* (it refers to a catalog entry) (5017 instances)
+
+59 images were used for validation.
+
+We reached: 
+| precision | recall | mAP_0.5 | mAP_0.5:0.95 |
+|---|---|---|---|
+| 0.99 | 0.99 | 0.98 | 0.75 |
+
+# Dataset
+
+The dataset is not released for the moment.
+
+## Demo
+
+An interactive demo is available on the following HugginFace Space: https://huggingface.co/spaces/HugoSchtr/DataCat_Yolov5
+
+## What's next
+
+The model performs well on our data and now needs to be incorporated into a dedicated pipeline for the research project.
+
+We also plan to train a new model on a larger training set in the near future.