Update README.md

README.md

@@ -1,5 +1,93 @@
 ---
 license: apache-2.0
-base_model:
-- layoutparser/detectron2
----
+tags:
+  - object-detection
+  - document-layout-analysis
+  - historical-documents
+  - layoutparser
+  - detectron2
+  - mask-rcnn
+language:
+  - sv
+pipeline_tag: object-detection
+---
+
+# Historical Document Layout Detection Model
+
+A fine-tuned Mask R-CNN model (via LayoutParser/Detectron2) for detecting layout
+elements in historical Swedish Medical journal pages.
+
+## Model Details
+
+- **Model type:** Mask R-CNN (ResNet backbone)
+- **Framework:** Detectron2 / LayoutParser
+- **Fine-tuned for:** Historical document layout analysis
+- **Language of source documents:** Swedish
+
+## Label Map
+
+| ID | Label             |
+|----|-------------------|
+| 0  | Advertisement     |
+| 1  | Author            |
+| 2  | Header or Footer  |
+| 3  | Image             |
+| 4  | List              |
+| 5  | Page Number       |
+| 6  | Table             |
+| 7  | Text              |
+| 8  | Title             |
+
+## Usage
+
+### Installation
+
+Follow instructions at: https://detectron2.readthedocs.io/en/latest/tutorials/install.html
+
+### Inference
+
+import cv2
+import layoutparser as lp
+
+# Configuration
+model_config_path = "config_mask_rcnn_resized.yaml"
+model_path = "model_final_LP.pth"
+label_map = {
+    0: "advertisement",
+    1: "author",
+    2: "header_or_footer",
+    3: "image",
+    4: "list",
+    5: "page_no",
+    6: "table",
+    7: "text",
+    8: "title",
+}
+
+# Load model
+model = lp.models.Detectron2LayoutModel(
+    config_path=model_config_path,
+    model_path=model_path,
+    extra_config=["MODEL.ROI_HEADS.SCORE_THRESH_TEST", 0.8],
+    label_map=label_map,
+)
+
+# Load and process image
+image = cv2.imread("<path_to_image>")
+image = image[..., ::-1]  # BGR to RGB
+
+# Detect layout
+layout = model.detect(image)
+
+# Print detected elements
+for block in layout:
+    print(f"Type: {block.type}, Score: {block.score:.3f}, Box: {block.coordinates}")
+
+# Visualize
+import matplotlib.pyplot as plt
+
+viz = lp.draw_box(image, layout, box_width=3, show_element_type=True)
+plt.figure(figsize=(12, 16))
+plt.imshow(viz)
+plt.axis("off")
+plt.show()