Update readme.md

README.md

@@ -1,3 +1,66 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+tags:
+  - object-detection
+  - chart-understanding
+  - document-ai
+  - cascade-rcnn
+  - swin-transformer
+---
+
+# Chart Element Detector
+
+A chart element detection model based on
+[CACHED](https://github.com/pengyu965/ChartDete)
+(Context-Aware Chart Element Detection).
+
+## Model Details
+
+- **Architecture**: Cascade R-CNN + Swin Transformer + FPN
+- **Task**: Chart element detection and localization
+- **Classes**: 18 chart element classes
+- **Dataset**: PMC Chart Dataset
+- **COCO AP**: 0.729
+
+## Classes
+
+x_tick_label, y_tick_label, x_tick, y_tick,
+x_axis_title, y_axis_title, chart_title,
+legend_marker, legend_label, legend_title,
+value_label, mark_label, tick_grouping,
+plot_area, x_axis_area, y_axis_area,
+legend_area, others
+
+## Output Format
+```json
+{
+  "chart": [
+    {
+      "x1": 10.0,
+      "y1": 20.0,
+      "x2": 100.0,
+      "y2": 200.0,
+      "score": 0.95,
+      "class": "chart_title"
+    }
+  ]
+}
+```
+
+## Requirements
+```
+torch==1.13.1
+mmdet==2.28.2
+mmcv-full==1.7.0
+```
+
+## Citation
+```bibtex
+@inproceedings{yan2023cached,
+  title={CACHED: Context-Aware Chart Element Detection},
+  author={Yan, Pengyu and Ahmed, Saleem and Doermann, David},
+  booktitle={ICDAR},
+  year={2023}
+}
+```
+```