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README.md

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+---
+license: mit
+library_name: rfdetr
+tags:
+  - plant-disease
+  - disease-detection
+  - agriculture
+  - computer-vision
+  - object-detection
+  - rf-detr
+datasets:
+  - plant-disease-faxnj
+metrics:
+  - map
+pipeline_tag: object-detection
+---
+
+# CropScan - Plant Disease Detection Model
+
+CropScan is an RF-DETR model fine-tuned for plant disease detection. It identifies and localizes disease regions on plant leaves.
+
+## Model Details
+
+- **Model Architecture**: RF-DETR (medium)
+- **Task**: Object Detection / Disease Localization
+- **Performance**: mAP@50: 0.502
+- **Training**: Fine-tuned on plant disease dataset
+
+## Usage
+
+```python
+from rfdetr import RFDETRBase
+
+model = RFDETRBase()
+model.load_state_dict(torch.load("checkpoint_best_total.pth"))
+```
+
+## Training Data
+
+This model was trained on the Plant Disease dataset from Roboflow Universe.
+
+```bibtex
+@misc{plant-disease-faxnj_dataset,
+    title = { Plant disease Dataset },
+    type = { Open Source Dataset },
+    author = { Project },
+    howpublished = { \url{ https://universe.roboflow.com/project-oklwn/plant-disease-faxnj } },
+    url = { https://universe.roboflow.com/project-oklwn/plant-disease-faxnj },
+    journal = { Roboflow Universe },
+    publisher = { Roboflow },
+    year = { 2024 },
+    month = { feb },
+}
+```
+
+## Intended Use
+
+- Plant disease detection in agricultural applications
+- Research on plant pathology
+- Integration with segmentation models (e.g., SAM2) for precise mask generation
+
+## Limitations
+
+- Trained primarily on PlantVillage-style images
+- Best performance on individual leaf images with clear backgrounds
+- May require SAM2 integration for precise segmentation masks