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README.md

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-license: apache-2.0
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+---
+license: apache-2.0
+---
+
+# 🍓 Auto-Strawberry: Strawberry Daughter Plant Dataset and Pretrained Models
+
+Welcome to the **Auto-Strawberry** project! This repository hosts the **strawberry daughter plant dataset** and **pretrained deep learning models** developed for automated estimation of plant growth attributes using stereo vision and deep learning techniques.
+
+## 📦 Dataset Overview
+
+The **Strawberry Daughter Plant Dataset** contains:
+
+- **Multi-view RGB images:** 6 views per sample captured using a stereo vision camera setup (`cam0` and `cam1`).
+- **Ground truth labels:**
+  - Total Leaf Area
+  - Fresh Mass
+  - Largest Petiole Length
+  - Average Crown Diameter
+- **Format:** Images in `.jpg` and labels stored in a JSON file.
+
+### Dataset Structure:
+```plaintext
+- cam0/
+- cam1/
+- annotations.json
+```
+
+## 🧠 Pretrained Models
+
+### Available Backbone Models:
+- **ResNet34**
+- **Vision Transformer (ViT-B-16)**
+- **EfficientNet B0**
+
+### Model Weights:
+Each model was trained using the **strawberry dataset** for the regression task of estimating leaf area and other growth metrics. The weights provided here can be used for inference and fine-tuning.
+
+## 📥 Download and Usage
+
+### Hugging Face Integration:
+```bash
+pip install huggingface_hub
+```
+
+```python
+from huggingface_hub import hf_hub_download
+
+# Download the model from Hugging Face Hub
+hf_hub_download(repo_id="sinabjam/auto-strawberry", filename="desired_file_name.pth")
+```
+## 🎯 Applications
+- Plant phenotyping
+- Automated growth monitoring
+- Precision agriculture insights
+
+## 📜 License
+This project is licensed under the **Apache 2.0 License**.
+
+## 📬 Contact
+- **Author:** Sina Baghbanijam
+- **Email:** [sbaghba@ncsu.edu](mailto:sbaghba@ncsu.edu)
+- **Project Repository:** [GitHub Link](https://github.com/sbaghba/Auto-Strawberry)
+
+**🌟 If you use this dataset or models in your research, please cite this repository!**