| --- |
| license: apache-2.0 |
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| |
| # 🍓 Auto-Strawberry: Strawberry Daughter Plant Dataset and Pretrained Models |
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| Welcome to the **Auto-Strawberry** project! This repository hosts the **strawberry daughter plant sample dataset** and **pretrained deep learning models** developed for automated estimation of plant growth attributes using stereo vision and deep learning techniques. |
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| ## 📦 Dataset Overview |
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| The **Strawberry Daughter Plant Dataset** contains: |
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| - **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. |
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|
| ### Dataset Structure: |
| ```plaintext |
| - cam0/ |
| - cam1/ |
| - annotations.json |
| ``` |
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| ## 🧠 Pretrained Models |
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| ### Available Backbone Models: |
| - **ResNet34** |
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| ### 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. |
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| ## 📥 Download and Usage |
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| ### 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 |
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| ## 📜 License |
| This project is licensed under the **Apache 2.0 License**. |
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| ## 📬 Contact |
| - **Author:** Sina Baghbanijam |
| - **Email:** [sbaghba@ncsu.edu](mailto:sbaghba@ncsu.edu) |
| - **Project Repository:** [GitHub Link](https://github.com/sbaghba/Auto-Strawberry) |
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| **🌟 If you use this dataset or models in your research, please cite this repository!** |
