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---
tags:
- vision
- image-classification
datasets:
- OttoYu/Treecondition
widget:
- src: https://bit.ly/3KbaDNI
example_title: Canker Diseases
- src: https://bit.ly/40FN317
example_title: Bacterial canker
- src: https://bit.ly/3LYSGn6
example_title: Citrus canker
- src: https://www.elitetreecare.com/wp-content/uploads/2016/06/black-knot.jpg
example_title: Black knot
- src: https://gtr-arbor.com.hk/wp-content/uploads/2015/01/fungi2-5.jpg
example_title: Fungi
- src: https://gtr-arbor.com.hk/wp-content/uploads/2011/05/insectA2-2.jpg
example_title: Termite
co2_eq_emissions:
emissions: 1.3038362907488008
---
# 🌳 Tree Condition Classification 樹況分類 (bilingual)
### Model Description
This online application covers 22 most typical tree disease over 290+ images. If you find any trees that has hidden injures, you can classifies with our model and report the tree condition via this form (https://rb.gy/c1sfja). 此在線程式涵蓋22種官方部門樹況分類的標準，超過290張圖像。如果您發現任何樹木有隱傷，您可以使用我們的模型進行分類並通過此表格報告樹木狀況。
- **Developed by:** Yu Kai Him Otto
- **Shared via:** Huggingface.co
- **Model type:** Opensource
## Uses
You can use the this model for tree condition image classification.
## Training Details
### Training Data
- Loss: 0.355
- Accuracy: 0.852
- Macro F1: 0.787
- Micro F1: 0.852
- Weighted F1: 0.825
- Macro Precision: 0.808
- Micro Precision: 0.852
- Weighted Precision: 0.854
- Macro Recall: 0.811
- Micro Recall: 0.852
- Weighted Recall: 0.852 |