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--- |
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license: apache-2.0 |
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language: |
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- en |
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base_model: |
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- Ultralytics/YOLOv5 |
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--- |
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# YOLOv5 Weed Detection |
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This is a Gradio application for detecting weeds in images using a fine-tuned YOLOv5 model trained on a Weed-AI dataset. |
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## How to Use |
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1. Upload an image using the interface. |
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2. The model will process the image and display the annotated image with detected weeds and their bounding boxes. |
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3. A text output will summarize the detected objects, including their class and confidence score. |
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## Model Information |
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The model used in this application is a YOLOv5 model fine-tuned on the [Northern WA Wheatbelt Blue Lupins](https://weed-ai.sydney.edu.au/datasets/9df290f4-a29b-44b2-9de6-24bca1cee846) dataset from Weed-AI. |
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## Files |
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- `app.py`: The Python script containing the Gradio application code. |
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- `requirements.txt`: Lists the Python dependencies. |
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- `best.pt`: The trained YOLOv5 model weights (this will be uploaded separately). |
