---
title: Objectdetectionv1
emoji: 🦀
colorFrom: gray
colorTo: indigo
sdk: gradio
sdk_version: 5.42.0
app_file: app.py
pinned: false
license: apache-2.0
---



# YOLOv5 Weed Detection

This is a Gradio application for detecting weeds in images using a fine-tuned YOLOv5 model trained on a Weed-AI dataset.

## How to Use

1.  Upload an image using the interface.
2.  The model will process the image and display the annotated image with detected weeds and their bounding boxes.
3.  A text output will summarize the detected objects, including their class and confidence score.

## Model Information

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.

## Files

-   `app.py`: The Python script containing the Gradio application code.
-   `requirements.txt`: Lists the Python dependencies.
-   `best.pt`: The trained YOLOv5 model weights (this will be uploaded separately).

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference