--- title: Object Detection Chatbot emoji: 🐢 colorFrom: blue colorTo: gray sdk: streamlit sdk_version: 1.38.0 app_file: app.py pinned: false --- Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference # 🔍 YOLOv8 Object Detection on Video This Streamlit app allows you to upload a video file and perform object detection using the YOLOv8 model. The app processes the video, detects objects, and provides a downloadable version of the video with bounding boxes around detected objects. ## 🚀 Live Demo Check out the live demo of the app on Hugging Face Spaces: 🔗 [YOLOv8 Object Detection App on Hugging Face](https://huggingface.co/spaces/datascientist22/object-detection-chatbot) ## 📂 GitHub Repository You can find the source code for this project on GitHub: 🔗 [GitHub Repository](https://github.com/mldatascientist23/Generative_AI_Projects) ## 📋 Features - **Upload Video**: Upload your video file in MP4, AVI, or MOV format. - **Object Detection**: Detects objects in the video using the YOLOv8 model. - **Processed Video Download**: Download the processed video with bounding boxes around detected objects. ## 🚀 How to Use 1. **Upload a Video**: Use the sidebar to upload a video file. 2. **Process the Video**: Click on the "Submit" button to start processing the video. 3. **Download the Result**: Once the processing is complete, download the processed video using the "Download Processed Video" button. ## 🛠️ Installation To run the app locally, follow these steps: 1. Clone the repository: ```bash git clone https://github.com/mldatascientist23/Generative_AI_Projects.git cd Generative_AI_Projects/YOLOv8_Object_Detection ``` 2. Install the required packages: ```bash pip install -r requirements.txt ``` 3. Run the Streamlit app: ```bash streamlit run app.py ``` ## 📦 Requirements - `streamlit` - `opencv-python-headless` - `ultralytics` - `numpy` ## 🧑‍💻 Created By This app was created by [Engr. Hamesh Raj](https://www.linkedin.com/in/datascientisthameshraj/). Feel free to connect with me on LinkedIn!