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