使用streamlit部署yolov9目标检测模型python源码+运行说明.zip

# Object Detection using YoloV9 and Streamlit Python ## Folder contents The project **streamlit-object-detection-with-yolov9** contains one source main file [streamlit_app.py](streamlit_app.py). I used **yolov9c.pt** model. You can download the model [here](https://github.com/ultralytics/assets/releases/download/v8.1.0/yolov9c.pt), or you can see more from [Ultralytics YOLOV9](https://docs.ultralytics.com/models/yolov9/#performance-on-ms-coco-dataset). Below is short explanation of remaining files in the project folder. ``` ├── app.py ├── streamlit_app.py This is the file object detection using YoloV9 and Streamlit └── README.md This is the file you are currently reading ``` ## How to run Clone this repository ```sh git clone https://github.com/fuadidendi/streamlit-object-detection-yolov9.git ``` Go to the directory and run by ```sh streamlit run streamlit_app.py ``` ## Preview ### Local Video Source Local video selected as video source. Make sure there is a camera connected to your device. Just toggle on the Start Video and the real-time object detection from your camera will be begin. ### Youtube Video Source Youtube video is selected as the video source, you must enter the YouTube video link. Here below preview when you use youtube video as video source. I used No Copyright Video [Tokyo Walk - Pedestrian | Free Footage Stock Video](https://www.youtube.com/watch?v=OUlP6JLVKYo)