yolov8-使用yolov8实现火灾检测算法.zip

<div align="center"> # YOLOv8 Streamlit APP ## Introduction This repository supply a user-friendly interactive interface for [YOLOv8](https://github.com/ultralytics/ultralytics) and the interface is powered by [Streamlit](https://github.com/streamlit/streamlit). It could serve as a resource for future reference while working on your own projects. ## Features - Feature1: Object detection task. - Feature2: Multiple detection models. `yolov8n`, `yolov8s`, `yolov8m`, `yolov8l`, `yolov8x` - Feature3: Multiple input formats. `Image`, `Video`, `Webcam` ## Interactive Interface ### Image Input Interface  ### Video Input Interface  ### Webcam Input Interface  ## Installation ### Create a new conda environment ```commandline # create conda create -n yolov8-streamlit python=3.8 -y # activate conda activate yolov8-streamlit ``` ### get the pro ### Install packages ```commandline # yolov8 dependencies pip install ultralytics # Streamlit dependencies pip install streamlit ``` ### Download Pre-trained YOLOv8 Detection Weights Create a directory named `weights` and create a subdirectory named `detection` and save the downloaded YOLOv8 object detection weights inside this directory. The weight files can be downloaded from the table below. | Model | size<br><sup>(pixels) | mAP<sup>val<br>50-95 | Speed<br><sup>CPU ONNX<br>(ms) | Speed<br><sup>A100 TensorRT<br>(ms) | params<br><sup>(M) | FLOPs<br><sup>(B) | | ------------------------------------------------------------------------------------ | --------------------- | -------------------- | ------------------------------ | ----------------------------------- | ------------------ | ----------------- | | [YOLOv8n](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8n.pt) | 640 | 37.3 | 80.4 | 0.99 | 3.2 | 8.7 | | [YOLOv8s](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8s.pt) | 640 | 44.9 | 128.4 | 1.20 | 11.2 | 28.6 | | [YOLOv8m](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8m.pt) | 640 | 50.2 | 234.7 | 1.83 | 25.9 | 78.9 | | [YOLOv8l](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8l.pt) | 640 | 52.9 | 375.2 | 2.39 | 43.7 | 165.2 | | [YOLOv8x](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8x.pt) | 640 | 53.9 | 479.1 | 3.53 | 68.2 | 257.8 | ## Run ```commandline streamlit run app.py ``` Then will start the Streamlit server and open your web browser to the default Streamlit page automatically.