https://github.com/JackDance/YOLOv8-streamlit-app

🔥🔥🔥 Use streamlit framework to increase yolov8 front-end page interaction function
https://github.com/JackDance/YOLOv8-streamlit-app

classfication detection pose-estimation streamlit tracking yolov8

Last synced: 3 months ago
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🔥🔥🔥 Use streamlit framework to increase yolov8 front-end page interaction function

• Host: GitHub
• URL: https://github.com/JackDance/YOLOv8-streamlit-app
• Owner: JackDance
• Created: 2023-05-15T03:32:44.000Z (over 1 year ago)
• Default Branch: master
• Last Pushed: 2023-05-22T01:44:02.000Z (over 1 year ago)
• Last Synced: 2024-08-02T01:25:15.258Z (6 months ago)
• Topics: classfication, detection, pose-estimation, streamlit, tracking, yolov8
• Language: Python
• Homepage:
• Size: 7.9 MB
• Stars: 67
• Watchers: 1
• Forks: 23
• Open Issues: 3
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

• awesome-yolo-object-detection - JackDance/YOLOv8-streamlit-app - streamlit-app?style=social"/> : 🔥🔥🔥 Use streamlit framework to increase yolov8 front-end page interaction function. "知乎「Mr.Luyao」《[深度学习/机器学习项目的前端展示利器--Streamlit](https://zhuanlan.zhihu.com/p/630029493)》"。 (Applications)
• awesome-yolo-object-detection - JackDance/YOLOv8-streamlit-app - streamlit-app?style=social"/> : 🔥🔥🔥 Use streamlit framework to increase yolov8 front-end page interaction function. "知乎「Mr.Luyao」《[深度学习/机器学习项目的前端展示利器--Streamlit](https://zhuanlan.zhihu.com/p/630029493)》"。 (Applications)

README

        



# 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

![image_input_demo](https://github.com/JackDance/YOLOv8-streamlit-app/blob/master/pic_bed/image_input_demo.png)

### Video Input Interface

![video_input_demo](https://github.com/JackDance/YOLOv8-streamlit-app/blob/master/pic_bed/video_input_demo.png)

### Webcam Input Interface

![webcam_input_demo](https://github.com/JackDance/YOLOv8-streamlit-app/blob/master/pic_bed/webcam_input_demo.png)

## Installation

### Create a new conda environment

```commandline

# create

conda create -n yolov8-streamlit python=3.8 -y

# activate

conda activate yolov8-streamlit

```

### Clone repository

```commandline

git clone https://github.com/JackDance/YOLOv8-streamlit-app

```

### 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
(pixels) | mAPval
50-95 | Speed
CPU ONNX
(ms) | Speed
A100 TensorRT
(ms) | params
(M) | FLOPs
(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.

## TODO List

- Add `Tracking` capability.

- Add `Classification` capability.

- Add `Pose estimation` capability.

***

If you also like this project, you may wish to give a `star` (^.^)✨ . If any questions, please raise `issue`~