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https://github.com/LitChi-bit/YOLOv5-6.0-GUI
This is a recent project of mine, and it will not necessarily be maintained in the later stage, this is just a memorial.
https://github.com/LitChi-bit/YOLOv5-6.0-GUI
Last synced: 12 days ago
JSON representation
This is a recent project of mine, and it will not necessarily be maintained in the later stage, this is just a memorial.
- Host: GitHub
- URL: https://github.com/LitChi-bit/YOLOv5-6.0-GUI
- Owner: LitChi-bit
- License: mit
- Created: 2023-04-02T08:31:21.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2023-04-20T00:48:46.000Z (about 1 year ago)
- Last Synced: 2024-02-29T10:35:16.110Z (4 months ago)
- Language: Python
- Size: 30 MB
- Stars: 4
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Lists
- awesome-yolo-object-detection - LitChi-bit/YOLOv5-6.0-GUI - bit/YOLOv5-6.0-GUI?style=social"/> : Qt-GUI implementation of the YOLOv5 algorithm (ver.6). (Applications)
README
## YOLOv5-GUI
---
# 🎈YOLOv5(ver.6)的Qt-GUI实现
## 🎈Qt-GUI implementation of the YOLOv5(ver.6).
---
>*☢ 注：是在已有基础上进行的改进，旨在增加兼容性。如有问题请 Pull requests。
权重文件暂时不公开，需使用官方提供的权重或自己训练的权重！！！
☢ Note: It is an improvement on the existing one and is intended to increase compatibility.
The weight file is temporarily not public, and you need to use the weights provided by the official or the weights you train!!!*
✦ 基于YOLOv5的v5版本和v6版本及 ***Javacr*** 大佬的UI逻辑进行编写。
✦ 提供深色和浅色两个UI。(深色版本显示不理想，最近没有时间去完善，想用也可以用，但是不建议用)
Provides dark and light UI.
## Installation and use
0.Fetching projects from git
```bash
git clone https://github.com/sakkios/YOLOv5-6.0-GUI.git
```
1.Installation environment
```bash
pip install -r requirements.txt
```
2.Launching applications
```bash
python run.py
```
## Attention
GUI默认为浅色模式，你也可以通过下述方法将程序界面调整为深色模式。
The GUI defaults to light mode, and you can also adjust the program interface to dark mode by using the above methods.
```bash
#open python file: run.py
import main_ui_light
##Modify the code to -->
import main_ui_dark
```
### 下载预训练权重
Pretrained Checkpoints
| Model | size
(pixels) | mAPval
50-95 | mAPval
50 | Speed
CPU b1
(ms) | Speed
V100 b1
(ms) | Speed
V100 b32
(ms) | params
(M) | FLOPs
@640 (B) |
| ----------------------------------------------------------------------------------------------- | --------------------- | -------------------- | ----------------- | ---------------------------- | ----------------------------- | ------------------------------ | ------------------ | ---------------------- |
| [YOLOv5n](https://github.com/ultralytics/yolov5/releases/download/v7.0/yolov5n.pt) | 640 | 28.0 | 45.7 | **45** | **6.3** | **0.6** | **1.9** | **4.5** |
| [YOLOv5s](https://github.com/ultralytics/yolov5/releases/download/v7.0/yolov5s.pt) | 640 | 37.4 | 56.8 | 98 | 6.4 | 0.9 | 7.2 | 16.5 |
| [YOLOv5m](https://github.com/ultralytics/yolov5/releases/download/v7.0/yolov5m.pt) | 640 | 45.4 | 64.1 | 224 | 8.2 | 1.7 | 21.2 | 49.0 |
| [YOLOv5l](https://github.com/ultralytics/yolov5/releases/download/v7.0/yolov5l.pt) | 640 | 49.0 | 67.3 | 430 | 10.1 | 2.7 | 46.5 | 109.1 |
| [YOLOv5x](https://github.com/ultralytics/yolov5/releases/download/v7.0/yolov5x.pt) | 640 | 50.7 | 68.9 | 766 | 12.1 | 4.8 | 86.7 | 205.7 |
| | | | | | | | | |
| [YOLOv5n6](https://github.com/ultralytics/yolov5/releases/download/v7.0/yolov5n6.pt) | 1280 | 36.0 | 54.4 | 153 | 8.1 | 2.1 | 3.2 | 4.6 |
| [YOLOv5s6](https://github.com/ultralytics/yolov5/releases/download/v7.0/yolov5s6.pt) | 1280 | 44.8 | 63.7 | 385 | 8.2 | 3.6 | 12.6 | 16.8 |
| [YOLOv5m6](https://github.com/ultralytics/yolov5/releases/download/v7.0/yolov5m6.pt) | 1280 | 51.3 | 69.3 | 887 | 11.1 | 6.8 | 35.7 | 50.0 |
| [YOLOv5l6](https://github.com/ultralytics/yolov5/releases/download/v7.0/yolov5l6.pt) | 1280 | 53.7 | 71.3 | 1784 | 15.8 | 10.5 | 76.8 | 111.4 |
| [YOLOv5x6](https://github.com/ultralytics/yolov5/releases/download/v7.0/yolov5x6.pt)
+ [TTA] | 1280
1536 | 55.0
**55.8** | 72.7
**72.7** | 3136
- | 26.2
- | 19.4
- | 140.7
- | 209.8
- |
## Reference
ultralytics/yolov5
Javacr/PyQt5-YOLOv5