# Web_PCB
## Introdection
Implement the defect detection model deployed on cloud server based on YOLOv5, including online end detection and result demonstration; Two datasets are included (Peking University pcb defect dataset and DeepPCB dataset). The project is implemented by python-flask.
## Environment
```
pip install requirements.txt
```
## How to use
* Downlowd ```static.zip``` from [here](https://pan.baidu.com/s/1w4YmtiYxAX_yJSR_zCuuNg)(code:6s9z)
* Unzip ```static.zip``` to ```./```.
* Run ```python app.py```.
* Main Interface
<div align="center"><img src="./imgs/main.png" align="center" alt="preview" width="700" height="450" /></div>
* Defect Detection On The Cloud (Peking University PCB Defect Dataset)
<div align="center"><img src="./imgs/detection.png" align="center" alt="preview" width="700" height="450" /></div>
* Test result presentation (Peking University PCB Defect Dataset)
<div align="center"><img src="./imgs/pkpcb.png" align="center" alt="preview" width="500" height="600" /></div>
* Test result presentation (DeepPCB dataset)
<div align="center"><img src="./imgs/deeppcb.png" align="center" alt="preview" width="600" height="600" /></div>
## Contact
Kang Qing
Biometrics and Intelligence Perception Lab
College of Automation Science and Engineering
South China University of Technology
Wushan RD.,Tianhe District,Guangzhou,P.R.China,510641
auqkang@mail.scut.edu.cn
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基于YOLOv5部署在云服务器上的缺陷检测模型
共61个文件
pyc:29个
py:19个
png:4个
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2024-05-16
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实现基于YOLOv5部署在云服务器上的缺陷检测模型,包括在线终端检测和结果演示;包括两个数据集(北京大学pcb缺陷数据集和DeepPCB数据集)。该项目由 python-flask 实现。 环境 pip install requirements.txt
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Web_PCB-main.zip (61个子文件)
Web_PCB-main
app.json 167B
app.py 2KB
utils
__init__.py 476B
loss.py 9KB
augmentations.py 11KB
metrics.py 14KB
autoanchor.py 7KB
general.py 34KB
downloads.py 6KB
plots.py 20KB
datasets.py 44KB
callbacks.py 2KB
__pycache__
downloads.cpython-36.pyc 4KB
general.cpython-37.pyc 30KB
plots.cpython-36.pyc 18KB
general.cpython-36.pyc 30KB
datasets.cpython-36.pyc 35KB
torch_utils.cpython-36.pyc 12KB
plots.cpython-37.pyc 18KB
datasets.cpython-37.pyc 35KB
augmentations.cpython-37.pyc 9KB
downloads.cpython-37.pyc 4KB
callbacks.cpython-37.pyc 2KB
autoanchor.cpython-37.pyc 6KB
autobatch.cpython-37.pyc 2KB
metrics.cpython-37.pyc 11KB
augmentations.cpython-36.pyc 9KB
torch_utils.cpython-37.pyc 12KB
__init__.cpython-37.pyc 592B
__init__.cpython-36.pyc 544B
autoanchor.cpython-36.pyc 6KB
metrics.cpython-36.pyc 11KB
loss.cpython-37.pyc 6KB
torch_utils.py 13KB
templates
index_2.html 563KB
index_1.html 2.5MB
index.html 3KB
model.py 9KB
create_html.py 2KB
runtime.txt 12B
requirements.txt 96B
models
__init__.py 0B
tf.py 20KB
DeepPCB.pt 13.82MB
common.py 29KB
PK_PCB.pt 13.82MB
experimental.py 4KB
__pycache__
experimental.cpython-36.pyc 5KB
yolo.cpython-37.pyc 12KB
yolo.cpython-36.pyc 12KB
common.cpython-36.pyc 28KB
experimental.cpython-37.pyc 5KB
__init__.cpython-37.pyc 182B
__init__.cpython-36.pyc 134B
common.cpython-37.pyc 28KB
yolo.py 15KB
imgs
main.png 58KB
detection.png 443KB
deeppcb.png 85KB
pkpcb.png 201KB
README.md 1KB
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