https://github.com/emingenc/yolo-pi-cctv
yolov5 pi cctv integration
https://github.com/emingenc/yolo-pi-cctv
deep-learning raspberry-pi yolov5
Last synced: 12 months ago
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yolov5 pi cctv integration
- Host: GitHub
- URL: https://github.com/emingenc/yolo-pi-cctv
- Owner: emingenc
- License: agpl-3.0
- Created: 2021-09-16T13:54:42.000Z (almost 5 years ago)
- Default Branch: master
- Last Pushed: 2021-09-17T07:00:12.000Z (almost 5 years ago)
- Last Synced: 2023-08-01T11:44:21.022Z (almost 3 years ago)
- Topics: deep-learning, raspberry-pi, yolov5
- Language: Python
- Homepage:
- Size: 61.5 MB
- Stars: 0
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
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README
# pi-cctv
1) Setup your raspberry pi with [Raspberry Pi instructions](https://github.com/novitai/setuptools/tree/master/raspberrypi)
2) Enable your camera
* Make sure your camera connected to your Raspberry Pi :
```sudo raspi-config```
select interface options and enable your camera. It will ask you to reboot if not reboot device with:
```sudo reboot```
3) Clone this repo :
* Before clone install git:
```sudo apt update```
```sudo apt install git```
```git clone https://github.com/emingenc/pi-cctv.git```
```cd pi-cctv```
4) Install requirements:
* before installinng requirements.txt create venv:
4a. Install python3-venv:
```sudo apt-get install python3-venv```
4b. Create venv:
```python3 -m venv venv```
4c. Activate venv:
```source venv/bin/activate```
4d. Install requirements.txt:
```pip3 install -r requirements.txt```
5) Auto-start at boot:
* open etc/profile:
```sudo nano /etc/profile```
* add these commands end of the file
```source /home/pi/pi-cctv/venv/bin/activate```
```cd /home/pi/pi-cctv```
```python3 /home/pi/pi-cctv/main.py &```
a. ctrl+x
b. save(press y)
c. press Enter to save file
6) apt-get requirements for image compression:
* install:
```sudo apt-get install libopenjp2-7 libtiff5```
7) Torch and torchvision install to pi:
* you can clone this repo and install via wheel:
```git clone https://github.com/Kashu7100/pytorch-armv7l ```
```cd pytorch-armv7l```
```pip3 install torch-1.7.0a0-cp37-cp37m-linux_armv7l.whl```
```pip3 install torchvision-0.8.0a0+45f960c-cp37-cp37m-linux_armv7l.whll```
note detect.py will not run unless you dont comment out torch and torchvision from requiremnts.txt.
# Custom object detection
1) Train a model with dataset [Check this tutorial](https://github.com/ultralytics/yolov5/wiki/Train-Custom-Data)
2) After you trained a model copy model weights which extension is .pt to this repo.
3) Change weight parameter with weight you just copied in main.py detected_objects detect function
4) run your main.py with object class name that you want to send post request to the server.
```python3 camera.py --file-name --obj ```