# Smart-Security-Camera

**Repository Path**: cxxowl/Smart-Security-Camera

## Basic Information

- **Project Name**: Smart-Security-Camera
- **Description**: IoT security camera running open-cv for object detection 
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-04-10
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Smart-Security-Camera
IoT Raspberry Pi security camera running open-cv for object detection. The camera will send an email with an image of any objects it detects. It also runs a server that provides a live video stream over the internet.

[Watch the original video here](https://youtu.be/Y2QFu-tTvTI)

## Setup

This project uses a Raspberry Pi Camera to stream video. Before running the code, make sure to configure the raspberry pi camera on your device.

Open the terminal and run

```
sudo raspi-config
```

Select `Interface Options`, then `Pi Camera` and toggle on. Press `Finish` and exit.

You can verify that the camera works by running

```
raspistill -o image.jpg
```
which will save a image from the camera in your current directory. You can open up the file inspector and view the image.

## Installing Dependencies

This project uses openCV to detect objects in the video feed. You can install openCV by using the following [tutorial](http://www.pyimagesearch.com/2016/04/18/install-guide-raspberry-pi-3-raspbian-jessie-opencv-3/). I used the Python 2.7 version of the tutorial.

The installation took almost 8 hours (!!) on my Raspberry Pi Zero, but it would be considerably faster on a more powerful board like the Raspberry Pi 3.

The tutorial will prompt you to create a virtual environment. Make sure you are using the virtual environment by typing the following commands

```bash
source ~/.profile
workon cv
```

Next, navigate to the repository directory

```
cd Smart-Security-Camera
```

and install the dependencies for the project

```
pip install -r requirements.txt
```

*Note: If you're running python3, you'll have to change the import statements at the top of the mail.py file*

```
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
from email.mime.image import MIMEImage
```
*and change your print statements from quotes to parenthesis*

```
print "" => print()
```

## Customization

To get emails when objects are detected, you'll need to make a couple modifications to the `mail.py` file.

Open `mail.py` with vim `vim mail.py`, then press `i` to edit. Scroll down to the following section

```
# Email you want to send the update from (only works with gmail)
fromEmail = 'myemail@gmail.com'
fromEmailPassword = 'password1234'

# Email you want to send the update to
toEmail = 'anotheremail@gmail.com'
```
and replace with your own email/credentials. The `mail.py` file logs into a gmail SMTP server and sends an email with an image of the object detected by the security camera. 

Press `esc` then `ZZ` to save and exit.

You can also modify the `main.py` file to change some other properties.

```
email_update_interval = 600 # sends an email only once in this time interval
video_camera = VideoCamera(flip=True) # creates a camera object, flip vertically
object_classifier = cv2.CascadeClassifier("models/fullbody_recognition_model.xml") # an opencv classifier
```
Notably, you can use a different object detector by changing the path `"models/fullbody_recognition_model.xml"` in `object_classifier = cv2.CascadeClassifier("models/fullbody_recognition_model.xml")`.

to a new model in the models directory.

```
facial_recognition_model.xml
fullbody_recognition_model.xml
upperbody_recognition_model.xml
```

## Running the Program

Run the program

```
python main.py
```

You can view a live stream by visiting the ip address of your pi in a browser on the same network. You can find the ip address of your Raspberry Pi by typing `ifconfig` in the terminal and looking for the `inet` address. 

Visit `<raspberrypi_ip>:5000` in your browser to view the stream.

Note: To view the live stream on a different network than your Raspberry Pi, you can use [ngrok](https://ngrok.com/) to expose a local tunnel. Once downloaded, run ngrok with `./ngrok http 5000` and visit one of the generated links in your browser.

Note: The video stream will not start automatically on startup. To start the video stream automatically, you will need to run the program  from your `/etc/rc.local` file see this [video](https://youtu.be/51dg2MsYHns?t=7m4s) for more information about how to configure that.