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https://github.com/HackerShackOfficial/Smart-Security-Camera

IoT security camera running open-cv for object detection 📹
https://github.com/HackerShackOfficial/Smart-Security-Camera

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IoT security camera running open-cv for object detection 📹

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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 = '[email protected]'

fromEmailPassword = 'password1234'



# Email you want to send the update to

toEmail = '[email protected]'

```

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 `: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.