DIY: A Robot That Can Dream!

sudo  apt-get update
sudo apt-get upgrade
sudo apt-get install build-essential cmake pkg-config 
sudo apt-get install libjpeg-dev libtiff5-dev libjasper-dev libpng12-dev 
sudo apt-get install libavcodec-dev libavformat-dev libswscale-dev libv4l-dev  
sudo apt-get install libxvidcore-dev libx264-dev
sudo apt-get install libgtk2.0-dev libgtk-3-dev  
sudo apt-get install libatlas-base-dev gfortran

 sudo nano /etc/dphys-swapfile

sudo /etc/init.d/dphys-swapfile stop  
sudo /etc/init.d/dphys-swapfile start
sudo pip3 install opencvsudo pip3 install numpy
wget https://bootstrap.pypa.io/get-pip.py
pip install dlib

Now, we will install the Face recoginition library. To do so, run the following command in the terminal:

 sudo  pip3 install face recoginition

Run the sudo apt-get update command again. Now, our basic setup for emotion recognition is done. 

 Deep dream requirements/setup

For deep dream, we need to install the following modules in Python.  

• Caffe
• Protobuf (also known as Protocol Buffers)
• PsyCam

Open your Linux terminal and then run the above commands to install the modules (Refer to Fig 5, Fig 6, Fig 7, Fig 8, Fig 9, Fig 10, Fig 11). 

You can also follow this link for deep dream installation on Raspberry Pi.

We have now completed the basic setup of the libraries so now, let’s write the code for real-time Face recognition. 

Coding

First, we need to download OpenCV, OpenCV contribution, and the Face recognition library folder. To do so, open the terminal window and then run the following commands in the terminal:

git colone https://github.com/opencv/opencv

git colone https://github.com/opencv/opencv_contrib

This is to recognize the person in front of the robot (known or unknown). In this code, we will import 3 modules: face recognition, cv2, and numpy. We will create different arrays for recognizing faces and names. Make sure to write the image file name of that member for correct face recognition.

In the next part of the code, we will try to match the face that the camera has captured with the array of known faces. If the face matches, then the code will run the espeak synthesizer to speak the person’s name using the syntax ‘espeak.synth ()’ as in the pic below (See Fig.12)

You can refer to the Face Recognition Robot project for setup the robot head and understanding the face recognition system in a better way.

Preparing  Dreaming Code

Now, let’s do a deep dream code setting.

Download the deep dream pycsam library using the following command:

git clone https://github.com/JoBergs/PsyCam

Then open the PsyCam folder and change the file path for dream creating image in utlities.py to the same path where we save the captured frame of emotionrecog.py image. Now in the PsyCam folder, create a new Python file and then create a script that runs the testpsycam.py file in certain intervals of time and then makes it go on sleep mode ie off/on.

To see the dream image created by the robot, open the dream folder that is situated in the psycam folder.

Our coding is now done.

Connect the camera to Raspberry Pi and the OLED display with Arduino for eye motion, as given in Part 1 of this project. 

Connection

Connect the Raspberry Pi Type-C USB port with 5V cable. After that, connect the Raspberry Pi camera using a ribbon cable to the Raspberry Pi camera port.

Testing

After setting and saving all the codes, it’s time now to test the features of our robot. Run the face.py and run.py scripts, and wait for after a few seconds. The screen will then start showing the face and the robot will start talking according to the face it will detect (Refer to Fig 14).

Testing Dreams 

To check what our robot has dreamt of, open the dreams folder and see the saved picture of the robot’s dream (See Fig 15, 16, 17, 18, 19, 20, 21).