14 Time-lapse Photography

This chapter builds upon the previous tutorial, capturing frames from the camera at regular intervals and saving them in the static folder within the ugv_pt_rpi directory.

Preparation

Since the product automatically runs the main program at startup, which occupies the camera resource, this tutorial cannot be used in such situations. You need to terminate the main program or disable its automatic startup before restarting the robot.
It's worth noting that because the robot's main program uses multi-threading and is configured to run automatically at startup through crontab, the usual method sudo killall python typically doesn't work. Therefore, we'll introduce the method of disabling the automatic startup of the main program here.
If you have already disabled the automatic startup of the robot's main demo, you do not need to proceed with the section on Terminate the Main Demo.

Terminate the Main Demo

1. Click the "+" icon next to the tab for this page to open a new tab called "Launcher."

2. Click on "Terminal" under "Other" to open a terminal window.

3. Type bash into the terminal window and press Enter.

4. Now you can use the Bash Shell to control the robot.

5. Enter the command: crontab -e.

6. If prompted to choose an editor, enter 1 and press Enter to select nano.

7. After opening the crontab configuration file, you'll see the following two lines:

@reboot ~/ugv_pt_rpi/ugv-env/bin/python ~/ugv_pt_rpi/app.py >> ~/ugv.log 2>&1
@reboot /bin/bash ~/ugv_pt_rpi/start_jupyter.sh >> ~/jupyter_log.log 2>&1

8. Add a # character at the beginning of the line with ……app.py >> …… to comment out this line.

#@reboot ~/ugv_pt_rpi/ugv-env/bin/python ~/ugv_pt_rpi/app.py >> ~/ugv.log 2>&1
@reboot /bin/bash ~/ugv_pt_rpi/start_jupyter.sh >> ~/jupyter_log.log 2>&1

9. Press Ctrl + X in the terminal window to exit. It will ask you Save modified buffer? Enter Y and press Enter to save the changes.

10. Reboot the device. Note that this process will temporarily close the current Jupyter Lab session. If you didn't comment out ……start_jupyter.sh >>…… in the previous step, you can still use Jupyter Lab normally after the robot reboots (JupyterLab and the robot's main program app.py run independently). You may need to refresh the page.

11. One thing to note is that since the sub-controller continues to communicate with the host through the serial port, the host may not start up properly during the restart process due to the continuous change of serial port levels. Taking the case where the upper machine is a Raspberry Pi, after the Raspberry Pi is shut down and the green LED is constantly on without the green LED blinking, you can turn off the power switch of the robot, then turn it on again, and the robot will restart normally.

12. Enter the reboot command: sudo reboot

13. After waiting for the device to restart (during the restart process, the green LED of the Raspberry Pi will blink, and when the frequency of the green LED blinking decreases or goes out, it means that the startup is successful), refresh the page and continue with the remaining part of this tutorial.

Example

The following code block can be run directly:

1. Select the code block below.

2. Press Shift + Enter to run the code block.

3. Watch the real-time video window.

4. Press STOP to close the real-time video and release the camera resources.

If you cannot see the real-time camera feed when running:

Click on Kernel -> Shut down all kernels above.
Close the current section tab and open it again.
Click STOP to release the camera resources, then run the code block again.
Reboot the device.

Notes

If you are using a USB camera, you need to uncomment the line frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB).

Differences from the Previous Chapter

You can adjust the value of time_intervel to change the interval between photos, measured in seconds.
The photos you capture will be stored in the `/ugv_pt_rpi/static/` folder..

import cv2  # Import the OpenCV library for image processing
from picamera2 import Picamera2  # Import the Picamera2 library to access the Raspberry Pi Camera
import numpy as np
from IPython.display import display, Image  # Import IPython display functionality
import ipywidgets as widgets  # Import the ipywidgets library for creating cloud interactive widgets
import threading  # Import the threading library for multithreading

import os, time  # Import the os and time libraries for file operations and time-related functionalities

# Change the interval time for taking photos here (in seconds)
time_intervel = 3  # Take a photo every 3 seconds

# Set the path for saving the images
# You can change the save path here
photo_path = '/home/ws/ugv_pt_rpi/static/'

# Create a toggle button as a stop button
# ================
stopButton = widgets.ToggleButton(
    value=False,  # The initial state of the button is unselected
    description='Stop',  # Text displayed on the button
    disabled=False,  # The button is initially enabled
    button_style='danger',  # 'success', 'info', 'warning', 'danger' or ''
    tooltip='Description',  # Tooltip displayed when hovering over the button
    icon='square'  # Button icon (FontAwesome name without the `fa-` prefix)
)


# Define a function for displaying the video stream and taking photos at regular intervals
# ================
def view(button):
    last_picture_time = time.time()  # Record the time of the last photo taken
    num_count = 0  # Initialize the photo counter
    # If you are using a CSI camera you need to comment out the picam2 code and the camera code
    # Since the latest versions of OpenCV no longer support CSI cameras (4.9.0.80), you need to use picamera2 to get the camera footage
    # picam2 = Picamera2()  # Create an instance of Picamera2
    # Configure camera parameters, set video format and size
    # picam2.configure(picam2.create_video_configuration(main={"format": 'XRGB8888', "size": (640, 480)}))
    # picam2.start()  # Start the camera
    
    camera = cv2.VideoCapture(-1) #Create camera example
    #Set resolution
    camera.set(cv2.CAP_PROP_FRAME_WIDTH, 640)
    camera.set(cv2.CAP_PROP_FRAME_HEIGHT, 480)
    
    display_handle=display(None, display_id=True)  # Create a display handle for updating the displayed content
    
    i = 0
    while True:
        # frame = picam2.capture_array()
        # frame = cv2.flip(frame, 1) # flip the image
        _, frame = camera.read() #Capturing a frame from the camera


        # Take a photo every few seconds
        if time.time() - last_picture_time >= time_intervel:
            num_count = num_count + 1  # Update the photo counter
            photo_filename = f'{photo_path}photo_{num_count}.jpg'  # Define the file name for the photo
            cv2.imwrite(photo_filename, frame)  # Save the photo to the specified path
            last_picture_time = time.time()  # Update the time of the last photo taken
            print(f'{num_count} photos saved. new photo: {photo_filename}')  # Print information about the saved photo
            
        _, frame = cv2.imencode('.jpeg', frame)  # Encode the frame as JPEG format
        display_handle.update(Image(data=frame.tobytes()))  # Update the displayed image
        if stopButton.value==True:  # Check if the stop button is pressed
            #picam2.close()  # If yes, close the camera
            cv2.release() # If yes, close the camera
            display_handle.update(None)

            
# Display the stop button and start the video stream display thread
# ================
display(stopButton)
thread = threading.Thread(target=view, args=(stopButton,))
thread.start()

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