Time‑Lapse Photography

This chapter builds on the previous one. It captures images from the camera at fixed time intervals and stores them in the static folder under the ugv_pt_rpi directory.

Preparation

Since the product runs the main program automatically at startup by default, which occupies the camera resource, you cannot use this tutorial under that condition. You need to terminate the main program or disable its auto-start, then restart the robot.

Note that the robot's main program uses multi‑threading and is configured to run at boot via crontab, so a conventional sudo killall python usually does not work. Therefore we describe here how to disable the auto-start of the main program.

If you have already disabled the auto-start of the robot's main program, you do not need to execute the Terminate the Main Program section below.

Terminate the Main Program

1. Click the "+" icon next to the current page tab to open a new Launcher tab.

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

3. In the terminal window, type bash and press Enter.

4. You can now control the robot using the Bash shell.

5. Enter the command: crontab -e

6. If asked which editor to use, type 1 and press Enter to select nano.

7. After opening the crontab configuration file, you should 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 # at the very beginning of the line that starts with ……app.py >> …… to comment it out.

# @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. In the terminal page, press Ctrl+X to exit. It will ask Save modified buffer? Type 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 did not comment out the line ……start_jupyter.sh >> …… in the previous step, you will still be able to use Jupyter Lab normally after the robot restarts (JupyterLab and the robot main program app.py run independently). You may need to refresh the page.

11. One important point: because the lower computer continuously communicates with the upper computer via the serial port, a voltage glitch on the serial line during the upper computer reboot may prevent it from booting correctly. For example, on a Raspberry Pi as the upper computer, after a reboot the Pi may shut down but not restart – the red LED stays on while the green LED does not light. In that case, you can turn off the robot power switch and then turn it on again; the robot will then restart normally.

12. Enter the reboot command: sudo reboot

13. Wait for the device to restart (during reboot the green LED on the Raspberry Pi will blink; when the blinking slows down or stops, it indicates that startup has succeeded), refresh the page, and continue with the remaining parts of this tutorial.

Example

The following code block can be executed 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 resource.

If you cannot see the camera's real-time video when running

Click "Kernel" → "Shut down all kernels"
Close this chapter's tab and reopen it
Press STOP to release the camera resource, then re‑run the code block
Reboot the device

Notes

If you are using a CSI camera, comment out the line frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB).

Differences from the previous chapter

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

import cv2 # import OpenCV for image processing
from picamera2 import Picamera2 # import Picamera2 to access Raspberry Pi Camera
import numpy as np
from IPython.display import display, Image # import IPython display functions
import ipywidgets as widgets # import ipywidgets for interactive controls
import threading # import threading for multi‑threading

import os, time # import os and time for file operations and time‑related functions

# Change the photo interval here (seconds)
time_intervel = 3 # take a photo every 3 seconds

# Set the path to save photos
# 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, # initial state: not selected
    description='Stop', # text displayed on the button
    disabled=False, # button initially enabled
    button_style='danger', # 'success', 'info', 'warning', 'danger' or ''
    tooltip='Description', # tooltip on hover
    icon='square' # button icon (FontAwesome name, without `fa-` prefix)
)


# Define a function to display the video stream and capture photos periodically
# ================
def view(button):
    last_picture_time = time.time() # record the time of the last photo
    num_count = 0 # initialize photo counter
    
    # If you are using a CSI camera, uncomment the picam2 code and comment out the camera code
    # Because newer versions of OpenCV (4.9.0.80) no longer support CSI cameras, you need to use picamera2 to capture camera frames
    
    # picam2 = Picamera2()  # create a Picamera2 instance
    # 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 a camera instance
    # 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 content
    
    i = 0
    while True:
        # frame = picam2.capture_array()
        # frame = cv2.flip(frame, 1) # flip the image
        _, frame = camera.read() # capture 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 photo counter
            photo_filename = f'{photo_path}photo_{num_count}.jpg' # define the photo filename
            cv2.imwrite(photo_filename, frame) # save the photo to the specified path
            last_picture_time = time.time() # update the last photo time
            print(f'{num_count} photos saved. new photo: {photo_filename}') # print save information
            
        _, frame = cv2.imencode('.jpeg', frame) # encode the frame to JPEG format
        display_handle.update(Image(data=frame.tobytes())) # update the displayed image
        if stopButton.value == True: # check if the stop button has been pressed
            # picam2.close() # if yes, close the camera
            cv2.release() # if yes, release 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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14 Time-Lapse Photography

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