Tutorial: Capturing Videos Using OpenCV in Python

OpenCV is a powerful library for computer vision, and one of its core functionalities is capturing video from cameras or video files. This tutorial will guide you through the process of capturing, processing, and saving video using OpenCV.

What You’ll Learn

1. Introduction to Video Capture

The class cv2.VideoCapture is used to capture video. It can:

• Access live video from a webcam.
• Read video files from disk.

2. Capturing Video from a Webcam

Example: Capture Video from Webcam

import cv2

# Initialize video capture (0 for the default camera)
cap = cv2.VideoCapture(0)

if not cap.isOpened():
    print("Error: Could not open webcam.")
    exit()

while True:
    # Capture frame-by-frame
    ret, frame = cap.read()

    # Check if the frame was successfully captured
    if not ret:
        print("Error: Failed to capture frame.")
        break

    # Display the frame
    cv2.imshow("Webcam Feed", frame)

    # Break the loop on 'q' key press
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

# Release the capture and close windows
cap.release()
cv2.destroyAllWindows()

3. Capturing Video from a File

Example: Read Video from File

import cv2

# Open a video file
cap = cv2.VideoCapture("video.mp4")

if not cap.isOpened():
    print("Error: Could not open video file.")
    exit()

while True:
    # Capture frame-by-frame
    ret, frame = cap.read()

    # Break the loop if no frames are left
    if not ret:
        print("End of video.")
        break

    # Display the frame
    cv2.imshow("Video Playback", frame)

    # Break the loop on 'q' key press
    if cv2.waitKey(30) & 0xFF == ord('q'):
        break

# Release the capture and close windows
cap.release()
cv2.destroyAllWindows()

4. Displaying Video Frames

Frames captured using cv2.VideoCapture can be displayed using cv2.imshow.

Example: Resize and Display Video Frames

import cv2

cap = cv2.VideoCapture(0)

while True:
    ret, frame = cap.read()
    if not ret:
        break

    # Resize the frame to half its original size
    resized_frame = cv2.resize(frame, None, fx=0.5, fy=0.5)

    # Display the resized frame
    cv2.imshow("Resized Webcam Feed", resized_frame)

    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()

5. Saving Captured Video

Use cv2.VideoWriter to save video frames to a file.

Example: Save Webcam Feed to File

import cv2

# Initialize webcam
cap = cv2.VideoCapture(0)

# Define the codec and create VideoWriter object
fourcc = cv2.VideoWriter_fourcc(*'XVID')  # XVID codec
out = cv2.VideoWriter('output.avi', fourcc, 20.0, (640, 480))

if not cap.isOpened():
    print("Error: Could not open webcam.")
    exit()

while True:
    ret, frame = cap.read()
    if not ret:
        break

    # Write the frame to the file
    out.write(frame)

    # Display the frame
    cv2.imshow("Recording Webcam", frame)

    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

# Release resources
cap.release()
out.release()
cv2.destroyAllWindows()

6. Processing Video Frames

Example: Convert Frames to Grayscale

import cv2

cap = cv2.VideoCapture(0)

while True:
    ret, frame = cap.read()
    if not ret:
        break

    # Convert the frame to grayscale
    gray_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    # Display the grayscale frame
    cv2.imshow("Grayscale Webcam Feed", gray_frame)

    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()

Example: Apply Edge Detection

import cv2

cap = cv2.VideoCapture(0)

while True:
    ret, frame = cap.read()
    if not ret:
        break

    # Apply Canny edge detection
    edges = cv2.Canny(frame, 100, 200)

    # Display the edges
    cv2.imshow("Edge Detection", edges)

    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()

7. Practical Examples

7.1 Capture and Save Video with Timestamp

import cv2
from datetime import datetime

cap = cv2.VideoCapture(0)
fourcc = cv2.VideoWriter_fourcc(*'XVID')
out = cv2.VideoWriter('output_with_timestamp.avi', fourcc, 20.0, (640, 480))

while True:
    ret, frame = cap.read()
    if not ret:
        break

    # Add a timestamp to the frame
    timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
    cv2.putText(frame, timestamp, (10, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)

    # Write and display the frame
    out.write(frame)
    cv2.imshow("Video with Timestamp", frame)

    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cap.release()
out.release()
cv2.destroyAllWindows()

7.2 Extract Frames from Video

import cv2
import os

# Open a video file
cap = cv2.VideoCapture("video.mp4")
output_dir = "extracted_frames"
os.makedirs(output_dir, exist_ok=True)

frame_count = 0
while True:
    ret, frame = cap.read()
    if not ret:
        break

    # Save every 10th frame
    if frame_count % 10 == 0:
        frame_path = os.path.join(output_dir, f"frame_{frame_count}.jpg")
        cv2.imwrite(frame_path, frame)

    frame_count += 1

cap.release()
print("Frames extracted and saved!")

8. Summary

• Capturing Video:
  • Use cv2.VideoCapture(0) for webcam or specify a video file path.
• Displaying Video:
  • Use cv2.imshow() to display video frames in a window.
• Saving Video:
  • Use cv2.VideoWriter to save video to a file.
• Processing Frames:
  • Apply transformations like resizing, grayscale, or edge detection to frames.

Key Functions

• cv2.VideoCapture(): Captures video from a source.
• cv2.imshow(): Displays video frames.
• cv2.VideoWriter(): Saves video to a file.
• cv2.cvtColor(): Converts color spaces (e.g., to grayscale).

By combining these techniques, you can build powerful video processing applications using OpenCV!