Tutorial: Writing Images Using OpenCV in Python

OpenCV (Open Source Computer Vision Library) is a popular library for image processing and computer vision tasks.

Writing images to files is one of the fundamental operations provided by OpenCV.

In this tutorial, we’ll explore how to write images to files using OpenCV.

Table of Contents

What You’ll Learn

Introduction to Writing Images
Basic Image Writing with cv2.imwrite()
Writing Images with Different Formats
Adjusting Image Quality
Writing Grayscale Images
Practical Examples

1. Introduction to Writing Images

The function cv2.imwrite() is used to write an image to a file. The syntax is as follows:

cv2.imwrite(filename, image)

filename: The name of the file where the image will be saved. The format is inferred from the file extension (e.g., .jpg, .png).
image: The image array to be written.

2. Basic Image Writing with cv2.imwrite()

Example: Writing an Image

import cv2

# Read an image
image = cv2.imread("input.jpg")

# Write the image to a new file
cv2.imwrite("output.jpg", image)

print("Image saved successfully!")

3. Writing Images with Different Formats

OpenCV supports several image formats. The format is determined by the file extension in the filename parameter.

Example: Saving as PNG

import cv2

# Read an image
image = cv2.imread("input.jpg")

# Save as PNG
cv2.imwrite("output.png", image)

print("Image saved as PNG!")

Example: Saving as BMP

import cv2

# Read an image
image = cv2.imread("input.jpg")

# Save as BMP
cv2.imwrite("output.bmp", image)

print("Image saved as BMP!")

4. Adjusting Image Quality

OpenCV allows adjusting image quality when saving images in formats like JPEG and PNG by using optional parameters.

JPEG Quality

The quality of a JPEG image can be set using the [int(cv2.IMWRITE_JPEG_QUALITY), quality] parameter, where quality is a value between 0 and 100 (higher is better).

import cv2

# Read an image
image = cv2.imread("input.jpg")

# Save with reduced JPEG quality
cv2.imwrite("low_quality.jpg", image, [int(cv2.IMWRITE_JPEG_QUALITY), 50])

# Save with high JPEG quality
cv2.imwrite("high_quality.jpg", image, [int(cv2.IMWRITE_JPEG_QUALITY), 95])

print("Images saved with different JPEG quality!")

PNG Compression

The compression level for PNG images can be set using [int(cv2.IMWRITE_PNG_COMPRESSION), compression], where compression ranges from 0 to 9 (lower is better).

import cv2

# Read an image
image = cv2.imread("input.jpg")

# Save with low compression
cv2.imwrite("low_compression.png", image, [int(cv2.IMWRITE_PNG_COMPRESSION), 0])

# Save with high compression
cv2.imwrite("high_compression.png", image, [int(cv2.IMWRITE_PNG_COMPRESSION), 9])

print("Images saved with different PNG compression levels!")

5. Writing Grayscale Images

If you want to save a grayscale version of an image, you need to convert the image to grayscale before writing it.

Example: Save Grayscale Image

import cv2

# Read an image
image = cv2.imread("input.jpg")

# Convert to grayscale
gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

# Save the grayscale image
cv2.imwrite("grayscale.jpg", gray_image)

print("Grayscale image saved!")

6. Practical Examples

6.1 Save Images from Video Frames

This example demonstrates extracting and saving frames from a video.

import cv2

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

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

    # Save every 10th frame
    if frame_count % 10 == 0:
        cv2.imwrite(f"frame_{frame_count}.jpg", frame)
    
    frame_count += 1

video.release()
print("Frames saved successfully!")

6.2 Save an Image with Drawing

This example demonstrates saving an image after adding custom drawings.

import cv2

# Create a blank image
image = cv2.imread("input.jpg")

# Draw a red rectangle
cv2.rectangle(image, (50, 50), (200, 200), (0, 0, 255), 5)

# Save the modified image
cv2.imwrite("output_with_rectangle.jpg", image)

print("Image with drawing saved!")

6.3 Batch Save Images

This example demonstrates saving multiple images in a batch process.

import cv2
import os

# Create a list of image filenames
image_files = ["image1.jpg", "image2.jpg", "image3.jpg"]

# Create an output directory
output_dir = "output_images"
os.makedirs(output_dir, exist_ok=True)

# Process and save each image
for image_file in image_files:
    image = cv2.imread(image_file)
    output_path = os.path.join(output_dir, os.path.basename(image_file))
    cv2.imwrite(output_path, image)

print("Batch images saved!")

7. Summary

Use cv2.imwrite() to save images in various formats.
Adjust image quality using format-specific parameters (IMWRITE_JPEG_QUALITY, IMWRITE_PNG_COMPRESSION).
Convert images to grayscale or modify them before saving.
Combine OpenCV’s functionality to save images from videos or batch process images.

Key Functions Used

cv2.imread(): Reads an image.
cv2.imwrite(): Writes an image to a file.
cv2.cvtColor(): Converts image color spaces (e.g., to grayscale).

By mastering these techniques, you can efficiently handle and save images for a variety of use cases!

Writing Images