Display an image in OpenCV using Python

Displaying an image using OpenCV in Python is quite straightforward. Here's a step-by-step tutorial to guide you through the process:

Steps to Display an Image using OpenCV:

1. Setup:

First, ensure you have OpenCV installed. If not, install it using pip:

pip install opencv-python

2. Import Necessary Libraries:

Begin your Python script by importing the required libraries:

import cv2

3. Load the Image:

Use the imread() function of OpenCV to read an image. This function loads the image from the specified file:

image = cv2.imread('path_to_image.jpg')

Replace 'path_to_image.jpg' with the path to your image file.

4. Display the Image:

Use the imshow() function to display the loaded image:

cv2.imshow('Image Window', image)

Here, 'Image Window' is the name of the window in which the image will be displayed. You can change it to any title you prefer.

5. Wait and Close:

After displaying the image, you'll need to keep the window open and wait for a key event. The waitKey() function waits for a key event for a specified amount of time (in milliseconds). If you pass 0, it will wait indefinitely until a key is pressed:

cv2.waitKey(0)

Finally, after a key is pressed, you'll want to close all OpenCV windows:

cv2.destroyAllWindows()

Complete Code:

Combining all the above steps, here's the complete script:

import cv2

# Load the image
image = cv2.imread('path_to_image.jpg')

# Display the image
cv2.imshow('Image Window', image)

# Wait for a key press and then close the image window
cv2.waitKey(0)
cv2.destroyAllWindows()

Run the script, and it will display your image in a new window. Press any key to close the window.

That's it! This is the basic way to display an image using OpenCV in Python.

Python code for showing images in OpenCV:

import cv2

# Load an image
img = cv2.imread('image.jpg')

# Display the image
cv2.imshow('Image', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

Image loading and display with OpenCV:

import cv2

# Load an image
img = cv2.imread('image.jpg')

# Display the image
cv2.imshow('Loaded Image', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

Reading and displaying images using OpenCV:

import cv2

# Read an image
img = cv2.imread('image.jpg')

# Display the image
cv2.imshow('Read and Display Image', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

Real-time image display with OpenCV:

import cv2

# Open the camera
cap = cv2.VideoCapture(0)

while True:
    # Read a frame from the camera
    ret, frame = cap.read()

    # Display the real-time frame
    cv2.imshow('Real-time Image Display', frame)

    # Break the loop on 'Esc' key press
    if cv2.waitKey(1) & 0xFF == 27:
        break

# Release the camera and close the window
cap.release()
cv2.destroyAllWindows()

Displaying images with matplotlib and OpenCV in Python:

import cv2
from matplotlib import pyplot as plt

# Load an image
img = cv2.imread('image.jpg')

# Convert BGR to RGB for matplotlib
img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)

# Display the image using matplotlib
plt.imshow(img_rgb)
plt.axis('off')
plt.show()

Image window customization in OpenCV display:

import cv2

# Load an image
img = cv2.imread('image.jpg')

# Create a named window with custom properties
cv2.namedWindow('Custom Window', cv2.WINDOW_NORMAL)
cv2.resizeWindow('Custom Window', 800, 600)

# Display the image in the custom window
cv2.imshow('Custom Window', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

Handling multiple image displays in OpenCV:

import cv2

# Load multiple images
img1 = cv2.imread('image1.jpg')
img2 = cv2.imread('image2.jpg')

# Display images side by side
combined_img = cv2.hconcat([img1, img2])
cv2.imshow('Multiple Image Display', combined_img)
cv2.waitKey(0)
cv2.destroyAllWindows()

Adding text and annotations to displayed images in OpenCV:

import cv2

# Load an image
img = cv2.imread('image.jpg')

# Add text and annotation to the image
cv2.putText(img, 'OpenCV Image', (50, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)

# Display the annotated image
cv2.imshow('Annotated Image', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

Displaying images in a graphical user interface (GUI) with OpenCV:

import cv2
from tkinter import *
from PIL import Image, ImageTk

# Load an image
img = cv2.imread('image.jpg')

# Convert BGR to RGB for PIL
img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
img_pil = Image.fromarray(img_rgb)

# Create a Tkinter window
root = Tk()
root.title("OpenCV Image")

# Convert PIL image to Tkinter PhotoImage
img_tk = ImageTk.PhotoImage(img_pil)

# Display the image in a Label widget
label = Label(root, image=img_tk)
label.pack()

# Run the Tkinter event loop
root.mainloop()

Displaying images with different color maps in OpenCV:

import cv2

# Load an image in grayscale
img = cv2.imread('image.jpg', cv2.IMREAD_GRAYSCALE)

# Apply a color map (e.g., COLORMAP_JET)
color_mapped_img = cv2.applyColorMap(img, cv2.COLORMAP_JET)

# Display the original and color-mapped images
cv2.imshow('Original Image', img)
cv2.imshow('Color Mapped Image', color_mapped_img)
cv2.waitKey(0)
cv2.destroyAllWindows()

Displaying images with adjustable size and resolution in OpenCV:

import cv2

# Load an image
img = cv2.imread('image.jpg')

# Resize the image
resized_img = cv2.resize(img, (800, 600))

# Display the resized image
cv2.imshow('Resized Image', resized_img)
cv2.waitKey(0)
cv2.destroyAllWindows()