
- OpenCV Python Tutorial
- OpenCV Python - Home
- OpenCV Python - Overview
- OpenCV Python - Environment
- OpenCV Python - Reading Image
- OpenCV Python - Write Image
- OpenCV Python - Using Matplotlib
- OpenCV Python - Image Properties
- OpenCV Python - Bitwise Operations
- OpenCV Python - Shapes and Text
- OpenCV Python - Mouse Events
- OpenCV Python - Add Trackbar
- OpenCV Python - Resize and Rotate
- OpenCV Python - Image Threshold
- OpenCV Python - Image Filtering
- OpenCV Python - Edge Detection
- OpenCV Python - Histogram
- OpenCV Python - Color Spaces
- OpenCV Python - Transformations
- OpenCV Python - Image Contours
- OpenCV Python - Template Matching
- OpenCV Python - Image Pyramids
- OpenCV Python - Image Addition
- OpenCV Python - Image Blending
- OpenCV Python - Fourier Transform
- OpenCV Python - Capture Videos
- OpenCV Python - Play Videos
- OpenCV Python - Images From Video
- OpenCV Python - Video from Images
- OpenCV Python - Face Detection
- OpenCV Python - Meanshift/Camshift
- OpenCV Python - Feature Detection
- OpenCV Python - Feature Matching
- OpenCV Python - Digit Recognition
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- OpenCV Python - Quick Guide
- OpenCV Python - Resources
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OpenCV Python - Using Matplotlib
Python’s Matplotlib is a powerful plotting library with a huge collection of plotting functions for the variety of plot types. It also has imshow() function to render an image. It gives additional facilities such as zooming, saving etc.
Example
Ensure that Matplotlib is installed in the current working environment before running the following program.
import numpy as np import cv2 import matplotlib.pyplot as plt # Load an color image in grayscale img = cv2.imread('OpenCV_Logo.png',0) plt.imshow(img) plt.show()
Output

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