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Learn Opencv Computer Vision Tutorial, validate concepts with Opencv Computer Vision MCQ Questions, and prepare interviews through Opencv Computer Vision Interview Questions and Answers.
OpenCV MCQ
The de facto open-source CV toolkit—load images, filter pixels, detect features, and grab video frames.
OpenCV
Library
imread
BGR Mat
process
blur / edge
VideoCapture
Frames
OpenCV essentials
OpenCV provides optimized implementations for image I/O, color conversion, geometric transforms, filtering, morphology, feature detection, and video capture. Python's cv2 wraps C++ for speed; BGR is default for historical reasons—not RGB.
BGR vs RGB
cv2.imread stores color images as BGR; swap channels before sending to libraries expecting RGB.
Key ideas
cv2.imread / imwrite
Load/save; flags control color vs grayscale.
cvtColor
BGR↔RGB, BGR↔HSV, grayscale conversions.
resize / warp
Geometry and camera-like remaps.
GaussianBlur / Canny
Smoothing and edge pipelines.
Minimal script
import cv2 → img = cv2.imread(path) → process → cv2.imshow / VideoCapture loop