`import cv2`	Import OpenCV
`img = cv2.imread("image.jpg")`	Read image (BGR)
`cv2.imread("image.jpg", cv2.IMREAD_GRAYSCALE)`	Read as grayscale
`cv2.imwrite("output.jpg", img)`	Save image
`cv2.imshow("Window", img)`	Display image
`cv2.waitKey(0)`	Wait for key press
`cv2.destroyAllWindows()`	Close windows

📊 Image Properties

🎨 Color Spaces

`cv2.cvtColor(img, cv2.COLOR_BGR2RGB)`	BGR to RGB
`cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)`	BGR to Grayscale
`cv2.cvtColor(img, cv2.COLOR_BGR2HSV)`	BGR to HSV
`cv2.cvtColor(img, cv2.COLOR_BGR2LAB)`	BGR to LAB
`cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)`	Grayscale to BGR

`cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY)`	Binary threshold
`cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)`	Otsu's threshold
`cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 11, 2)`	Adaptive threshold
`cv2.inRange(hsv, lower, upper)`	Color range mask

`cv2.resize(img, (width, height))`	Resize image
`cv2.resize(img, None, fx=0.5, fy=0.5)`	Scale by factor
`cv2.rotate(img, cv2.ROTATE_90_CLOCKWISE)`	Rotate 90°
`cv2.flip(img, 1)`	Horizontal flip
`cv2.flip(img, 0)`	Vertical flip
`cv2.warpAffine(img, M, (w, h))`	Affine transform
`cv2.warpPerspective(img, M, (w, h))`	Perspective transform

`cv2.getRotationMatrix2D(center, angle, scale)`	Rotation matrix
`cv2.getAffineTransform(pts1, pts2)`	Affine matrix
`cv2.getPerspectiveTransform(pts1, pts2)`	Perspective matrix

`kernel = np.ones((5,5), np.uint8)`	Create kernel
`cv2.erode(img, kernel, iterations=1)`	Erosion
`cv2.dilate(img, kernel, iterations=1)`	Dilation
`cv2.morphologyEx(img, cv2.MORPH_OPEN, kernel)`	Opening (erosion + dilation)
`cv2.morphologyEx(img, cv2.MORPH_CLOSE, kernel)`	Closing (dilation + erosion)
`cv2.morphologyEx(img, cv2.MORPH_GRADIENT, kernel)`	Morphological gradient

`contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)`	Find contours
`cv2.drawContours(img, contours, -1, (0,255,0), 2)`	Draw all contours
`cv2.contourArea(cnt)`	Contour area
`cv2.arcLength(cnt, True)`	Contour perimeter
`cv2.approxPolyDP(cnt, epsilon, True)`	Approximate polygon
`cv2.boundingRect(cnt)`	Bounding rectangle

`cv2.line(img, pt1, pt2, color, thickness)`	Draw line
`cv2.rectangle(img, pt1, pt2, color, thickness)`	Draw rectangle
`cv2.circle(img, center, radius, color, thickness)`	Draw circle
`cv2.ellipse(img, center, axes, angle, 0, 360, color)`	Draw ellipse
`cv2.polylines(img, [pts], True, color, thickness)`	Draw polygon
`cv2.putText(img, text, org, font, scale, color, thickness)`	Draw text

`orb = cv2.ORB_create()`	Create ORB detector
`kp, des = orb.detectAndCompute(img, None)`	Detect and compute
`cv2.drawKeypoints(img, kp, None)`	Draw keypoints
`sift = cv2.SIFT_create()`	Create SIFT
`bf = cv2.BFMatcher()`	Brute-force matcher
`matches = bf.match(des1, des2)`	Match descriptors

`cv2.HoughLines(edges, 1, np.pi/180, 200)`	Hough lines
`cv2.HoughLinesP(edges, 1, np.pi/180, 100, minLineLength, maxLineGap)`	Probabilistic Hough lines
`cv2.HoughCircles(gray, cv2.HOUGH_GRADIENT, 1, 20)`	Hough circles

`cap = cv2.VideoCapture(0)`	Open webcam
`cap = cv2.VideoCapture("video.mp4")`	Open video file
`ret, frame = cap.read()`	Read frame
`cap.get(cv2.CAP_PROP_FPS)`	Get FPS
`cap.set(cv2.CAP_PROP_FRAME_WIDTH, 640)`	Set width
`cap.release()`	Release capture

`fourcc = cv2.VideoWriter_fourcc(*'XVID')`	Video codec
`out = cv2.VideoWriter('output.avi', fourcc, 20.0, (640,480))`	Create writer
`out.write(frame)`	Write frame
`out.release()`	Release writer