Live Image Filtering - Python Notebook

To apply live image filtering using OpenCV, you can modify the code for accessing the camera to include image processing steps. Below is an example of how to implement live image filtering with options for preview, blurring, corner feature detection, and Canny edge detection. You can switch between different filters using keyboard inputs.

import cv2
import sys
import numpy

PREVIEW  = 0  # Preview Mode
BLUR     = 1  # Blurring Filter
FEATURES = 2  # Corner Feature Detector
CANNY    = 3  # Canny Edge Detector

feature_params = dict(maxCorners=500, qualityLevel=0.2, minDistance=15, blockSize=9)
s = 0
if len(sys.argv) > 1:
    s = sys.argv[1]

image_filter = PREVIEW
alive = True

win_name = "Camera Filters"
cv2.namedWindow(win_name, cv2.WINDOW_NORMAL)
result = None

source = cv2.VideoCapture(s)

while alive:
    has_frame, frame = source.read()
    if not has_frame:
        break

    frame = cv2.flip(frame, 1)

    if image_filter == PREVIEW:
        result = frame
    elif image_filter == CANNY:
        result = cv2.Canny(frame, 80, 150)
    elif image_filter == BLUR:
        result = cv2.blur(frame, (13, 13))
    elif image_filter == FEATURES:
        result = frame
        frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
        corners = cv2.goodFeaturesToTrack(frame_gray, **feature_params)
        if corners is not None:
            for x, y in numpy.float32(corners).reshape(-1, 2):
                cv2.circle(result, (x, y), 10, (0, 255, 0), 1)

    cv2.imshow(win_name, result)

    key = cv2.waitKey(1)
    if key == ord("Q") or key == ord("q") or key == 27:
        alive = False
    elif key == ord("C") or key == ord("c"):
        image_filter = CANNY
    elif key == ord("B") or key == ord("b"):
        image_filter = BLUR
    elif key == ord("F") or key == ord("f"):
        image_filter = FEATURES
    elif key == ord("P") or key == ord("p"):
        image_filter = PREVIEW

source.release()
cv2.destroyWindow(win_name)