shaky_neon_webcam.py

import cv2
import numpy as np

cap = cv2.VideoCapture(0)
ret, frame = cap.read()

rgb_noise_mask = np.random.randint(0, 256, size=frame.shape, dtype=np.uint8)

rgb_noise_mask = cv2.resize(
    cv2.resize(rgb_noise_mask, (rgb_noise_mask.shape[1] // 25, rgb_noise_mask.shape[0] // 25),),
    (rgb_noise_mask.shape[1], rgb_noise_mask.shape[0]),
    interpolation=cv2.INTER_AREA,
)

for _ in range(5):
    # Several rounds of rolling and blurring to
    # make a pretty tie-dye and smooth the edges of the colormap
    rgb_noise_mask = np.roll(rgb_noise_mask, 50, 0)
    rgb_noise_mask = np.roll(rgb_noise_mask, 50, 1)
    rgb_noise_mask = cv2.GaussianBlur(rgb_noise_mask, (33, 33), 0)

while True:
    
    ret, frame = cap.read()

    edges = cv2.Canny(frame, 100, 200, L2gradient=True)
    edges = np.dstack((edges,)*3)
    
    kernel = np.ones((2,2), dtype=np.uint8)
    edges = cv2.morphologyEx(edges, cv2.MORPH_CLOSE, kernel)
    
    fudge_x, fudge_y = np.random.randint(1, 10, 2)
    x_fudged_edges = np.roll(edges, fudge_x, 1)
    y_fudged_edges = np.roll(edges, fudge_y, 0)
    fudged_edges = cv2.add(x_fudged_edges, y_fudged_edges)
    
    rainbow_edges = (fudged_edges * rgb_noise_mask).astype(np.uint8)
    frame = edges + rainbow_edges
    
    cv2.imshow("frame", frame)
    if cv2.waitKey(1) & 0xFF == ord("q"):
        break
        
cap.release()
cv2.destroyAllWindows()