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import cv2 | |
import numpy as np | |
# import matplotlib.pyplot as plt | |
#== Parameters ======================================================================= | |
BLUR = 21 | |
CANNY_THRESH_1 = 10 | |
CANNY_THRESH_2 = 200 | |
MASK_DILATE_ITER = 10 | |
MASK_ERODE_ITER = 10 | |
def get_mask(contrasted=None,canny_thr1 = 7,canny_thr2=20): | |
blurred = cv2.GaussianBlur(contrasted, (3, 3), 0) | |
edges = cv2.Canny(blurred, 7, 20) | |
edges = cv2.dilate(edges, None) | |
edges = cv2.erode(edges, None) | |
#-- Find contours in edges, sort by area --------------------------------------------- | |
contour_info = [] | |
# _, contours, _ = cv2.findContours(edges, cv2.RETR_LIST, cv2.CHAIN_APPROX_NONE) | |
# Previously, for a previous version of cv2, this line was: | |
contours, _ = cv2.findContours(edges, cv2.RETR_LIST, cv2.CHAIN_APPROX_NONE) | |
# Thanks to notes from commenters, I've updated the code but left this note | |
for c in contours: | |
contour_info.append(( | |
c, | |
cv2.isContourConvex(c), | |
cv2.contourArea(c), | |
)) | |
contour_info = sorted(contour_info, key=lambda c: c[2], reverse=True) | |
max_contour = contour_info[0] | |
mask = np.zeros(edges.shape) | |
cv2.fillConvexPoly(mask, max_contour[0], (255)) | |
#-- Smooth mask, then blur it -------------------------------------------------------- | |
mask = cv2.dilate(mask, None, iterations=MASK_DILATE_ITER) | |
mask = cv2.erode(mask, None, iterations=MASK_ERODE_ITER) | |
mask = cv2.GaussianBlur(mask, (BLUR, BLUR), 0) | |
# mask_stack = np.dstack([mask]*3) # Create 3-channel alpha mask | |
#-- Blend masked img into MASK_COLOR background -------------------------------------- | |
# mask_stack = mask_stack.astype('float32') / 255.0 # Use float matrices, | |
# img = img.astype('float32') / 255.0 # for easy blending | |
mask_stack = mask/255.0 | |
# gray = gray/255.0 | |
masked = (mask_stack * contrasted) + ((1-mask_stack)) # Blend | |
masked = (masked).astype('uint8') | |
# masked = masked/255 | |
return masked |