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import cv2 | |
import numpy as np | |
%matplotlib inline | |
import matplotlib.pyplot as plt | |
def buffer_coastline(img, threshold=135): | |
arr = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY) | |
mask = np.ndarray(arr.shape + (3,)).astype(np.uint8) | |
below = arr < threshold | |
mask[below] = [255,255,255] | |
mask = cv2.morphologyEx(mask[:,:,0], cv2.MORPH_OPEN, kernel=np.ones([3, 3]), iterations=3) | |
edm1 = cv2.distanceTransform(mask, cv2.cv.CV_DIST_L2, 5) | |
s = (edm1 < 10) | |
mask[s] = 255 | |
mask[~s] = 0 | |
edm2 = cv2.distanceTransform(mask, cv2.cv.CV_DIST_L2, 5) | |
s = (edm2 < 20) & (edm1 < 10) | |
mask[s] = 255 | |
mask[~s] = 0 | |
return mask, edm1, edm2 | |
def render_array(arr1, arr2=None, width=7, height=7, cmap=plt.cm.jet): | |
if arr2 is None: | |
fig, ax = plt.subplots(1, figsize=(width,height), facecolor='white') | |
ax.axis('off') | |
plt.imshow(arr1, cmap=cmap) | |
plt.show() | |
else: | |
fig, (ax1, ax2) = plt.subplots(nrows=1, ncols=2) | |
fig.set_size_inches(width, height) | |
ax1.imshow(arr2) | |
ax1.axis('off') | |
ax2.imshow(arr1) | |
ax2.axis('off') | |
img = clipped[3][:,:,0:3].copy() | |
mask, edm1, edm2 = buffer_coastline(img.copy()) | |
render_array(edm1, edm2, width=10, height=10) | |
img = clipped[3].copy() | |
img[:,:,3] = mask | |
render_array(img, mask, width=10, height=10) | |
masks = [] | |
for image_arr in clipped: | |
mask, edm1, edm2 = buffer_coastline(image_arr, threshold=125) | |
masks.append(mask) | |
union_mask = reduce( lambda s,e: s & e, masks ) | |
union_mask = cv2.dilate(union_mask, kernel=np.ones([3, 3]), iterations=3) | |
binary_mask = union_mask.copy() | |
binary_mask[(union_mask > 0)] = 1 | |
img = clipped[3].copy() | |
img[:,:,3] = union_mask | |
render_array(img, width=10, height=10) |
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