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import numpy as np | |
import cv2 | |
import _utils | |
from matplotlib import pyplot as plt | |
smallestSideSize = 500 | |
# real would be thicker because of masking process | |
mainRectSize = .04 | |
fgSize = .15 | |
img = cv2.imread('img_test/10.jpg') | |
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) | |
height, width = img.shape[:2] | |
new_w, new_h = _utils.new_image_size(width, height, smallestSideSize) | |
# resize image to lower resources usage | |
# if you need masked image in original size, do not resize it | |
img_small = cv2.resize(img, (new_w, new_h), interpolation=cv2.INTER_AREA) | |
# quantify colors | |
# img_small = _utils.quantify_colors(img_small, 32, 10) | |
# create mask tpl | |
mask = np.zeros(img_small.shape[:2], np.uint8) | |
# create BG rect | |
bg_w = round(new_w * mainRectSize) | |
bg_h = round(new_h * mainRectSize) | |
bg_rect = (bg_w, bg_h, new_w - bg_w, new_h - bg_h) | |
# create FG rect | |
fg_w = round(new_w * (1 - fgSize) / 2) | |
fg_h = round(new_h * (1 - fgSize) / 2) | |
fg_rect = (fg_w, fg_h, new_w - fg_w, new_h - fg_h) | |
# color: 0 - bg, 1 - fg, 2 - probable bg, 3 - probable fg | |
cv2.rectangle(mask, fg_rect[:2], fg_rect[2:4], color=cv2.GC_FGD, thickness=-1) | |
mask_preset = mask.copy() | |
bgdModel1 = np.zeros((1, 65), np.float64) | |
fgdModel1 = np.zeros((1, 65), np.float64) | |
cv2.grabCut(img_small, mask, bg_rect, bgdModel1, fgdModel1, 3, cv2.GC_INIT_WITH_RECT) | |
mask_rect = mask.copy() | |
cv2.rectangle(mask, bg_rect[:2], bg_rect[2:4], color=cv2.GC_PR_BGD, thickness=bg_w * 3) | |
cv2.grabCut(img_small, mask, bg_rect, bgdModel1, fgdModel1, 10, cv2.GC_INIT_WITH_MASK) | |
mask_mask = mask.copy() | |
# mask to remove background | |
mask_result = np.where((mask == 1) + (mask == 3), 255, 0).astype('uint8') | |
# if we are removing too much, assume there is no background | |
unique, counts = np.unique(mask_result, return_counts=True) | |
mask_dict = dict(zip(unique, counts)) | |
if mask_dict[0] > mask_dict[255] * 1.6: | |
mask_result = np.where((mask == 0) + (mask != 1) + (mask != 3), 255, 0).astype('uint8') | |
# apply mask to image | |
masked = cv2.bitwise_and(img_small, img_small, mask=mask_result) | |
masked[mask_result < 2] = [0, 0, 255] # change black bg to blue | |
# draw rect on original image | |
cv2.rectangle(img_small, bg_rect[:2], bg_rect[2:4], (255, 0, 0), 2) | |
cv2.rectangle(img_small, fg_rect[:2], fg_rect[2:4], (0, 255, 0), 2, cv2.FILLED) | |
plt.subplot(2, 3, 1), plt.imshow(img_small), plt.title("Orig img with preset") | |
plt.subplot(2, 3, 2), plt.imshow(mask_result), plt.title("Final Mask") | |
plt.subplot(2, 3, 3), plt.imshow(masked), plt.title("Result") | |
plt.subplot(2, 3, 4), plt.imshow(mask_preset), plt.title("Mask preset FG") | |
plt.subplot(2, 3, 5), plt.imshow(mask_rect), plt.title("GC_INIT_WITH_RECT") | |
plt.subplot(2, 3, 6), plt.imshow(mask_mask), plt.title("GC_INIT_WITH_MASK") | |
plt.show() |