# 图像修复交互式案例——通过水流填充算法来修复被破坏的图像区域；
# 使用俩种方法进行修复
# cv2.INPAINT_TELEA （Fast Marching Method 快速行进算法），对位于点附近、边界法线附近和边界轮廓上的像素赋予更多权重。一旦一个像素被修复，它将使用快速行进的方法移动到下一个最近的像素。
# cv2.INPAINT_NS 流体力学算法，使用了流体力学的一些方法，基本原则是启发式的，首先沿着边从已知区域移动到未知区域（因为边是连续的）。它在匹配修复区域边界处的渐变向量的同时，继续等高线（连接具有相同强度的点的线，就像等高线连接具有相同高程的点一样）。
# USAGE
# python inpaint.py D:/deepLearning/py-demo/20210808/images/ml.jpg
# 按下鼠标左键,添加点、线，按下鼠标右键，添加矩形框，以制作被污染的需要修复图像
# 按下空格键：执行修复功能
# 按下r键：重置待修复的mask
# 按下esc键，退出
import cv2
import numpy as np
class Sketcher:
def __init__(self, windowname, dests, colors_func):
self.prev_pt = None # 线起始点
self.drag_start = None # 矩形起点
self.drag_rect = None # 矩形（左上角，右下角）坐标
self.windowname = windowname
self.dests = dests
self.colors_func = colors_func
self.dirty = False
self.drawing = False
self.mode = False
self.show()
cv2.setMouseCallback(self.windowname, self.on_mouse)
def show(self):
cv2.imshow(self.windowname, self.dests[0])
def on_mouse(self, event, x, y, flags, param):
pt = (x, y)
if event == cv2.EVENT_LBUTTONDOWN:
self.prev_pt = pt
self.drawing = True
elif event == cv2.EVENT_RBUTTONDOWN:
# 第一次初始化时设定pt，往后保留上一个点作为矩形起点
if self.drag_start == None:
self.drag_start = pt
if self.prev_pt and flags & cv2.EVENT_FLAG_LBUTTON:
for dst, color in zip(self.dests, self.colors_func()):
cv2.line(dst, self.prev_pt, pt, color, 5)
self.dirty = True
self.prev_pt = pt
self.show()
if self.drag_start and flags & cv2.EVENT_FLAG_RBUTTON:
xo, yo = self.drag_start
x0, y0 = np.minimum([xo, yo], [x, y])
x1, y1 = np.maximum([xo, yo], [x, y])
self.drag_rect = None
if x1 - x0 > 0 and y1 - y0 > 0:
self.drag_rect = (x0, y0, x1, y1)
for dst, color in zip(self.dests, self.colors_func()):
cv2.rectangle(dst, (x0, y0), (x1, y1), color, -1)
self.dirty = True
self.drag_start = None
self.drag_rect = None
self.show()
else:
self.drag_start = pt
@property
def dragging(self):
return self.drag_rect is not None
def main():
import sys
try:
fn = sys.argv[1]
except:
fn = 'images/ml_.jpg'
img = cv2.imread(fn)
if img is None:
print('Failed to load image file:', fn)
sys.exit(1)
img_mark = img.copy()
mark = np.zeros(img.shape[:2], np.uint8)
sketch = Sketcher('img', [img_mark, mark], lambda: ((255, 255, 255), 255))
while True:
ch = cv2.waitKey()
if ch == 27:
break
if ch == ord(' '):
cv2.imshow('mask', mark)
fmmres = cv2.inpaint(img_mark, mark, 3, cv2.INPAINT_TELEA)
nsres = cv2.inpaint(img_mark, mark, 3, cv2.INPAINT_NS)
cv2.imshow('inpaint fmm res', fmmres)
cv2.imshow('inpaint ns res', nsres)
if ch == ord('r'):
img_mark[:] = img
mark[:] = 0
sketch.show()
print('Done')
if __name__ == '__main__':
main()
cv2.destroyAllWindows()
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