def cut_(origin):
img = common.bgr2gray_(origin)
img = common.binary_(img, thresh=config.binary_threshold)
cut, mask = common.grabCut_(origin, newmask=img)
return cut
def roi_(origin):
img = common.binary_(origin, thresh=config.binary_threshold)
img = common.erode_(img)
img = common.morph_(img)
img = common.canny_(img)
contours = common.findContours_(img, origin)
# FFT 矫正
roi = common.minAreaRect_(origin, contours)
return roi
def chosen(origin):
# randon hough
img = common.binary_(origin, thresh=config.binary_threshold)
img = common.erode_(img)
img = common.morph_(img)
img = common.canny_(img)
origin = common.hough_lines_p_(img, origin)
contours = common.findContours_(img, origin)
roi = common.boundingRect_(origin, contours)
return roi
plt.subplot(1, 2, 1)
plt.imshow(img)
ax = plt.gca() # 获取到当前坐标轴信息
ax.xaxis.set_ticks_position('top') # 将X坐标轴移到上面
plt.subplot(1, 2, 2)
plt.imshow(cut)
ax = plt.gca() # 获取到当前坐标轴信息
ax.xaxis.set_ticks_position('top') # 将X坐标轴移到上面
plt.show()
# ret, cut = cv2.threshold(cut, 100, 255, cv2.THRESH_BINARY)
return img, cut
if __name__ == '__main__':
# 0黑色，255白色
# 11,12,13
file_name = "../data/img/2.jpg"
img = cv2.imread(file_name)
img = common.bgr2gray_(img)
img = common.binary_(img)
img, cut = rotate_(img, (1430, 895), (280, 30),
30,
draw=False,
display=True)
print(cut)