def main():
filename = "../data/img/fingerprint.png"
img = np.empty((2, 2))
if cv2.os.path.exists(filename):
img = image_processing.load_image_grayscale(filename)
else:
print("file does not exist")
exit(1)
result_img = Optimal_pattern(img)
image_processing.image_show(result_img)
young_pattern_hist(result_img)
def width_init_img(img, debug=False):
logger.debug("width of initial img")
img = image_processing.blur(img, debug=debug)
img = image_processing.threshold(img, debug=debug)
img = image_processing.bitwise_not(img, debug=debug)
img = image_processing.morphological_transformations(img, debug=debug)
img = image_processing.thinning(img, debug=debug)
# image_processing.image_save(img, title="sample")
if debug:
image_processing.image_show(img, title="width_init_img")
return get_width(img, debug=debug)
def noise(img, noise_param=10000, debug=False):
logger.debug("generating noise")
row, col = img.shape
logger.debug("noise" + str(noise_param / (row * col) * 100) + "%")
# 白
pts_x = np.random.randint(0, col - 1, noise_param)
pts_y = np.random.randint(0, row - 1, noise_param)
img[(pts_y, pts_x)] = 255 # y,xの順番になることに注意
# 黒
pts_x = np.random.randint(0, col - 1, noise_param)
pts_y = np.random.randint(0, row - 1, noise_param)
img[(pts_y, pts_x)] = 0
if debug:
image_processing.image_show(img)
return img
def trim(img, left=0., right=1., top=0., bottom=1., debug=False):
"""
トリミングする
:param debug:
:param img: 0~1
:param left: 0~1
:param right: 0~1
:param top: 0~1
:param bottom: 0~1
:return:
"""
if debug:
print("start: trim")
height = img.shape[0]
width = img.shape[1]
if (left > right) or (top > bottom):
print("left & top should be lower than right & bottom")
exit(1)
elif (0 > left) and (left > 1):
print("parameter left should be 0 to 1")
exit(1)
elif (0 > right) and (right > 1):
print("parameter right should be 0 to 1")
exit(1)
elif (0 > top) and (top > 1):
print("parameter top should be 0 to 1")
exit(1)
elif (0 > bottom) and (bottom > 1):
print("parameter bottom should be 0 to 1")
exit(1)
else:
result = img[int(height * top):int(height * bottom),
int(width * left):int(width * right)]
if debug:
image_processing.image_show(img, "trim - before")
image_processing.image_show(result, "trim - after")
print("end : trim")
return result
import cv2
import numpy as np
from edit_img import image_processing
from optimise.Optimal_pattern import Optimal_pattern
import sys
print("animal")
print(sys.path)
for i in range(1, 5):
filename = "../data/img_animal/animal0{0}.jpg".format(i)
print(filename)
img = np.empty((2, 2))
if cv2.os.path.exists(filename):
img = image_processing.load_image_grayscale(filename)
else:
print("file does not exist")
exit(1)
result_img = Optimal_pattern(img)
image_processing.image_show(result_img)