demo_pre_seg__felz_slic.py · 曾伊言/Unsupervised-Segmentation

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曾伊言/Unsupervised-Segmentation

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Unsupervised-Segmentation

demo_pre_seg__felz_slic.py

demo_pre_seg__felz_slic.py 2.28 KB

import cv2
from skimage import segmentation

mark_boundaries = segmentation.mark_boundaries

def press_wasdqe_to_adjust_parameter_of_felz(img):
 paras = [64, 0.5, 128] # pieces
 # paras = [1, 0.8, 20] # default

act_dict = {0: (0, 1.0)}
 act_dict.update(zip([119, 97, 113], [(i, 1.2) for i in range(len(paras))], )) # _KeyBoard: W A Q
 act_dict.update(zip([115, 100, 101], [(i, 0.8) for i in range(len(paras))], )) # KeyBoard: S D E

key = 0
 while True:
 if key != -1:
 i, multi = act_dict[key]
 paras[i] *= multi
 print(key, paras)

seg_map = segmentation.felzenszwalb(img,
 scale=int(paras[0]),
 sigma=paras[1],
 min_size=int(paras[2]))
 show = mark_boundaries(img, seg_map)
 cv2.imshow('', show)

wait_time = 1
 else:
 wait_time = 100

key = cv2.waitKey(wait_time)
 break
 cv2.imwrite('tiger_felz.jpg', show * 255)

def press_wasdqe_to_adjust_parameter_of_slic(img):
 paras = [100, 10000, 10] # pieces
 # paras = [100, 10, 10] # default
 # paras = [16, 64, 6] # appropriate

key = 0
 while True:
 if key != -1:
 i, multi = act_dict[key]
 paras[i] *= multi
 print(key, paras)

seg_map = segmentation.slic(img,
 compactness=int(paras[0]),
 n_segments=int(paras[1]),
 max_iter=int(paras[2]), )
 show = mark_boundaries(img, seg_map)
 cv2.imshow('', show)

wait_time = 1
 else:
 wait_time = 100

key = cv2.waitKey(wait_time)
 # break
 # cv2.imwrite('tiger_slic.jpg', show * 255)

if __name__ == '__main__':
 image = cv2.imread('image/tiger.jpg')
 press_wasdqe_to_adjust_parameter_of_felz(image)
 # press_wasdqe_to_adjust_parameter_of_slic(image)

一键复制编辑原始数据按行查看历史

Yonv 提交于 2019年06月19日 16:26 +08:00 . demo x3

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import cv2
from skimage import segmentation

mark_boundaries = segmentation.mark_boundaries


def press_wasdqe_to_adjust_parameter_of_felz(img):
 paras = [64, 0.5, 128] # pieces
 # paras = [1, 0.8, 20] # default

 act_dict = {0: (0, 1.0)}
 act_dict.update(zip([119, 97, 113], [(i, 1.2) for i in range(len(paras))], )) # _KeyBoard: W A Q
 act_dict.update(zip([115, 100, 101], [(i, 0.8) for i in range(len(paras))], )) # KeyBoard: S D E

 key = 0
 while True:
 if key != -1:
 i, multi = act_dict[key]
 paras[i] *= multi
 print(key, paras)

 seg_map = segmentation.felzenszwalb(img,
 scale=int(paras[0]),
 sigma=paras[1],
 min_size=int(paras[2]))
 show = mark_boundaries(img, seg_map)
 cv2.imshow('', show)

 wait_time = 1
 else:
 wait_time = 100

 key = cv2.waitKey(wait_time)
 break
 cv2.imwrite('tiger_felz.jpg', show * 255)


def press_wasdqe_to_adjust_parameter_of_slic(img):
 paras = [100, 10000, 10] # pieces
 # paras = [100, 10, 10] # default
 # paras = [16, 64, 6] # appropriate

 act_dict = {0: (0, 1.0)}
 act_dict.update(zip([119, 97, 113], [(i, 1.2) for i in range(len(paras))], )) # _KeyBoard: W A Q
 act_dict.update(zip([115, 100, 101], [(i, 0.8) for i in range(len(paras))], )) # KeyBoard: S D E

 key = 0
 while True:
 if key != -1:
 i, multi = act_dict[key]
 paras[i] *= multi
 print(key, paras)

 seg_map = segmentation.slic(img,
 compactness=int(paras[0]),
 n_segments=int(paras[1]),
 max_iter=int(paras[2]), )
 show = mark_boundaries(img, seg_map)
 cv2.imshow('', show)

 wait_time = 1
 else:
 wait_time = 100

 key = cv2.waitKey(wait_time)
 # break
 # cv2.imwrite('tiger_slic.jpg', show * 255)


if __name__ == '__main__':
 image = cv2.imread('image/tiger.jpg')
 press_wasdqe_to_adjust_parameter_of_felz(image)
 # press_wasdqe_to_adjust_parameter_of_slic(image)