mirror of
https://github.com/opencv/opencv.git
synced 2024-12-16 02:19:12 +08:00
108 lines
2.4 KiB
Python
108 lines
2.4 KiB
Python
import sys
|
|
import cv2 as cv
|
|
import numpy as np
|
|
|
|
# Global Variables
|
|
|
|
DELAY_CAPTION = 1500
|
|
DELAY_BLUR = 100
|
|
MAX_KERNEL_LENGTH = 31
|
|
|
|
src = None
|
|
dst = None
|
|
window_name = 'Smoothing Demo'
|
|
|
|
|
|
def main(argv):
|
|
cv.namedWindow(window_name, cv.WINDOW_AUTOSIZE)
|
|
|
|
# Load the source image
|
|
imageName = argv[0] if len(argv) > 0 else "../data/lena.jpg"
|
|
|
|
global src
|
|
src = cv.imread(imageName, 1)
|
|
if src is None:
|
|
print ('Error opening image')
|
|
print ('Usage: smoothing.py [image_name -- default ../data/lena.jpg] \n')
|
|
return -1
|
|
|
|
if display_caption('Original Image') != 0:
|
|
return 0
|
|
|
|
global dst
|
|
dst = np.copy(src)
|
|
if display_dst(DELAY_CAPTION) != 0:
|
|
return 0
|
|
|
|
# Applying Homogeneous blur
|
|
if display_caption('Homogeneous Blur') != 0:
|
|
return 0
|
|
|
|
## [blur]
|
|
for i in range(1, MAX_KERNEL_LENGTH, 2):
|
|
dst = cv.blur(src, (i, i))
|
|
if display_dst(DELAY_BLUR) != 0:
|
|
return 0
|
|
## [blur]
|
|
|
|
# Applying Gaussian blur
|
|
if display_caption('Gaussian Blur') != 0:
|
|
return 0
|
|
|
|
## [gaussianblur]
|
|
for i in range(1, MAX_KERNEL_LENGTH, 2):
|
|
dst = cv.GaussianBlur(src, (i, i), 0)
|
|
if display_dst(DELAY_BLUR) != 0:
|
|
return 0
|
|
## [gaussianblur]
|
|
|
|
# Applying Median blur
|
|
if display_caption('Median Blur') != 0:
|
|
return 0
|
|
|
|
## [medianblur]
|
|
for i in range(1, MAX_KERNEL_LENGTH, 2):
|
|
dst = cv.medianBlur(src, i)
|
|
if display_dst(DELAY_BLUR) != 0:
|
|
return 0
|
|
## [medianblur]
|
|
|
|
# Applying Bilateral Filter
|
|
if display_caption('Bilateral Blur') != 0:
|
|
return 0
|
|
|
|
## [bilateralfilter]
|
|
# Remember, bilateral is a bit slow, so as value go higher, it takes long time
|
|
for i in range(1, MAX_KERNEL_LENGTH, 2):
|
|
dst = cv.bilateralFilter(src, i, i * 2, i / 2)
|
|
if display_dst(DELAY_BLUR) != 0:
|
|
return 0
|
|
## [bilateralfilter]
|
|
|
|
# Done
|
|
display_caption('Done!')
|
|
|
|
return 0
|
|
|
|
|
|
def display_caption(caption):
|
|
global dst
|
|
dst = np.zeros(src.shape, src.dtype)
|
|
rows, cols, _ch = src.shape
|
|
cv.putText(dst, caption,
|
|
(int(cols / 4), int(rows / 2)),
|
|
cv.FONT_HERSHEY_COMPLEX, 1, (255, 255, 255))
|
|
|
|
return display_dst(DELAY_CAPTION)
|
|
|
|
|
|
def display_dst(delay):
|
|
cv.imshow(window_name, dst)
|
|
c = cv.waitKey(delay)
|
|
if c >= 0 : return -1
|
|
return 0
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main(sys.argv[1:])
|