def per_step(img, e, s):
plt.subplot(1, 3, 1)
ImageUtils.imshow(transferer.content_image, 'Content Image')
plt.subplot(1, 3, 2)
ImageUtils.imshow(img, f'New Image, epoch {e}, step {s}')
plt.subplot(1, 3, 3)
ImageUtils.imshow(transferer.style_image, 'Style Image')
ImageUtils.flashplot()
fig = plt.figure(1)
fig.clf()
ax = fig.subplots(nrows=2, ncols=1)
ImageUtils.image_op(
images=[content_image, stylized_image, style_image],
op=lambda a, b, c: (a + b) / 2), 'Average Image'),
((2, 3, 3), style_orig, 'Style Image'),
((2, 3, 6), style_image, 'New Style Image'),
)
plotset2 = ( # This shows 1x3 simple layout
((1, 3, 1), content_image, 'Content Image'),
((1, 3, 2), stylized_image, 'New Image'),
((1, 3, 3), style_orig, 'Style Image'),
)
for c, i, t in plotset1:
plt.subplot(*c)
ImageUtils.imshow(i, t)
# View style transfers one by one
input('Next? : ')
ImageUtils.flashplot()
print("\t> Finished")
except Exception as e:
print(" - Failed on image", i)
print(f"\t> Image failed on {filename}: {e}.")
fails += 1 # This skips fails. To be fixed later
# For testing
if fails > 5: quit()
plt.subplot(1, 3, 2)
ImageUtils.imshow(img, f'New Image, epoch {e}, step {s}')
plt.subplot(1, 3, 3)
ImageUtils.imshow(transferer.style_image, 'Style Image')
ImageUtils.flashplot()
fig = plt.figure(1)
fig.clf()
ax = fig.subplots(nrows=2, ncols=1)
print("Starting Run")
image = transferer.run(epochs=4, steps=4, per_step=per_step)
plt.subplot(1, 3, 1)
ImageUtils.imshow(transferer.content_image, 'Content Image')
plt.subplot(1, 3, 2)
ImageUtils.imshow(image, 'New Image')
plt.subplot(1, 3, 3)
ImageUtils.imshow(transferer.style_image, 'Style Image')
plt.show()
input("Proceed: ")
# The following shows how the high frequency components have increased.
# Also, this high frequency component is basically an edge-detector.
def high_pass_x_y(image):
"""For visualizing produced artifacts"""
x_var = image[:, :, 1:, :] - image[:, :, :-1, :]
'https://facultystaff.richmond.edu/~dszajda/images/doug_small_website_photo_UR_Fall_2011.jpg',
'https://pbs.twimg.com/profile_images/1008157063376199682/HQQ5PrT5_400x400.jpg'
]
content_imgs = [ImageUtils.grab_image(x) for x in content_imgs]
style_dirs = dirs[:5]
for i, filename in enumerate(style_dirs):
x, y, w, h = detectAnime(path_to_pics + filename, i)
if x is not None:
print(x, y, w, h)
style_image = ImageUtils.grab_image("out.png")
plt.subplot(len(content_imgs) + 1, len(content_imgs) + 1, i + 1)
ImageUtils.imshow(style_image)
for j, content_image in enumerate(content_imgs):
for i, filename in enumerate(style_dirs):
# Attempt style transfer on content image with current style image
try:
# style_image = ImageUtils.grab_image(path_to_pics + filename)
# Testing code begins here
# Trying to remove image background
# seg.run_visualization(path_to_pics + filename)
# style_image = ImageUtils.grab_image('test.jpg')
# Attempting to resize style image for hypothesis
