def process(self, img):
# Convert bgcolor string to RGB value.
background_color = ImageColor.getrgb(self.background_color)
# Handle palleted images.
img = img.convert('RGBA')
# Copy orignial image and flip the orientation.
reflection = img.copy().transpose(Image.FLIP_TOP_BOTTOM)
# Create a new image filled with the bgcolor the same size.
background = Image.new("RGBA", img.size, background_color)
# Calculate our alpha mask.
start = int(255 - (255 * self.opacity)) # The start of our gradient.
steps = int(255 * self.size) # The number of intermedite values.
increment = (255 - start) / float(steps)
mask = Image.new('L', (1, 255))
for y in range(255):
if y < steps:
val = int(y * increment + start)
else:
val = 255
mask.putpixel((0, y), val)
alpha_mask = mask.resize(img.size)
# Merge the reflection onto our background color using the alpha mask.
reflection = Image.composite(background, reflection, alpha_mask)
# Crop the reflection.
reflection_height = int(img.size[1] * self.size)
reflection = reflection.crop((0, 0, img.size[0], reflection_height))
# Create new image sized to hold both the original image and
# the reflection.
composite = Image.new("RGBA", (img.size[0], img.size[1] + reflection_height), background_color)
# Paste the orignal image and the reflection into the composite image.
composite.paste(img, (0, 0))
composite.paste(reflection, (0, img.size[1]))
# Return the image complete with reflection effect.
return composite
def process(self, img):
original = img = img.convert('RGB')
overlay = Image.new('RGB', original.size, self.color)
mask = Image.new('RGBA', original.size,
(0, 0, 0, int((1.0 - self.overlay_opacity) * 255)))
img = Image.composite(original, overlay, mask).convert('RGB')
return img
def test_format_normalization():
"""
Make sure formats are normalized by ``prepare_image()``.
See https://github.com/matthewwithanm/django-imagekit/issues/262
"""
im = Image.new('RGBA', (100, 100))
ok_('transparency' in prepare_image(im, 'gIF')[1])
def test_format_normalization():
"""
Make sure formats are normalized by ``prepare_image()``.
See https://github.com/matthewwithanm/django-imagekit/issues/262
"""
im = Image.new('RGBA', (100, 100))
ok_('transparency' in prepare_image(im, 'gIF')[1])
def test_resize_antialiasing():
"""
Test that the Resize processor antialiases.
The Resize processor is used by all of the Resize* variants, so this should
cover all of resize processors. Basically, this is to test that it converts
to RGBA mode before resizing.
Related: jdriscoll/django-imagekit#192
"""
# Create a palette image and draw a circle into it.
img = Image.new('P', (500, 500), 1)
img.putpalette([
0, 0, 0,
255, 255, 255,
0, 0, 255,
])
d = ImageDraw.ImageDraw(img)
d.ellipse((100, 100, 400, 400), fill=2)
# Resize the image using the Resize processor
img = Resize(100, 100).process(img)
# Count the number of colors
color_count = len(list(filter(None, img.histogram())))
assert_true(color_count > 2)
def test_resize_antialiasing():
"""
Test that the Resize processor antialiases.
The Resize processor is used by all of the Resize* variants, so this should
cover all of resize processors. Basically, this is to test that it converts
to RGBA mode before resizing.
Related: jdriscoll/django-imagekit#192
"""
# Create a palette image and draw a circle into it.
img = Image.new('P', (500, 500), 1)
img.putpalette([
0,
0,
0,
255,
255,
255,
0,
0,
255,
])
d = ImageDraw.ImageDraw(img)
d.ellipse((100, 100, 400, 400), fill=2)
# Resize the image using the Resize processor
img = Resize(100, 100).process(img)
# Count the number of colors
color_count = len(list(filter(None, img.histogram())))
assert_true(color_count > 2)
def test_convert():
img = Image.new('RGBA', (200, 100))
img_RGBa = Convert("RGBa").process(img)
eq_(img_RGBa.mode, "RGBa")
img_RGBa_RGBA = Convert("RGBA").process(img)
eq_(img_RGBa_RGBA.mode, "RGBA")
def test_coloroverlay():
"""
Test that the ColorOverlay processor
"""
img = Image.new('RGB', (200, 100))
color = ImageColor.getrgb('#cc0000')
img = ColorOverlay(color, overlay_opacity=1.0).process(img)
eq_(img.getpixel((0, 0)), (204, 0, 0))
def test_resize_rounding():
"""
Regression test for matthewwithanm/pilkit#1
"""
img = Image.new('RGB', (95, 95))
img = ResizeToFill(28, 28).process(img)
eq_(img.size, (28, 28))
def test_resize_rounding():
"""
Regression test for matthewwithanm/pilkit#1
"""
img = Image.new('RGB', (95, 95))
img = ResizeToFill(28, 28).process(img)
eq_(img.size, (28, 28))
def test_coloroverlay():
"""
Test that the ColorOverlay processor
"""
img = Image.new('RGB', (200, 100))
color = ImageColor.getrgb('#cc0000')
img = ColorOverlay(color, overlay_opacity=1.0).process(img)
eq_(img.getpixel((0,0)), (204, 0, 0))
def test_convert():
img = Image.new('RGBA', (200, 100))
img_RGBa = Convert("RGBa").process(img)
eq_(img_RGBa.mode, "RGBa")
img_RGBa_RGBA = Convert("RGBA").process(img)
eq_(img_RGBa_RGBA.mode, "RGBA")
def test_resizetofit():
# First create an image with aspect ratio 2:1...
img = Image.new('RGB', (200, 100))
# ...then resize it to fit within a 100x100 canvas.
img = ResizeToFit(100, 100).process(img)
# Assert that the image has maintained the aspect ratio.
eq_(img.size, (100, 50))
def test_resizetofit():
# First create an image with aspect ratio 2:1...
img = Image.new('RGB', (200, 100))
# ...then resize it to fit within a 100x100 canvas.
img = ResizeToFit(100, 100).process(img)
# Assert that the image has maintained the aspect ratio.
eq_(img.size, (100, 50))
def test_upscale():
"""
Test that the upscale argument works as expected.
"""
img = Image.new('RGB', (100, 100))
for P in [Resize, ResizeToFit, ResizeToFill, SmartResize]:
img2 = P(500, 500, upscale=True).process(img)
eq_(img2.size, (500, 500))
img2 = P(500, 500, upscale=False).process(img)
eq_(img2.size, (100, 100))
def test_upscale():
"""
Test that the upscale argument works as expected.
"""
img = Image.new('RGB', (100, 100))
for P in [Resize, ResizeToFit, ResizeToFill, SmartResize]:
img2 = P(500, 500, upscale=True).process(img)
eq_(img2.size, (500, 500))
img2 = P(500, 500, upscale=False).process(img)
eq_(img2.size, (100, 100))
def process(self, img):
# Convert bgcolor string to RGB value.
background_color = ImageColor.getrgb(self.background_color)
# Handle palleted images.
img = img.convert('RGBA')
# Copy orignial image and flip the orientation.
reflection = img.copy().transpose(Image.FLIP_TOP_BOTTOM)
# Create a new image filled with the bgcolor the same size.
background = Image.new("RGBA", img.size, background_color)
# Calculate our alpha mask.
start = int(255 - (255 * self.opacity)) # The start of our gradient.
steps = int(255 * self.size) # The number of intermedite values.
increment = (255 - start) / float(steps)
mask = Image.new('L', (1, 255))
for y in range(255):
if y < steps:
val = int(y * increment + start)
else:
val = 255
mask.putpixel((0, y), val)
alpha_mask = mask.resize(img.size)
# Merge the reflection onto our background color using the alpha mask.
reflection = Image.composite(background, reflection, alpha_mask)
# Crop the reflection.
reflection_height = int(img.size[1] * self.size)
reflection = reflection.crop((0, 0, img.size[0], reflection_height))
# Create new image sized to hold both the original image and
# the reflection.
composite = Image.new("RGBA",
(img.size[0], img.size[1] + reflection_height),
background_color)
# Paste the orignal image and the reflection into the composite image.
composite.paste(img, (0, 0))
composite.paste(reflection, (0, img.size[1]))
# Return the image complete with reflection effect.
return composite
def process(self, img):
original = img = img.convert('RGBA')
for name in ['Color', 'Brightness', 'Contrast', 'Sharpness']:
factor = getattr(self, name.lower())
if factor != 1.0:
try:
img = getattr(ImageEnhance, name)(img).enhance(factor)
except ValueError:
pass
else:
# PIL's Color and Contrast filters both convert the image
# to L mode, losing transparency info, so we put it back.
# See https://github.com/jdriscoll/django-imagekit/issues/64
if name in ('Color', 'Contrast'):
img = Image.merge('RGBA', img.split()[:3] +
original.split()[3:4])
return img
def process(self, img):
original = img = img.convert('RGBA')
for name in ['Color', 'Brightness', 'Contrast', 'Sharpness']:
factor = getattr(self, name.lower())
if factor != 1.0:
try:
img = getattr(ImageEnhance, name)(img).enhance(factor)
except ValueError:
pass
else:
# PIL's Color and Contrast filters both convert the image
# to L mode, losing transparency info, so we put it back.
# See https://github.com/jdriscoll/django-imagekit/issues/64
if name in ('Color', 'Contrast'):
img = Image.merge(
'RGBA',
img.split()[:3] + original.split()[3:4])
return img
def process(image_url, processor = None, width=None, height=None, resolution=None, quality=100):
conn = S3Connection(settings.AWS_ACCESS_KEY_ID, settings.AWS_SECRET_ACCESS_KEY)
bucket = conn.get_bucket(settings.AWS_STORAGE_BUCKET_NAME)
if image_url[0] =='/': image_url = image_url[1:]
r = requests.get(image_url.replace('https', 'http'))
img = Image.open(StringIO(r.content))
processor = ResizeToFit(width, height)
new_img = processor.process(img)
new_file = StringIO()
save_image(new_img, new_file, 'JPEG')
new_k = Key(bucket)
parts = urlparse(image_url)
img_name = os.path.splitext(os.path.basename(parts.path))[0]
new_k.key = 'il/{}x{}/{}.jpeg'.format(width, height, img_name)
new_k.content_type = 'image/jpeg'
new_k.set_contents_from_file(new_file, policy='public-read')
new_image_url = new_k.generate_url(0, query_auth=False, force_http=True)
processed_image,_ = ProcessedImage.objects.update_or_create(source_image = image_url, processed_image = new_image_url)
return processed_image
def process(self, img):
img = img.convert('RGBA')
new_img = Image.new('RGBA', img.size, self.background_color)
new_img.paste(img, img)
return new_img
def test_should_raise_exception_when_crop_is_passed_without_height_and_width():
img = Image.new('RGB', (100, 100))
try:
Thumbnail(crop=True).process(img)
except Exception as e:
eq_(str(e), 'You must provide both a width and height when cropping.')
def test_should_repass_upscale_option_false(my_mock):
img = Image.new('RGB', (100, 100))
Thumbnail(height=200, width=200, upscale=False).process(img)
my_mock.assert_called_once_with(width=200, upscale=False, height=200)
def test_should_call_resizetofill_when_crop_and_ancho_is_passed(my_mock):
img = Image.new('RGB', (100, 100))
Thumbnail(height=200, width=200, anchor='fake').process(img)
assert_true(my_mock.called)
def test_resizetofit_mat():
img = Image.new('RGB', (200, 100))
img = ResizeToFit(100, 100, mat_color=0x000000).process(img)
eq_(img.size, (100, 100))
def test_resizetofit_mat():
img = Image.new('RGB', (200, 100))
img = ResizeToFit(100, 100, mat_color=0x000000).process(img)
eq_(img.size, (100, 100))
def test_make_gifs_opaque():
dir = os.path.dirname(__file__)
path = os.path.join(dir, 'assets', 'cat.gif')
gif = Image.open(path)
MakeOpaque().process(gif)
def test_make_gifs_opaque():
dir = os.path.dirname(__file__)
path = os.path.join(dir, 'assets', 'cat.gif')
gif = Image.open(path)
MakeOpaque().process(gif)
def test_should_call_resizetofit_when_crop_is_not_passed(my_mock):
img = Image.new('RGB', (100, 100))
Thumbnail(height=200, width=200, crop=False).process(img)
assert_true(my_mock.called)
def test_should_call_resizetofill_when_crop_and_ancho_is_passed(my_mock):
img = Image.new('RGB', (100, 100))
Thumbnail(height=200, width=200, anchor='fake').process(img)
assert_true(my_mock.called)
def test_should_repass_upscale_option_false(my_mock):
img = Image.new('RGB', (100, 100))
Thumbnail(height=200, width=200, upscale=False).process(img)
my_mock.assert_called_once_with(width=200, upscale=False, height=200)
def test_should_raise_exception_when_crop_is_passed_without_height_and_width():
img = Image.new('RGB', (100, 100))
try:
Thumbnail(crop=True).process(img)
except Exception as e:
eq_(str(e), 'You must provide both a width and height when cropping.')
def process(self, img):
original = img = img.convert('RGB')
overlay = Image.new('RGB', original.size, self.color)
mask = Image.new('RGBA', original.size, (0,0,0,int((1.0 - self.overlay_opacity)*255)))
img = Image.composite(original, overlay, mask).convert('RGB')
return img
def test_should_call_resizetofit_when_crop_is_not_passed(my_mock):
img = Image.new('RGB', (100, 100))
Thumbnail(height=200, width=200, crop=False).process(img)
assert_true(my_mock.called)
def test_GaussianBlur_radius_7():
img = GaussianBlur(radius=7).process(create_image())
img = img.crop((112, 112, 144, 144))
expected_img = Image.open(get_image_file("GaussianBlur_radius_7.png"))
assert_true(compare_images(img, expected_img))
def process(self, img):
img = img.convert('RGBA')
new_img = Image.new('RGBA', img.size, self.background_color)
new_img.paste(img, img)
return new_img
def create_image():
return Image.open(get_image_file())
def process(self, img):
original = img.convert('RGBA')
overlay = Image.open(self.watermark_image)
img = Image.alpha_composite(original, overlay).convert('RGB')
return img
