def process(self, image):
"""
@param image -- The image to process.
Returns a single image, or a list containing one or more images.
"""
BaseFilter.process(self, image)
# ---------------------------------------------------------------------------
# Create the mask around the source image
mask = image.split()[-1]
if image.mode[-1] != 'A' or isSimpleBBox(mask):
mask = createMask(image, threshold=self._threshold, fillHoles=True,
backgroundColor=self.background, blurRadius=self._blurRadius,
maskScale=self._maskScale)
# ---------------------------------------------------------------------------
# Process each value
newImages = []
for value in self._values:
if value is None:
value = self.background
bg = ImageChops.constant(image, value)
newImage = Image.composite(image.split()[0], bg, mask)
newImage.putalpha(image.split()[-1])
newImages.append(newImage)
if len(newImages) == 1:
return newImages[0]
else:
return newImages
def process(self, image):
"""
@param image -- The image to process.
Returns a single image, or a list containing one or more images.
"""
BaseFilter.process(self, image)
# ---------------------------------------------------------------------------
# Create the mask around the source image
mask = image.split()[-1]
if image.mode[-1] != 'A' or isSimpleBBox(mask):
mask = createMask(image, threshold=self._threshold, fillHoles=True,
backgroundColor=self.background, blurRadius=self._blurRadius,
maskScale=self._maskScale)
# ---------------------------------------------------------------------------
# Process each value
newImages = []
for value in self._values:
if value is None:
value = self.background
bg = ImageChops.constant(image, value)
newImage = Image.composite(image.split()[0], bg, mask)
newImage.putalpha(image.split()[-1])
newImages.append(newImage)
if len(newImages) == 1:
return newImages[0]
else:
return newImages
def process(self, image):
"""
@param image -- The image to process.
Returns a single image, or a list containing one or more images.
"""
BaseFilter.process(self, image)
# If no background image, just return the input image as-is
if self.bgPath is None:
return image
# ---------------------------------------------------------------------------
# Open the background image(s) if we haven't done so already
if self.bgImgs is None:
# If given a relative path, make it relative to the vision data directory
if not os.path.isabs(self.bgPath):
basePath = os.path.abspath(os.curdir)
basePath = os.path.split(basePath)
while(basePath[0]):
if basePath[1] == 'vision':
break
basePath = os.path.split(basePath[0])
# Did we find the vision directory?
if basePath[1] == 'vision':
fullPath = VisionUtils.findData(os.path.join(basePath[0], 'vision'),
self.bgPath, 'backgound', 'background images', True)
#basePath = os.path.join(basePath[0], 'vision', 'data')
else:
fullPath = self.bgPath
else:
fullPath = self.bgPath
# If given a filename, we only have 1 image
if os.path.isfile(fullPath):
self.bgImgs = [Image.open(fullPath).convert('LA')]
# Else, open up all images in this directory
else:
self.bgImgs = []
w = os.walk(fullPath)
while True:
try:
dirpath, dirnames, filenames = w.next()
except StopIteration:
break
# Don't enter directories that begin with '.'
for d in dirnames[:]:
if d.startswith('.'):
dirnames.remove(d)
dirnames.sort()
# Ignore files that begin with '.'
filenames = [f for f in filenames if not f.startswith('.')]
filenames.sort()
imageFilenames = [os.path.join(dirpath, f) for f in filenames]
# Process each image
for filename in imageFilenames:
self.bgImgs.append(Image.open(filename).convert('L'))
# Keep a cache of all images, scaled to the input image size
self.scaledBGImgs = [x.copy() for x in self.bgImgs]
# Pick a background at random.
idx = self._rng.randint(0, len(self.bgImgs)-1)
bgImg = self.scaledBGImgs[idx]
# ---------------------------------------------------------------------------
# re-scale the background to the source image if necessary
if bgImg.size != image.size:
bgImg = self.scaledBGImgs[idx] = self.bgImgs[idx].resize(image.size, Image.ANTIALIAS)
# ---------------------------------------------------------------------------
# Create the mask around the source image
mask = image.split()[-1]
if image.mode[-1] != 'A' or isSimpleBBox(mask):
mask = createMask(image, threshold=self._threshold, fillHoles=True,
backgroundColor=self.background, blurRadius=self._blurRadius,
maskScale=self._maskScale)
# ---------------------------------------------------------------------------
# Paste the image onto the background
newImage = bgImg.copy()
newImage.paste(image, (0,0), mask)
# Put an "all-on" alpha channel because we now want the network to consider the entire
# image
newImage.putalpha(ImageChops.constant(newImage, 255))
return newImage
def process(self, image):
"""
@param image -- The image to process.
Returns a single image, or a list containing one or more images.
"""
BaseFilter.process(self, image)
# If no background image, just return the input image as-is
if self.bgPath is None:
return image
# ---------------------------------------------------------------------------
# Open the background image(s) if we haven't done so already
if self.bgImgs is None:
# If given a relative path, make it relative to the vision data directory
if not os.path.isabs(self.bgPath):
basePath = os.path.abspath(os.curdir)
basePath = os.path.split(basePath)
while (basePath[0]):
if basePath[1] == 'vision':
break
basePath = os.path.split(basePath[0])
# Did we find the vision directory?
if basePath[1] == 'vision':
fullPath = VisionUtils.findData(
os.path.join(basePath[0], 'vision'), self.bgPath,
'backgound', 'background images', True)
#basePath = os.path.join(basePath[0], 'vision', 'data')
else:
fullPath = self.bgPath
else:
fullPath = self.bgPath
# If given a filename, we only have 1 image
if os.path.isfile(fullPath):
self.bgImgs = [Image.open(fullPath).convert('LA')]
# Else, open up all images in this directory
else:
self.bgImgs = []
w = os.walk(fullPath)
while True:
try:
dirpath, dirnames, filenames = w.next()
except StopIteration:
break
# Don't enter directories that begin with '.'
for d in dirnames[:]:
if d.startswith('.'):
dirnames.remove(d)
dirnames.sort()
# Ignore files that begin with '.'
filenames = [f for f in filenames if not f.startswith('.')]
filenames.sort()
imageFilenames = [
os.path.join(dirpath, f) for f in filenames
]
# Process each image
for filename in imageFilenames:
self.bgImgs.append(Image.open(filename).convert('L'))
# Keep a cache of all images, scaled to the input image size
self.scaledBGImgs = [x.copy() for x in self.bgImgs]
# Pick a background at random.
idx = self._rng.randint(0, len(self.bgImgs) - 1)
bgImg = self.scaledBGImgs[idx]
# ---------------------------------------------------------------------------
# re-scale the background to the source image if necessary
if bgImg.size != image.size:
bgImg = self.scaledBGImgs[idx] = self.bgImgs[idx].resize(
image.size, Image.ANTIALIAS)
# ---------------------------------------------------------------------------
# Create the mask around the source image
mask = image.split()[-1]
if image.mode[-1] != 'A' or isSimpleBBox(mask):
mask = createMask(image,
threshold=self._threshold,
fillHoles=True,
backgroundColor=self.background,
blurRadius=self._blurRadius,
maskScale=self._maskScale)
# ---------------------------------------------------------------------------
# Paste the image onto the background
newImage = bgImg.copy()
newImage.paste(image, (0, 0), mask)
# Put an "all-on" alpha channel because we now want the network to consider the entire
# image
newImage.putalpha(ImageChops.constant(newImage, 255))
return newImage