def process_image(self, input_file, output_file=None, focal_point=None, backend_name='default'):
"""
Run this filter on the given image file then write the result into output_file and return it
If output_file is not given, a new BytesIO will be used instead
"""
# Get backend
backend = get_image_backend(backend_name)
# Parse spec string
method_name, method_arg = self._method
# Open image
input_file.open('rb')
image = backend.open_image(input_file)
file_format = image.format
# Process image
method = getattr(backend, method_name)
image = method(image, method_arg, focal_point=focal_point)
# Make sure we have an output file
if output_file is None:
output_file = BytesIO()
# Write output
backend.save_image(image, output_file, file_format)
# Close the input file
input_file.close()
return output_file
def process_image(self, input_file, output_file=None, focal_point=None, backend_name='default'):
"""
Run this filter on the given image file then write the result into output_file and return it
If output_file is not given, a new BytesIO will be used instead
"""
# Get backend
backend = get_image_backend(backend_name)
# Parse spec string
method_name, method_arg = self._method
# Open image
input_file.open('rb')
image = backend.open_image(input_file)
file_format = image.format
# Process image
method = getattr(backend, method_name)
image = method(image, method_arg, focal_point=focal_point)
# Make sure we have an output file
if output_file is None:
output_file = BytesIO()
# Write output
backend.save_image(image, output_file, file_format)
# Close the input file
input_file.close()
return output_file
def get_suggested_focal_point(self, backend_name='default'):
backend = get_image_backend(backend_name)
image_file = self.file.file
# Make sure image is open and seeked to the beginning
image_file.open('rb')
image_file.seek(0)
# Load the image
image = backend.open_image(self.file.file)
image_data = backend.image_data_as_rgb(image)
# Make sure we have image data
# If the image is animated, image_data_as_rgb will return None
if image_data is None:
return
# Use feature detection to find a focal point
feature_detector = FeatureDetector(image.size, image_data[0], image_data[1])
focal_point = feature_detector.get_focal_point()
# Add 20% extra room around the edge of the focal point
if focal_point:
focal_point.width *= 1.20
focal_point.height *= 1.20
return focal_point
def get_suggested_focal_point(self, backend_name='default'):
backend = get_image_backend(backend_name)
image_file = self.file.file
# Make sure image is open and seeked to the beginning
image_file.open('rb')
image_file.seek(0)
# Load the image
image = backend.open_image(self.file.file)
image_data = backend.image_data_as_rgb(image)
# Make sure we have image data
# If the image is animated, image_data_as_rgb will return None
if image_data is None:
return
# Use feature detection to find a focal point
feature_detector = FeatureDetector(image.size, image_data[0],
image_data[1])
focal_point = feature_detector.get_focal_point()
# Add 20% extra room around the edge of the focal point
if focal_point:
focal_point.width *= 1.20
focal_point.height *= 1.20
return focal_point
def get_suggested_focal_point(self, backend_name='default'):
backend = get_image_backend(backend_name)
image_file = self.file.file
# Make sure image is open and seeked to the beginning
image_file.open('rb')
image_file.seek(0)
# Load the image
image = backend.open_image(self.file.file)
image_data = backend.image_data_as_rgb(image)
# Make sure we have image data
# If the image is animated, image_data_as_rgb will return None
if image_data is None:
return
# Use feature detection to find a focal point
feature_detector = FeatureDetector(image.size, image_data[0],
image_data[1])
faces = feature_detector.detect_faces()
if faces:
# Create a bounding box around all faces
left = min(face.left for face in faces)
top = min(face.top for face in faces)
right = max(face.right for face in faces)
bottom = max(face.bottom for face in faces)
focal_point = Rect(left, top, right, bottom)
else:
features = feature_detector.detect_features()
if features:
# Create a bounding box around all features
left = min(feature[0] for feature in features)
top = min(feature[1] for feature in features)
right = max(feature[0] for feature in features)
bottom = max(feature[1] for feature in features)
focal_point = Rect(left, top, right, bottom)
else:
return None
# Add 20% to width and height and give it a minimum size
x, y = focal_point.centroid
width, height = focal_point.size
width *= 1.20
height *= 1.20
width = max(width, 100)
height = max(height, 100)
return Rect.from_point(x, y, width, height)
def get_suggested_focal_point(self, backend_name='default'):
backend = get_image_backend(backend_name)
image_file = self.file.file
# Make sure image is open and seeked to the beginning
image_file.open('rb')
image_file.seek(0)
# Load the image
image = backend.open_image(self.file.file)
image_data = backend.image_data_as_rgb(image)
# Make sure we have image data
# If the image is animated, image_data_as_rgb will return None
if image_data is None:
return
# Use feature detection to find a focal point
feature_detector = FeatureDetector(image.size, image_data[0], image_data[1])
faces = feature_detector.detect_faces()
if faces:
# Create a bounding box around all faces
left = min(face.left for face in faces)
top = min(face.top for face in faces)
right = max(face.right for face in faces)
bottom = max(face.bottom for face in faces)
focal_point = Rect(left, top, right, bottom)
else:
features = feature_detector.detect_features()
if features:
# Create a bounding box around all features
left = min(feature[0] for feature in features)
top = min(feature[1] for feature in features)
right = max(feature[0] for feature in features)
bottom = max(feature[1] for feature in features)
focal_point = Rect(left, top, right, bottom)
else:
return None
# Add 20% to width and height and give it a minimum size
x, y = focal_point.centroid
width, height = focal_point.size
width *= 1.20
height *= 1.20
width = max(width, 100)
height = max(height, 100)
return Rect.from_point(x, y, width, height)
def process_image(self, input_file, backend_name='default'):
"""
Given an input image file as a django.core.files.File object,
generate an output image with this filter applied, returning it
as another django.core.files.File object
"""
backend = get_image_backend(backend_name)
if not self.method:
self._parse_spec_string()
# If file is closed, open it
input_file.open('rb')
image = backend.open_image(input_file)
file_format = image.format
method = getattr(backend, self.method_name)
image = method(image, self.method_arg)
output = StringIO.StringIO()
backend.save_image(image, output, file_format)
# and then close the input file
input_file.close()
# generate new filename derived from old one, inserting the filter spec string before the extension
input_filename_parts = os.path.basename(input_file.name).split('.')
filename_without_extension = '.'.join(input_filename_parts[:-1])
filename_without_extension = filename_without_extension[:60] # trim filename base so that we're well under 100 chars
output_filename_parts = [filename_without_extension, self.spec] + input_filename_parts[-1:]
output_filename = '.'.join(output_filename_parts)
output_file = File(output, name=output_filename)
return output_file
def process_image(self, input_file, backend_name='default'):
"""
Given an input image file as a django.core.files.File object,
generate an output image with this filter applied, returning it
as another django.core.files.File object
"""
backend = get_image_backend(backend_name)
if not self.method:
self._parse_spec_string()
# If file is closed, open it
input_file.open('rb')
image = backend.open_image(input_file)
file_format = image.format
method = getattr(backend, self.method_name)
image = method(image, self.method_arg)
output = StringIO.StringIO()
backend.save_image(image, output, file_format)
# and then close the input file
input_file.close()
# generate new filename derived from old one, inserting the filter spec string before the extension
input_filename_parts = os.path.basename(input_file.name).split('.')
filename_without_extension = '.'.join(input_filename_parts[:-1])
filename_without_extension = filename_without_extension[:
60] # trim filename base so that we're well under 100 chars
output_filename_parts = [filename_without_extension, self.spec
] + input_filename_parts[-1:]
output_filename = '.'.join(output_filename_parts)
output_file = File(output, name=output_filename)
return output_file
def test_default_backend(self):
# default backend should be pillow
backend = get_image_backend()
self.assertTrue(isinstance(backend, PillowBackend))
def test_default_backend(self):
# default backend should be pillow
backend = get_image_backend()
self.assertTrue(isinstance(backend, PillowBackend))