def transform(img, source, target, **kwargs):
global js,jsName
if kwargs['Json File'] != jsName:
js = json.load(open(kwargs['Json File']))
jsName = kwargs['Json File']
index = kwargs['index'] if 'index' in kwargs else np.random.randint(0, len(js), 1)[0] #use given, if none given, pick.
dictionary = None
if str(index).isdigit(): #see if we are trying to reference by index, else search through values.
dictionary = js[int(index)]
else:
if index in js:
dictionary = js[index]
else:
for d in js:
if str(index) in d or d in index:
dictionary = js[d]
break
if not dictionary:
raise ValueError("{0} not found in {1}".format(index, jsName))
result = {}
result.update(dictionary)
if 'File Key' in kwargs and kwargs['File Key'] != '':
if os.path.isfile(dictionary[kwargs['File Key']]):
openImageFile(dictionary[kwargs['File Key']]).save(target)
result['file'] = dictionary[kwargs['File Key']]
return result, None
def test_rgb(self):
filename = self.locateFile('tests/images/test_project5.jpg')
img_wrapper = image_wrap.openImageFile(filename)
img = img_wrapper.to_array()
target_wrapper = image_wrap.ImageWrapper(img)
filename_output = tempfile.mktemp(prefix='mstcr',
suffix='.png',
dir='.')
self.filesToKill.extend([filename_output])
target_wrapper.save(filename_output)
args, error = plugins.callPlugin('SelectRegion',
img_wrapper,
filename,
filename_output,
alpha='yes')
wrapper = image_wrap.openImageFile(filename_output)
output = wrapper.to_array()
self.assertTrue(sum(sum(output[:, :, 3])) > 255)
x, y, w, h = widthandheight(output[:, :, 3])
if x > 1:
self.assertTrue(sum(sum(output[:, 0:x - 1, 3])) == 0)
if y > 1:
self.assertTrue(sum(sum(output[0:y - 1, :, 3])) == 0)
self.assertTrue(sum(sum(output[y + h + 1:, x + w + 1:, 3])) == 0)
self.assertEqual(output.shape[0], img.shape[0])
self.assertEqual(output.shape[1], img.shape[1])
self.assertTrue('paste_x' in args and args['paste_x'] > 0)
self.assertTrue('paste_y' in args and args['paste_y'] > 0)
def transform(img, source, target, **kwargs):
finalimage = openImageFile(kwargs['Final Image'])
output = None
if 'inputmaskname' not in kwargs:
pastemask, analsys, error = createMask(img, finalimage)
if error:
logging.getLogger('maskgen').error("Error creating inputmask " +
error)
splits = os.path.split(source)
pastemask.invert()
pastemask.save(splits[0] + '_inputmask.png')
pastemask = pastemask.to_array()
output = {'inputmaskname': splits[0] + '_inputmask.png'}
else:
pastemask = openImageFile(kwargs['inputmaskname']).to_array()
finalimage = finalimage.to_array()
sourceimg = np.copy(img.to_array()).astype('float')
if len(pastemask.shape) > 2:
if pastemask.shape[2] > 3:
mult = pastemask[:, :, 3] / 255.0
else:
mult = pastemask[:, :, 1] / 255.0
else:
mult = pastemask / 255.0
for dim in range(sourceimg.shape[2]):
sourceimg[:,:,dim] = \
(sourceimg[:,:,dim]*(1.0-mult)).astype('uint8') + \
(finalimage[:,:,dim]*(mult)).astype('uint8')
ImageWrapper(sourceimg.astype('uint8')).save(target)
return output, None
def test_something(self):
filename = self.locateFile('tests/images/test_project1.jpg')
wrapper = image_wrap.openImageFile(filename)
filename_output = tempfile.mktemp(prefix='mstcr',
suffix='.png',
dir='.')
self.addFileToRemove(filename_output)
img = numpy.asarray(wrapper)
image_wrap.ImageWrapper(img).save(filename_output)
args, error = plugins.callPlugin('WienerFilter',
wrapper,
filename,
filename_output,
percentageChange=0.5)
wrapper = image_wrap.openImageFile(filename_output)
output = wrapper.to_array()
self.assertEqual(output.shape, img.shape)
diff = abs(output - img)
finaldiff = numpy.zeros((diff.shape[0], diff.shape[1]))
for i in range(3):
finaldiff = finaldiff + diff[:, :, i]
finaldiff[finaldiff > 0] = 1
self.assertTrue(
sum(sum(finaldiff)) /
(finaldiff.shape[0] * finaldiff.shape[1]) > 0.8)
def test_typical(self):
img_wrapper = image_wrap.openImageFile(
self.locateFile('tests/images/test.png'))
img = img_wrapper.to_array()
img_wrapper = image_wrap.ImageWrapper(img)
target_wrapper = image_wrap.ImageWrapper(img)
filename = self.locateFile('tests/images/test.png')
filename_output = tempfile.mktemp(prefix='mstcr',
suffix='.png',
dir='.')
self.filesToKill.extend([filename_output])
target_wrapper.save(filename_output)
args, error = plugins.callPlugin('SmartMaskSelector',
img_wrapper,
filename,
filename_output,
smallw=100,
smallh=100,
mediumw=150,
mediumh=150,
largew=200,
largeh=200,
size=2,
op=2)
wrapper = image_wrap.openImageFile(filename_output)
output = wrapper.to_array()
self.assertTrue(img_wrapper.size[1] == wrapper.size[1])
self.assertTrue(img_wrapper.size[0] == wrapper.size[0])
self.assertTrue(len(output.shape) == 2)
totalsize = sum(sum(output / 255))
print totalsize
self.assertTrue(totalsize <= (1.5 * 22500))
self.assertTrue(totalsize >= (22500 * 0.5))
self.assertTrue('paste_x' in args and args['paste_x'] > 0)
self.assertTrue('paste_y' in args and args['paste_y'] > 0)
def xtest_mask_gen(self):
from maskgen import tool_set
from maskgen.image_wrap import ImageWrapper
aorig = image_wrap.openImageFile('tests/images/0c5a0bed2548b1d77717b1fb4d5bbf5a-TGT-17-CLONE.png')
a = aorig.convert('YCbCr')
borig = image_wrap.openImageFile('tests/images/0c5a0bed2548b1d77717b1fb4d5bbf5a-TGT-18-CARVE.png')
b = borig.convert('YCbCr')
mask = tool_set._tallySeam((a.to_array()[:, :, 0]),
(b.to_array()[20:, :, 0]))
ImageWrapper(mask).save('seam_mask.png')
def test_opacity_analysis(self):
# need to redo with generated data.
initialImage = image_wrap.openImageFile(self.locateFile('tests/images/pre_blend.png'))
finalImage = image_wrap.openImageFile(self.locateFile('tests/images/post_blend.png'))
mask = image_wrap.openImageFile(self.locateFile('tests/images/blend_mask.png'))
donorMask = image_wrap.openImageFile(self.locateFile('tests/images/donor_to_blend_mask.png'))
donorImage = image_wrap.openImageFile(self.locateFile('tests/images/donor_to_blend.png'))
result = tool_set.generateOpacityImage(initialImage.to_array(), donorImage.to_array(), finalImage.to_array(), mask.to_array(),
donorMask.to_array(),None)
min = np.min(result)
max = np.max(result)
result = (result - min)/(max-min) * 255.0
def test_mask_withsame_size(self):
analyzer = FrameAnalyzer(199.87494824016565, 233.18743961352658, 33.31249137336093)
f1 = openImageFile(self.locateFile('tests/algorithms/f1.png')).image_array
f2 = openImageFile(self.locateFile('tests/algorithms/f2.png')).image_array
analyzer.updateFlow(f1, f2, 'forward')
flow_manager = OpticalFlow(f1, f2, analyzer.back_flow, analyzer.jump_flow)
frame = flow_manager.setTime(0.0)
self.assertEqual(0, np.sum(abs(frame - f1)))
frame = flow_manager.setTime(0.1)
self.assertTrue( np.sum(abs(frame - f1)) < np.sum(abs(frame - f2)))
print np.sum(abs(frame - f2))
frame = flow_manager.setTime(0.9)
self.assertTrue(np.sum(abs(frame - f1)) > np.sum(abs(frame - f2)))
frame = flow_manager.setTime(1.0)
self.assertEqual(0, np.sum(abs(frame - f2)))
def test_noise(self):
img_wrapper = image_wrap.openImageFile(
self.locateFile('tests/images/test_project1.jpg'))
filename_output = tempfile.mktemp(prefix='cstcr',
suffix='.png',
dir='.')
self.filesToKill.extend([filename_output])
img_wrapper.save(filename_output)
args, error = plugins.callPlugin(
'MagickAddNoise', img_wrapper,
self.locateFile('tests/images/test_project1.jpg'), filename_output,
**{"Noise Type": "salt-pepper"})
wrapper = image_wrap.openImageFile(filename_output)
output = wrapper.to_array()
self.assertTrue(output.shape == img_wrapper.to_array().shape)
def transform(img, source, target, **kwargs):
# NOTE: arguments passed on AS IS!!
im = openImageFile(source, args=kwargs)
imarray = np.array(im)
#deal with grayscale image
if len(imarray.shape) == 2:
w, h = imarray.shape
ret = np.empty((w, h, 3), dtype=np.uint8)
ret[:, :, :] = imarray[:, :, np.newaxis]
imarray = ret
analysis = {}
if 'Crop' in kwargs and kwargs['Crop'] == 'yes':
dims = getExifDimensions(source, crop=True)
if len(dims) > 0 and imarray.shape[0] != dims[0][0]:
h = int(imarray.shape[0] - dims[0]) / 2
w = int(imarray.shape[1] - dims[1]) / 2
imarray = imarray[h:-h, w:-w]
analysis['location'] = str((h, w))
if 'Image Rotated' in kwargs and kwargs['Image Rotated'] == 'yes':
orientation = exif.getOrientationFromExif(source)
if orientation is not None:
analysis.update(exif.rotateAnalysis(orientation))
imarray = exif.rotateAccordingToExif(imarray,
orientation,
counter=True)
ImageWrapper(imarray).save(target, format='PNG')
analysis['Image Rotated'] = 'yes' if 'rotation' in analysis else 'no'
return analysis, None
def transform(img, source, target, **kwargs):
img_to_paste = openImageFile(kwargs['donor'])
pasteregionsize = kwargs['region size'] if 'region size' in kwargs else 1.0
approach = kwargs['approach'] if 'approach' in kwargs else 'simple'
segment_algorithm = kwargs[
'segment'] if 'segment' in kwargs else 'felzenszwalb'
if pasteregionsize < 1.0:
dims = (int(img.size[1] * pasteregionsize),
int(img.size[0] * pasteregionsize))
else:
dims = (img.size[1], img.size[0])
x = (img.size[1] - dims[0]) / 2
y = (img.size[0] - dims[1]) / 2
imgarray = np.asarray(img)
if len(imgarray.shape) > 2:
newimg = imgarray[x:dims[0] + x, y:dims[1] + y, :]
else:
newimg = imgarray[x:dims[0] + x, y:dims[1] + y]
transform_matrix, out = performPaste(ImageWrapper(newimg), img_to_paste,
approach, segment_algorithm)
if pasteregionsize < 1.0:
out2 = np.copy(imgarray)
if len(imgarray.shape) > 2:
out2[x:dims[0] + x, y:dims[1] + y, :] = out
else:
out2[x:dims[0] + x, y:dims[1] + y] = out
out = out2
ImageWrapper(out).save(target)
return {
'transform matrix': tool_set.serializeMatrix(transform_matrix)
} if transform_matrix is not None else None, None
def test_shrink(self):
filename = self.locateFile('tests/algorithms/twins.jpg')
img = openImageFile(filename)
#img = openImageFile(filename, False, None)
somemask = img.to_array()
somemaskcopy = somemask
sc = SeamCarver(
filename, shape=(350, 450), energy_function=SobelFunc()
) # mask_filename=self.locateFile('tests/algorithms/cat_mask.png'))
image, mask = sc.remove_seams()
#ImageWrapper(image).save(os.path.join(os.path.dirname(filename), 'twins_f.png'))
#ImageWrapper(mask).save(os.path.join(os.path.dirname(filename), 'twins_m.png'))
radj, cadj = sc.mask_tracker.save_adjusters('adjusters.png')
sc.mask_tracker.read_adjusters(radj, cadj)
sc.mask_tracker.save_neighbors_mask('twins_m.png')
os.remove(radj)
os.remove(cadj)
os.remove('twins_m.png')
somemask = sc.mask_tracker.move_pixels(somemask)
#ImageWrapper(somemask).save(os.path.join(os.path.dirname(filename), 'twins_sm.png'))
self.assertTrue(image.shape == somemask.shape)
self.assertTrue(np.all(image == somemask))
self.assertTrue(
(image.shape[0],
image.shape[1]) == sc.mask_tracker.neighbors_mask.shape)
originalmask = sc.mask_tracker.invert_move_pixels(somemask)
self.assertTrue(somemaskcopy.shape == originalmask.shape)
#ImageWrapper(somemaskcopy).save(os.path.join(os.path.dirname(filename), 'twins_om.png'))
#ImageWrapper(originalmask).save(os.path.join(os.path.dirname(filename), 'twins_om2.png'))
self.assertTrue(
np.all(somemaskcopy[mask == 0] == originalmask[mask == 0]))
def run_plugin(argv=None):
import argparse
import itertools
parser = argparse.ArgumentParser(description='')
parser.add_argument('--plugin', help='name of plugin', required=True)
parser.add_argument('--input', help='base image or video', required=True)
parser.add_argument('--output',
help='result image or video',
required=True)
parser.add_argument(
'--arguments',
nargs='+',
default={},
help='Additional operation/plugin arguments e.g. rotation 60')
args = parser.parse_args()
op = software_loader.getOperation(getOperation(args.plugin)['name'])
parsedArgs = dict(
itertools.izip_longest(*[iter(args.arguments)] * 2, fillvalue=""))
for key in parsedArgs:
parsedArgs[key] = validateAndConvertTypedValue(
key, parsedArgs[key], op, skipFileValidation=False)
loadPlugins()
args, msg = callPlugin(args.plugin, openImageFile(args.input), args.input,
args.output, **parsedArgs)
if msg is not None:
print(msg)
if args is not None:
print('Results:')
print(str(args))
def test_something(self):
img = numpy.random.randint(0, 255, (500, 500, 3), dtype='uint8')
mask = numpy.zeros((500, 500), dtype='uint8')
mask[30:50, 30:50] = 255
self.assertTrue(
sum(sum(sum(img[30:50, 30:50] - img[400:420, 300:320]))) > 0)
img_wrapper = image_wrap.ImageWrapper(img)
target_wrapper = image_wrap.ImageWrapper(mask)
mask_wrapper = image_wrap.ImageWrapper(mask)
filename = tempfile.mktemp(prefix='mstc', suffix='.png', dir='.')
filename_mask = tempfile.mktemp(prefix='mstcm', suffix='.png', dir='.')
filename_output = tempfile.mktemp(prefix='mstcr',
suffix='.png',
dir='.')
self.filesToKill.extend([filename, filename_mask, filename_output])
img_wrapper.save(filename)
mask_wrapper.save(filename_mask)
target_wrapper.save(filename_output)
args, error = plugins.callPlugin('DesignPasteClone',
img_wrapper,
filename,
filename_output,
inputmaskname=filename_mask,
paste_x=300,
paste_y=400)
wrapper = image_wrap.openImageFile(filename_output)
output = wrapper.to_array()
self.assertTrue(
sum(sum(sum(img[30:50, 30:50] - output[400:420, 300:320]))) == 0)
def test_something(self):
img = numpy.random.randint(0, 255, (500, 500, 3), dtype='uint8')
wrapper = image_wrap.ImageWrapper(img)
filename = tempfile.mktemp(prefix='mstc', suffix='.png', dir='.')
filename_output = tempfile.mktemp(prefix='mstcr',
suffix='.png',
dir='.')
self.filesToKill.append(filename)
wrapper.save(filename)
self.filesToKill.append(filename_output)
image_wrap.ImageWrapper(img).save(filename_output)
args, error = plugins.callPlugin('MedianBlur',
wrapper,
filename,
filename_output,
kernelSize=25,
percentageChange=0.5)
wrapper = image_wrap.openImageFile(filename_output)
output = wrapper.to_array()
self.assertEqual(output.shape, img.shape)
diff = abs(output - img)
finaldiff = numpy.zeros((500, 500))
for i in range(3):
finaldiff = finaldiff + diff[:, :, i]
finaldiff[finaldiff > 0] = 1
self.assertTrue(abs(sum(sum(finaldiff)) - 62500) < 100)
def test_snap(self):
img = numpy.zeros((500, 500), dtype='uint8')
wrapper = image_wrap.ImageWrapper(img)
filename = tempfile.mktemp(prefix='mstc', suffix='.png', dir='.')
filename_output = tempfile.mktemp(prefix='mstcr',
suffix='.png',
dir='.')
self.filesToKill.append(filename)
wrapper.save(filename)
self.filesToKill.append(filename_output)
image_wrap.ImageWrapper(img).save(filename_output)
args, error = plugins.callPlugin('CropSelector',
wrapper,
filename,
filename_output,
percentage_width=0.1,
percentage_height=0.1,
eightbit_boundary='yes')
wrapper = image_wrap.openImageFile(filename_output)
output = wrapper.to_array()
self.assertEqual(output.shape, img.shape)
self.assertTrue('crop_x' in args and args['crop_x'] <= 56)
self.assertTrue('crop_y' in args and args['crop_y'] <= 56)
self.assertTrue('crop_width' in args and args['crop_width'] == 56)
self.assertTrue('crop_height' in args and args['crop_height'] == 56)
self.assertTrue(args['crop_y'] % 8 == 0)
self.assertTrue(args['crop_x'] % 8 == 0)
self.assertTrue(
output[-(args['crop_height'] - args['crop_y'] + 1),
-(args['crop_width'] - args['crop_x'] + 1)] == 255)
self.assertTrue(
output[-(args['crop_height'] - args['crop_y'] - 1),
-(args['crop_width'] - args['crop_x'] - 1)] == 0)
def test_seam_carve(self):
img_wrapper = image_wrap.openImageFile(self.locateFile('tests/images/test_project5.jpg'))
img = img_wrapper.to_array()
mask = np.zeros(img.shape).astype('uint8')
cv2.circle(mask, (img.shape[0]/8,img.shape[1]/8), img.shape[0]/16, (255, 0, 0), -1)
cv2.circle(mask, (img.shape[0] *5/ 8, img.shape[1] *5/ 8), img.shape[0] / 16, (0, 255, 0), -1)
mask_wrapper = image_wrap.ImageWrapper(mask)
mask_output = tempfile.mktemp(prefix='mstcr', suffix='.png', dir='.')
self.addFileToRemove(mask_output)
mask_wrapper.save(mask_output)
target_wrapper = image_wrap.ImageWrapper(img)
filename = self.locateFile('tests/images/test_project5.jpg')
filename_output = tempfile.mktemp(prefix='mstcr', suffix='.jpg', dir='.')
self.addFileToRemove(filename_output)
target_wrapper.save(filename_output)
args,error = plugins.callPlugin('SeamCarve',
img_wrapper,
filename,
filename_output,
inputmaskname=os.path.abspath(mask_output),
percentage_height=0.95,
percentage_width=0.95)
output_files = args['output_files']
self.assertTrue('column adjuster' in output_files and os.path.exists(output_files['column adjuster']))
self.assertTrue('row adjuster' in output_files and os.path.exists(output_files['row adjuster']))
self.assertTrue('plugin mask' in output_files and os.path.exists(output_files['plugin mask']))
self.assertTrue('neighbor mask' in output_files and os.path.exists(output_files['neighbor mask']))
for v in output_files.values():
os.remove(v)
def test_shrink_forward_energy_arch(self):
#filename = self.locateFile('tests/algorithms/arch_sunset.jpg')
#newshape = (470, 250)
filename = self.locateFile('tests/algorithms/pexels-photo-746683.jpg')
newshape = (1450, 1950)
img = openImageFile(filename)
imgcopy = img.to_array()
sc = SeamCarver(filename,
shape=newshape,
energy_function=SobelFunc(),
seam_function=foward_base_energy_function,
keep_size=True)
image, mask = sc.remove_seams()
#ImageWrapper(image).save(os.path.join(os.path.dirname(filename), 'as_f.png'))
#ImageWrapper(mask).save(os.path.join(os.path.dirname(filename), 'as_m.png'))
#radj, cadj = sc.mask_tracker.save_adjusters('adjusters.png')
#sc.mask_tracker.read_adjusters( radj, cadj )
sc.mask_tracker.save_neighbors_mask('as_m.png')
imgcopymoved = sc.mask_tracker.move_pixels(imgcopy)
#ImageWrapper(somemask).save(os.path.join(os.path.dirname(filename), 'as_sm.png'))
self.assertTrue(image.shape == imgcopymoved.shape)
self.assertTrue(np.all(image == imgcopymoved))
self.assertTrue(
(image.shape[0],
image.shape[1]) == sc.mask_tracker.neighbors_mask.shape)
originalmask = sc.mask_tracker.invert_move_pixels(imgcopymoved)
self.assertTrue(imgcopy.shape == originalmask.shape)
#ImageWrapper(imgcopymoved).save(os.path.join(os.path.dirname(filename), 'as_om.png'))
#ImageWrapper(originalmask).save(os.path.join(os.path.dirname(filename), 'as_om2.png'))
self.assertTrue(np.all(imgcopy[mask == 0] == originalmask[mask == 0]))
def test_compare(self):
from maskgen import tool_set
wrapper1 = image_wrap.openImageFile(
self.locateFile('tests/images/pre_blend.png'))
arr2 = np.copy(wrapper1.image_array)
for x in np.random.randint(1, arr2.shape[0] - 1, 100):
for y in np.random.randint(1, arr2.shape[1] - 1, 100):
arr2[x, y, 1] = arr2[x, y, 1] + np.random.randint(-20, 20)
arr2[100:200, 100:200, 2] = arr2[100:200, 100:200, 2] - 25
wrapper2 = image_wrap.ImageWrapper(arr2)
args = [{
'aggregate': 'luminance',
'minimum threshold': 3,
"weight": 4
}, {
'aggregate': 'luminance',
'minimum threshold': 3,
"weight": 1
}, {
'aggregate': 'max'
}]
for arg in args:
result = tool_set.mediatedCompare(
wrapper1.to_array().astype('int16'),
wrapper2.to_array().astype('int16'),
arguments=arg)
self.assertTrue(np.all(result[0][100:200, 100:200] == 255))
result[0][100:200, 100:200] = 0
self.assertTrue(np.all(result[0] == 0))
def find_segmentation_classifier(image_name, segmentation_directory):
import os
real_name = os.path.split(image_name)[0]
dotpos = min(33, real_name.find('.'))
real_name = real_name[0:dotpos]
segment_name = os.path.join(segmentation_directory, real_name + '.png')
return image_wrap.openImageFile(segment_name) if os.path.exists(
segment_name) else None
def transform(img, source, target, **kwargs):
donor = kwargs['donor'] # raise error if missing donor
im_source = openImageFile(source).image_array
im_donor_trace = openImageFile(donor).image_array
if np.shape(im_source)[0:2] != np.shape(im_donor_trace)[0:2]:
orientation_source = np.shape(im_source)[0] - np.shape(im_source)[1]
orientation_donor = np.shape(im_donor_trace)[0] - np.shape(
im_donor_trace)[1]
if sign(orientation_source) != sign(orientation_donor):
im_donor_trace = np.rot90(im_donor_trace, -1)
location, im_source = centeredCrop(im_source, im_donor_trace)
ImageWrapper(im_source).save(target, format='PNG')
else:
location = (0, 0)
return {'location': location}, None
def test_gamma(self):
img_wrapper = image_wrap.openImageFile(
self.locateFile('tests/images/test_project1.jpg'))
filename_output = tempfile.mktemp(prefix='cstcr',
suffix='.png',
dir='.')
self.filesToKill.extend([filename_output])
img_wrapper.save(filename_output)
args, error = plugins.callPlugin(
'ManualGammaCorrection',
img_wrapper,
self.locateFile('tests/images/test_project1.jpg'),
filename_output,
gamma=2.0)
wrapper = image_wrap.openImageFile(filename_output)
output = wrapper.to_array()
self.assertTrue(output.shape == img_wrapper.to_array().shape)
def transform(img, source, target, **kwargs):
donor = kwargs['donor']
sizSource = img.size
sizDonor = openImageFile(donor).size
validateImageSizes(sizSource, sizDonor)
# Use Liquid Rescale to resize donor image
# to size of source image.
resizeUsingLQR(target, sizDonor)
return None, None
def transform(img, source, target, **kwargs):
channel_map = {"red": 0, "green": 1, "blue": 2}
donor = kwargs['mask'] if 'mask' in kwargs else source
channel_name = kwargs['channel'] if 'channel' in kwargs else "green"
img = openImageFile(donor)
color_im = np.zeros((img.size[1], img.size[0], 3), dtype=np.uint8)
color_im[:, :, channel_map[channel_name]] = img.image_array
ImageWrapper(color_im).save(target)
return None, None
def test_contrast(self):
img_wrapper = image_wrap.openImageFile(
self.locateFile('tests/images/test_project1.jpg'))
filename_output = tempfile.mktemp(prefix='cstcr',
suffix='_c.png',
dir='.')
self.filesToKill.extend([filename_output])
img_wrapper.save(filename_output)
args, error = plugins.callPlugin(
'Constrast',
img_wrapper,
self.locateFile('tests/images/test_project1.jpg'),
filename_output,
direction="increase")
wrapper = image_wrap.openImageFile(filename_output)
output = wrapper.to_array()
self.assertTrue(output.shape == img_wrapper.to_array().shape)
def check_save(self, wrapper, foarmat):
dir = os.path.dirname(self.locateFile('tests/images/postfill.png'))
fname = os.path.join(dir,
'foo.' + ('tif' if foarmat != 'PNG' else 'png'))
self.addFileToRemove(fname)
wrapper.save(fname, format=foarmat)
compareWrapper = image_wrap.openImageFile(fname)
self.assertTrue(
(compareWrapper.image_array == wrapper.image_array).all())
def test_two_channel(self):
wrapper = image_wrap.openImageFile(
self.locateFile('tests/images/two_channel.jpg'))
wrapper.to_mask()
wrapper.apply_transparency()
wrapper.convert('L')
wrapper.convert('RGBA')
wrapper.to_float()
wrapper.to_rgb()
def draw(self, frame, filename):
from maskgen.analytics.analysis import ela
im = ela(openImageFile(filename))
photo = ImageTk.PhotoImage(
fixTransparency(imageResize(im, (400, 400))).toPIL())
canvas = Canvas(frame, width=400, height=400)
canvas.create_image(0, 0, image=photo, anchor=NW)
canvas.grid(row=0, column=0)
return (im, photo)
def test_modulate(self):
img_wrapper = image_wrap.openImageFile(
self.locateFile('tests/images/test_project1.jpg'))
filename_output = tempfile.mktemp(prefix='cstcr',
suffix='.png',
dir='.')
self.filesToKill.extend([filename_output])
img_wrapper.save(filename_output)
args, error = plugins.callPlugin(
'MagickModulate',
img_wrapper,
self.locateFile('tests/images/test_project1.jpg'),
filename_output,
saturation=130,
brightness=130)
wrapper = image_wrap.openImageFile(filename_output)
output = wrapper.to_array()
self.assertTrue(output.shape == img_wrapper.to_array().shape)
def transform(img, source, target, **kwargs):
rgba = img.convert('RGBA')
donor_img_file = kwargs['donor']
inputmask = openImageFile(donor_img_file)
donor = inputmask.convert('RGBA')
if donor.size != rgba.size:
donor = donor.resize(rgba.size, Image.ANTIALIAS)
rgba.paste(donor, (0, 0), donor)
rgba.save(target)
return None, None
