def pythonSaveToPSD(image):
# Prep
pdb.gimp_image_undo_group_start(image)
pdb.gimp_context_push()
# Code
drawable = pdb.gimp_image_get_active_drawable(image)
filename = pdb.gimp_image_get_filename(image)
temp = filename.replace("_CLEAN", "")
temp2 = temp.replace("_EDIT", "")
temp = temp2.replace("_XCF", "")
filename = temp.replace("_PSD", "")
path = os.path.dirname(filename)
path += "_PSD"
name = os.path.basename(filename)
out_psd = os.path.join(path, name)
out_psd = os.path.splitext(out_psd)[0] + '.psd'
# Create folder
if not os.path.exists(path):
os.makedirs(path)
# Save in PSD
pdb.gimp_file_save(image, drawable, out_psd, out_psd)
pdb.gimp_image_clean_all(image)
# Finish
pdb.gimp_context_pop()
pdb.gimp_image_undo_group_end(image)
pdb.gimp_displays_flush()
def pythonSaveToClean(image):
# Prep
pdb.gimp_image_undo_group_start(image)
pdb.gimp_context_push()
# Code
filename_old = pdb.gimp_image_get_filename(image)
filename = filename_old.replace("_CLEAN", "")
# drawable = pdb.gimp_image_get_active_drawable(image)
path = os.path.dirname(filename)
path += "_CLEAN"
name = os.path.basename(filename)
out_file = os.path.join(path, name)
# Create CLEAN folder
if not os.path.exists(path):
os.makedirs(path)
# Merge visible layers in new image and export in CLEAN folder
new_image = pdb.gimp_image_duplicate(image)
layer = pdb.gimp_image_merge_visible_layers(new_image, CLIP_TO_IMAGE)
pdb.gimp_file_save(new_image, layer, out_file, out_file)
pdb.gimp_image_delete(new_image)
pdb.gimp_image_clean_all(image)
# Finish
pdb.gimp_context_pop()
pdb.gimp_image_undo_group_end(image)
pdb.gimp_displays_flush()
def pythonSaveToEditJpeg(image):
# Prep
pdb.gimp_image_undo_group_start(image)
pdb.gimp_context_push()
# Code
# drawable = pdb.gimp_image_get_active_drawable(image)
filename = pdb.gimp_image_get_filename(image)
temp = filename.replace("_CLEAN", "")
temp2 = temp.replace("_EDIT", "")
filename = temp2.replace("_XCF", "")
path = os.path.dirname(filename)
path += "_EDIT"
name = os.path.basename(filename)
out_file = os.path.join(path, name)
out_file = os.path.splitext(out_file)[0] + '.jpg'
# Create _EDIT folder
if not os.path.exists(path):
os.makedirs(path)
# Merge visible layers in new image and export in JPEG
new_image = pdb.gimp_image_duplicate(image)
layer = pdb.gimp_image_merge_visible_layers(new_image, CLIP_TO_IMAGE)
pdb.gimp_file_save(new_image, layer, out_file, out_file)
pdb.gimp_image_delete(new_image)
pdb.gimp_image_clean_all(image)
# Finish
pdb.gimp_context_pop()
pdb.gimp_image_undo_group_end(image)
pdb.gimp_displays_flush()
def make_captcha(sx, sy, font_height, letter_spacing, left_margin, angle_range,
fonts, answer):
"""Generate a captcha consisting of the letters in answer.
:rtype: :class:`gimp.Image`
:returns: The CAPTCHA as a gimp-python image object.
"""
img = gimp.Image(sx, sy, RGB_IMAGE)
img.disable_undo()
light_noise_layer = gimp.Layer(img, 'light noise', sx, sy, RGB_IMAGE, 100,
NORMAL_MODE)
img.add_layer(light_noise_layer, 0)
gpdb.gimp_selection_none(img)
gpdb.gimp_drawable_fill(light_noise_layer, WHITE_FILL)
# plug_in_randomize_hurl at 1% 1 time is vastly superior to
# scatter_rgb here, but has a bug where it creates an artifact at
# the top of the image when invoked in a scripting context like
# this.
#
# Future experiment: dial down the amount of noise generated by
# scatter, then run it through levels to darken it, then
# blur. This should be equivalent to hurl + blur.
#gpdb.plug_in_randomize_hurl(img, light_noise_layer, 1, 1, 0, 0)
gpdb.plug_in_scatter_hsv(img, light_noise_layer, 1, 25, 200, 180)
gpdb.plug_in_gauss_iir(img, light_noise_layer, 1, 1, 1)
gpdb.gimp_desaturate(light_noise_layer)
# Next make pure black layer which we will copy repeatedly as a
# place to cut out letters.
blackLayer = gimp.Layer(img, 'black', sx, sy, RGB_IMAGE, 100, NORMAL_MODE)
img.add_layer(blackLayer, 0)
blackLayer.add_alpha()
gpdb.gimp_layer_add_alpha(blackLayer)
gpdb.gimp_drawable_fill(blackLayer, WHITE_FILL)
gpdb.gimp_invert(blackLayer)
# Loop through each letter, making it a separate black layer.
right = left_margin
last_substrate = None
for letter in answer:
font = random.choice(FONTS)
substrate = blackLayer.copy()
img.add_layer(substrate, 0)
new_right = cookie_cutter_letter(img, substrate, right, font, letter)
# look out for really narrow letters
if new_right - right < 20:
new_right += 5
right = new_right
img.remove_layer(blackLayer)
# Hide the light noise layer, then collapse all the remaining
# layers (all letters) into a single layer.
light_noise_layer.visible = False
textLayer = gpdb.gimp_image_merge_visible_layers(img, CLIP_TO_IMAGE)
light_noise_layer.visible = True
# Create a layer of dark noise which will display the letters.
dark_noise_layer = gimp.Layer(img, 'dark noise', sx, sy, RGB_IMAGE, 100,
MULTIPLY_MODE)
img.add_layer(dark_noise_layer, 1)
gpdb.gimp_drawable_fill(dark_noise_layer, WHITE_FILL)
gpdb.plug_in_randomize_hurl(img, dark_noise_layer, 25, 1, 0, 0)
gpdb.gimp_desaturate(dark_noise_layer)
# These next operations are ordered carefully. Changing the order
# dramatically affects how the output looks.
# Here's where we do the cutout operation.
gpdb.gimp_selection_layer_alpha(textLayer)
gpdb.gimp_selection_invert(img)
gpdb.gimp_edit_clear(dark_noise_layer)
gpdb.gimp_selection_none(img)
# After the cutout, blur the dark noise layer and then darken it:
gpdb.plug_in_gauss_iir(img, dark_noise_layer, 1, 1, 1)
gpdb.gimp_levels(dark_noise_layer, HISTOGRAM_VALUE, 127, 255, 0.25, 0, 255)
textLayer.visible = False
# If you start gimp without --no-interface with an X server, this
# line will let you see the image looks like at this point in the
# script, layers and all. It should be fine to move this line to
# any problematic part of the script for debugging.
#
# gimp.Display(gpdb.gimp_image_duplicate(img))
final = img.flatten()
gpdb.gimp_image_clean_all(img)
img.enable_undo()
return img, final
def runPlugin(
filename_input,
filename_result,
filename_face_detect,
filename_cascade,
colour_rectangle
) :
"""
This function gets registered with GIMP as it implements the following Plugin : Detect Faces
This function will attempt to detect faces within an image, and any faces which it does detect it will frame with a rectangle. Once it has finished doing this,
it will save the resulting image into a file.
Parameters:
filename_input (String) :
The filename of the input image.
filename_result (String) :
The filename of the file into which the resulting image will be saved.
filename_cascade (String) :
The filename of the Harr Transform Cascade file which should be used to detect the faces.
colour_rectangle (String) :
The colour to use for the face framing rectangles.
Returns:
NA
Invoked by :
GIMP
Invokes:
None
"""
nameProcedure = "runPlugin_single"
print("%s : Enter" % (nameProcedure))
print("%s : %s" % (nameProcedure, filename_input))
print("%s : %s" % (nameProcedure, filename_result))
print("%s : %s" % (nameProcedure, colour_rectangle))
# Open and display withih GIMP, the input image.
image_input = pdb.gimp_file_load(filename_input, filename_input)
pdb.gimp_display_new(image_input)
# "Clean" the following image by setting its Dirty (Edit) counter to 0.
#
# If this is not done and the user attempts to close the image, then GIMP will complain that the image has
# unsaved changes.
pdb.gimp_image_clean_all(image_input)
# Run the Face detection code on the Input image.
#
# At the time this Plugin was developed, Python and its Plugins could only be implemented using Python 2; whereas the Face detection code has
# unfortunately been implemented using Python 3 source code and modules. Therefore, if this Plugin were to try and run the Face detection code
# directly, then the Python Runtime system would fail. It is for this reason that the Face detection code has been invoked below as a separate
# processs.
subprocess.call(
[
"python3",
filename_face_detect,
filename_cascade,
filename_input,
filename_result,
colour_rectangle
]
)
# Open and display within GIMP, the result image.
image_result = pdb.gimp_file_load(filename_result, filename_result)
pdb.gimp_display_new(image_result)
# "Clean" the following image by setting its Dirty (Edit) counter to 0.
#
# If this is not done and the user attempts to close the image, then GIMP will complain that the image has
# unsaved changes.
pdb.gimp_image_clean_all(image_result)
print("%s : Exit" % (nameProcedure))
def make_captcha(sx, sy, font_height, letter_spacing, left_margin,
angle_range, fonts, answer):
"""Generate a captcha consisting of the letters in answer.
:rtype: :class:`gimp.Image`
:returns: The CAPTCHA as a gimp-python image object.
"""
img = gimp.Image(sx, sy, RGB_IMAGE)
img.disable_undo()
light_noise_layer = gimp.Layer(img, 'light noise', sx, sy,
RGB_IMAGE, 100, NORMAL_MODE)
img.add_layer(light_noise_layer, 0)
gpdb.gimp_selection_none(img)
gpdb.gimp_drawable_fill(light_noise_layer, WHITE_FILL)
# plug_in_randomize_hurl at 1% 1 time is vastly superior to
# scatter_rgb here, but has a bug where it creates an artifact at
# the top of the image when invoked in a scripting context like
# this.
#
# Future experiment: dial down the amount of noise generated by
# scatter, then run it through levels to darken it, then
# blur. This should be equivalent to hurl + blur.
#gpdb.plug_in_randomize_hurl(img, light_noise_layer, 1, 1, 0, 0)
gpdb.plug_in_scatter_hsv(img, light_noise_layer, 1, 25, 200, 180)
gpdb.plug_in_gauss_iir(img, light_noise_layer, 1, 1, 1)
gpdb.gimp_desaturate(light_noise_layer)
# Next make pure black layer which we will copy repeatedly as a
# place to cut out letters.
blackLayer = gimp.Layer(img, 'black', sx, sy, RGB_IMAGE, 100, NORMAL_MODE)
img.add_layer(blackLayer, 0)
blackLayer.add_alpha()
gpdb.gimp_layer_add_alpha(blackLayer)
gpdb.gimp_drawable_fill(blackLayer, WHITE_FILL)
gpdb.gimp_invert(blackLayer)
# Loop through each letter, making it a separate black layer.
right = left_margin
last_substrate = None
for letter in answer:
font = random.choice(FONTS)
substrate = blackLayer.copy()
img.add_layer(substrate, 0)
new_right = cookie_cutter_letter(img, substrate, right, font, letter)
# look out for really narrow letters
if new_right - right < 20:
new_right += 5
right = new_right
img.remove_layer(blackLayer)
# Hide the light noise layer, then collapse all the remaining
# layers (all letters) into a single layer.
light_noise_layer.visible = False
textLayer = gpdb.gimp_image_merge_visible_layers(img, CLIP_TO_IMAGE)
light_noise_layer.visible = True
# Create a layer of dark noise which will display the letters.
dark_noise_layer = gimp.Layer(img, 'dark noise', sx, sy,
RGB_IMAGE, 100, MULTIPLY_MODE)
img.add_layer(dark_noise_layer, 1)
gpdb.gimp_drawable_fill(dark_noise_layer, WHITE_FILL)
gpdb.plug_in_randomize_hurl(img, dark_noise_layer, 25, 1, 0, 0)
gpdb.gimp_desaturate(dark_noise_layer)
# These next operations are ordered carefully. Changing the order
# dramatically affects how the output looks.
# Here's where we do the cutout operation.
gpdb.gimp_selection_layer_alpha(textLayer)
gpdb.gimp_selection_invert(img)
gpdb.gimp_edit_clear(dark_noise_layer)
gpdb.gimp_selection_none(img)
# After the cutout, blur the dark noise layer and then darken it:
gpdb.plug_in_gauss_iir(img, dark_noise_layer, 1, 1, 1)
gpdb.gimp_levels(dark_noise_layer, HISTOGRAM_VALUE, 127, 255, 0.25, 0, 255)
textLayer.visible = False
# If you start gimp without --no-interface with an X server, this
# line will let you see the image looks like at this point in the
# script, layers and all. It should be fine to move this line to
# any problematic part of the script for debugging.
#
# gimp.Display(gpdb.gimp_image_duplicate(img))
final = img.flatten()
gpdb.gimp_image_clean_all(img)
img.enable_undo()
return img, final