Mercurial > ift6266
view data_generation/transformations/gimp_script.py @ 239:42005ec87747
Mergé (manuellement) les changements de Sylvain pour utiliser le code de dataset d'Arnaud, à cette différence près que je n'utilse pas les givens. J'ai probablement une approche différente pour limiter la taille du dataset dans mon débuggage, aussi.
author | fsavard |
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date | Mon, 15 Mar 2010 18:30:21 -0400 |
parents | 1f5937e9e530 |
children | 39421555993f |
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#!/usr/bin/env python # coding: utf-8 ''' Filtres GIMP sous Python Auteur: Nicolas Boulanger-Lewandowski Date: Hiver 2010 run with: gimp -i --batch-interpreter python-fu-eval --batch - < gimp_script.py end with: pdb.gimp_quit(0) Implémente le motionblur et le pinch ''' from gimpfu import * import numpy img = gimp.Image(32, 32, GRAY) img.disable_undo() layer1 = gimp.Layer(img, "layer1", 32, 32, GRAY_IMAGE, 100, NORMAL_MODE) img.add_layer(layer1, 0) dest_rgn = layer1.get_pixel_rgn(0, 0, 32, 32, True) def setpix(image): dest_rgn[:,:] = (image.T*255).astype(numpy.uint8).tostring() layer1.flush() layer1.update(0, 0, 32, 32) def getpix(): return numpy.fromstring(dest_rgn[:,:], 'UInt8').astype(numpy.float32).reshape((32,32)).T / 255.0 class GIMP1(): def get_settings_names(self): return ['mblur_length', 'mblur_angle', 'pinch'] def regenerate_parameters(self, complexity): if complexity: self.mblur_length = abs(int(round(numpy.random.normal(0, 3*complexity)))) else: self.mblur_length = 0 self.mblur_angle = int(round(numpy.random.uniform(0,360))) self.pinch = numpy.random.uniform(-complexity, 0.7*complexity) return [self.mblur_length, self.mblur_angle, self.pinch] def transform_image(self, image): if self.mblur_length or self.pinch: setpix(image) if self.mblur_length: pdb.plug_in_mblur(img, layer1, 0, self.mblur_length, self.mblur_angle, 0, 0) if self.pinch: pdb.plug_in_whirl_pinch(img, layer1, 0.0, self.pinch, 1.0) image = getpix() return image # test if __name__ == '__main__': import Image im = numpy.asarray(Image.open("a.bmp").convert("L")) / 255.0 test = GIMP1() print test.get_settings_names(), '=', test.regenerate_parameters(1) #for i in range(1000): im = test.transform_image(im) import pylab pylab.imshow(im, pylab.matplotlib.cm.Greys_r) pylab.show() pdb.gimp_quit(0)