def main():
img_path = "lena.png"
dataset_path = "/home/martin/datasets/flickr/thumbnails"
dataset_csv = "dataset.csv"
block_size = 64
dataset = Dataset(dataset_path)
#dataset.create()
file_paths, rgb_means = dataset.load(dataset_csv)
collage = Collage(img_path, file_paths, rgb_means, block_size)
img_collage = collage.create()
io.imsave("collage.png", img_collage)
def flag_3(): if resp_1=="si" or resp_2=="si": return else: Collage.collage(nom,tam,RAM) return
def flag_2(): if resp_1=="No" or resp_1=="NO" or resp_1=="no": return else: Collage.collage_sec() return
import Image import Collage import Particiones Collage.hola() datos=[0,0,0,0,0,0,0,0] def flag_1(): if resp_2=="No" or resp_2=="NO" or resp_2=="no": return else: Particiones.imag_part(dim_part,nom) return def flag_2(): if resp_1=="No" or resp_1=="NO" or resp_1=="no": return else: Collage.collage_sec() return def flag_3(): if resp_1=="si" or resp_2=="si": return else: Collage.collage(nom,tam,RAM) return
def flag_3():
if resp_1 == "si" or resp_2 == "si":
return
else:
Collage.collage(nom, tam, RAM)
return
def flag_2():
if resp_1 == "No" or resp_1 == "NO" or resp_1 == "no":
return
else:
Collage.collage_sec()
return
import Image
import Collage
import Particiones
Collage.hola()
datos = [0, 0, 0, 0, 0, 0, 0, 0]
def flag_1():
if resp_2 == "No" or resp_2 == "NO" or resp_2 == "no":
return
else:
Particiones.imag_part(dim_part, nom)
return
def flag_2():
if resp_1 == "No" or resp_1 == "NO" or resp_1 == "no":
return
else:
Collage.collage_sec()
return
def flag_3():
if resp_1 == "si" or resp_2 == "si":
return
else:
