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import numpy as np
import neuralStyle


    

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from io import BytesIO
from PIL import Image as PIL_Image
import numpy as np
from IPython.display import display, Image

def display_img_array(ima, **kwargs):
    if ima.dtype == np.float32 or ima.dtype == np.float64:
        ima = (np.clip(ima, 0., 1.)*255).astype(np.uint8)
    im = PIL_Image.fromarray(ima[:,:,::-1])
    bio = BytesIO()
    im.save(bio, format='png')
    display(Image(bio.getvalue(), format='png', **kwargs))


    

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neuralStyle.precompute()


    

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from glob import glob


    

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photo_content_filename = "content/golden_gate.jpg"
for art_style_filename in glob("styles/*"):
    display_img_array(neuralStyle.imread(art_style_filename), width=640)
    for img in neuralStyle.p_transfer(photo_content_filename, art_style_filename):        
        display_img_array(img)


    

    




 3.7819809913635254
iter=0 loss=5321.783277 7.762786626815796






    













    




iter=1 loss=2249.734753 11.686580419540405






    













    




start transfer (640) 11.73551893234253
photo prepared 11.785621881484985
art prepared 11.8466956615448
precomputed layers 12.402926921844482
gen_features 12.436548233032227
define total_loss 12.53891634941101
iter=0 loss=11892.436927 16.633955478668213






    













    













    




start transfer (160) 1.4543533325195312e-05
photo prepared 0.024128198623657227
art prepared 0.039315223693847656
precomputed layers 0.08784675598144531
gen_features 0.08824920654296875
define total_loss 0.1906881332397461
iter=0 loss=1566.839950 1.8715076446533203






    













    




iter=1 loss=996.104410 3.3748979568481445






    













    




start transfer (400) 3.381082057952881
photo prepared 3.411853075027466
art prepared 3.4366507530212402
precomputed layers 3.657548666000366
gen_features 3.6701436042785645
define total_loss

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photo_content_filename = "content/ndhu.jpg"
for art_style_filename in glob("styles/*"):
    display_img_array(neuralStyle.imread(art_style_filename), width=640)
    for img in neuralStyle.p_transfer(photo_content_filename, art_style_filename):        
        display_img_array(img)


    

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photo_content_filename = "content/brad_pitt.jpg"
for art_style_filename in glob("styles/*"):
    display_img_array(neuralStyle.imread(art_style_filename), width=640)
    for img in neuralStyle.p_transfer(photo_content_filename, art_style_filename):        
        display_img_array(img)


    

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photo_content_filename = "styles/golden_gate.jpg"
for art_style_filename in ["starry_night.jpg", "the_scream.jpg", "shipwreck.jpg", "picasso_selfport1907.jpg"]:
    art_style_filename = "styles/"+ art_style_filename
    for img in neuralStyle.p_transfer(photo_content_filename, art_style_filename):
        display_img_array(img)


    

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photo_content_filename = "styles/brad_pitt.jpg"
for art_style_filename in ["starry_night.jpg", "the_scream.jpg", "shipwreck.jpg", "picasso_selfport1907.jpg"]:
    art_style_filename = "styles/"+ art_style_filename
    for img in neuralStyle.p_transfer(photo_content_filename, art_style_filename):
        display_img_array(img)


    

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photo_content_filename = "/home/tjw/圖片/baian_winter/4.jpeg"
for art_style_filename in ["starry_night.jpg", "the_scream.jpg", "shipwreck.jpg", "picasso_selfport1907.jpg"]:
    art_style_filename = "styles/"+ art_style_filename
    for img in neuralStyle.p_transfer(photo_content_filename, art_style_filename):
        display_img_array(img)


    

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photo_content_filename="styles/640px-Fractal_Heart2_5600x4200.jpg"
art_style_filename = "styles/JellyBellyBeans.jpg"
for img in neuralStyle.p_transfer(photo_content_filename, art_style_filename):
        display_img_array(img)


    

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