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change scipy.misc.imresize() to PIL.Image.resize() #179

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change scipy.misc.imresize() to PIL.Image.resize() #179

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3fad478
Update train.py
guplersaxanoid Oct 1, 2019
c4b5188
Update train.py
guplersaxanoid Oct 1, 2019
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4 changes: 2 additions & 2 deletions train.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,11 +5,11 @@
import time
import random
import numpy as np
import scipy, multiprocessing
import tensorflow as tf
import tensorlayer as tl
from model import get_G, get_D
from config import config
from PIL import Image

###====================== HYPER-PARAMETERS ===========================###
## Adam
Expand Down Expand Up @@ -184,7 +184,7 @@ def evaluate():
tl.vis.save_image(valid_lr_img[0], os.path.join(save_dir, 'valid_lr.png'))
tl.vis.save_image(valid_hr_img, os.path.join(save_dir, 'valid_hr.png'))

out_bicu = scipy.misc.imresize(valid_lr_img[0], [size[0] * 4, size[1] * 4], interp='bicubic', mode=None)
out_bicu = np.array(Image.fromarray(valid_lr_img[0]).resize((size[0] * 4, size[1] * 4), resample=Image.BICUBIC))
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I ran into the following error after applying this change.

Traceback (most recent call last):`
   File "C:\Users\chuzh\venv\lib\site-packages\PIL\Image.py", line 2645, in fromarray
     mode, rawmode = _fromarray_typemap[typekey]
KeyError: ((1, 1, 3), '<f4')

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File ".\train.py", line 210, in
    evaluate()
  File ".\train.py", line 192, in evaluate
    out_bicu = np.array(Image.fromarray(valid_lr_img[0]).resize((size[0] * 4, size[1] * 4), resample=Image.BICUBIC))
  File "C:\Users\chuzh\venv\lib\site-packages\PIL\Image.py", line 2647, in fromarray
    raise TypeError("Cannot handle this data type")
TypeError: Cannot handle this data type

Once I changed this line
out_bicu = np.array(Image.fromarray(valid_lr_img[0]).resize((size[0] * 4, size[1] * 4), resample=Image.BICUBIC))
to
out_bicu = np.array(Image.fromarray(((valid_lr_img[0] + 1)*127.5).astype(np.uint8)).resize((size[1] * 4, size[0] * 4), resample=Image.BICUBIC))
everything works correctly.

This is due to the fact that Image.fromarray( ) function only takes in numpy array whose elements are uint8 data type.

tl.vis.save_image(out_bicu, os.path.join(save_dir, 'valid_bicubic.png'))


Expand Down