During handling of the above exception, another exception occurred

[Nakasu-ksm]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "train.py", line 6, in
import tensorflow as tf
File "C:\Users\admin\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow_init_.py", line 24, in
from tensorflow.python import pywrap_tensorflow # pylint: disable=unused-import
File "C:\Users\admin\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow\python_init_.py", line 49, in
from tensorflow.python import pywrap_tensorflow
File "C:\Users\admin\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 74, in
raise ImportError(msg)
ImportError: Traceback (most recent call last):
File "C:\Users\admin\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 58, in
from tensorflow.python.pywrap_tensorflow_internal import *
File "C:\Users\admin\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow\python\pywrap_tensorflow_internal.py", line 28, in
_pywrap_tensorflow_internal = swig_import_helper()
File "C:\Users\admin\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow\python\pywrap_tensorflow_internal.py", line 24, in swig_import_helper
_mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)
File "C:\Users\admin\AppData\Local\Programs\Python\Python37\lib\imp.py", line 242, in load_module
return load_dynamic(name, filename, file)
File "C:\Users\admin\AppData\Local\Programs\Python\Python37\lib\imp.py", line 342, in load_dynamic
return _load(spec)
ImportError: DLL load failed: 找不到指定的模块。

Failed to load the native TensorFlow runtime.

See https://www.tensorflow.org/install/errors

for some common reasons and solutions. Include the entire stack trace
above this error message when asking for help.

[Nakasu-ksm]

@JiahuiYu

[JiahuiYu]

I have no idea how to execute on Windows. Apparently it relates to the python environment: python and tensorflow.

[Nakasu-ksm]

what can i do

[Nakasu-ksm]

cuda or cudnn

[Nakasu-ksm]

i use the gpu vesion

[JiahuiYu]

I would suggest you search how to execute tensorflow on Windows with GPU.

[Nakasu-ksm]

thanks i solve this question but train.py Get stuck �[32m[2019-05-22 23:29:51 @weights_viewer.py:60]�[0m Total size of trainable weights: 0G 10M 184K 136B (Assuming32-bit data type.)

[Nakasu-ksm]

Traceback (most recent call last):
File "test.py", line 23, in
ng.get_gpus(1)
File "C:\Users\admin\AppData\Local\Programs\Python\Python37\lib\site-packages\neuralgym\utils\gpus.py", line 54, in get_gpus
gpu_id = int(s[0])
IndexError: list index out of range

the test.py how can i modify it

import argparse

import cv2
import numpy as np
import tensorflow as tf
import neuralgym as ng

from inpaint_model import InpaintCAModel

parser = argparse.ArgumentParser()
parser.add_argument('--image', default='', type=str,
help='The filename of image to be completed.')
parser.add_argument('--mask', default='', type=str,
help='The filename of mask, value 255 indicates mask.')
parser.add_argument('--output', default='output.png', type=str,
help='Where to write output.')
parser.add_argument('--checkpoint_dir', default='', type=str,
help='The directory of tensorflow checkpoint.')

if name == "main":
ng.get_gpus(1)
args = parser.parse_args()

model = InpaintCAModel()
image = cv2.imread(args.image)
mask = cv2.imread(args.mask)

assert image.shape == mask.shape

h, w, _ = image.shape
grid = 8
image = image[:h//grid*grid, :w//grid*grid, :]
mask = mask[:h//grid*grid, :w//grid*grid, :]
print('Shape of image: {}'.format(image.shape))

image = np.expand_dims(image, 0)
mask = np.expand_dims(mask, 0)
input_image = np.concatenate([image, mask], axis=2)

sess_config = tf.ConfigProto()
sess_config.gpu_options.allow_growth = True
with tf.Session(config=sess_config) as sess:
    input_image = tf.constant(input_image, dtype=tf.float32)
    output = model.build_server_graph(input_image)
    output = (output + 1.) * 127.5
    output = tf.reverse(output, [-1])
    output = tf.saturate_cast(output, tf.uint8)
    # load pretrained model
    vars_list = tf.get_collection(tf.GraphKeys.GLOBAL_VARIABLES)
    assign_ops = []
    for var in vars_list:
        vname = var.name
        from_name = vname
        var_value = tf.contrib.framework.load_variable(args.checkpoint_dir, from_name)
        assign_ops.append(tf.assign(var, var_value))
    sess.run(assign_ops)
    print('Model loaded.')
    result = sess.run(output)
    cv2.imwrite(args.output, result[0][:, :, ::-1])

[JiahuiYu]

Remove the line of ng.get_gpus(1)

[Nakasu-ksm]

Traceback (most recent call last):
File "test.py", line 29, in
assert image.shape == mask.shape
AttributeError: 'NoneType' object has no attribute 'shape'

[Nakasu-ksm]

I don't know why Windows has so many problems

[JiahuiYu]

These are very basic errors and I believe you can solve by yourself.

[Nakasu-ksm]

But I have no idea to solve this

[Nakasu-ksm]

I will try to solve

[Nakasu-ksm]

import argparse

import cv2
import numpy as np
import tensorflow as tf
import neuralgym as ng

from inpaint_model import InpaintCAModel

parser = argparse.ArgumentParser()
parser.add_argument('--image', default='', type=str,
help='The filename of image to be completed.')
parser.add_argument('--mask', default='', type=str,
help='The filename of mask, value 255 indicates mask.')
parser.add_argument('--output', default='output.png', type=str,
help='Where to write output.')
parser.add_argument('--checkpoint_dir', default='', type=str,
help='The directory of tensorflow checkpoint.')

if name == "main":

args = parser.parse_args()

model = InpaintCAModel()
image = cv2.imread(args.image)
mask = cv2.imread("C:\Users\admin\Desktop\generative_inpainting-master\examples\mask.png")

assert image.shape == mask.shape

h, w, _ = image.shape
grid = 8
image = image[:h//grid*grid, :w//grid*grid, :]
mask = mask[:h//grid*grid, :w//grid*grid, :]
print('Shape of image: {}'.format(image.shape))

image = np.expand_dims(image, 0)
mask = np.expand_dims(mask, 0)
input_image = np.concatenate([image, mask], axis=2)

sess_config = tf.ConfigProto()
sess_config.gpu_options.allow_growth = True
with tf.Session(config=sess_config) as sess:
    input_image = tf.constant(input_image, dtype=tf.float32)
    output = model.build_server_graph(input_image)
    output = (output + 1.) * 127.5
    output = tf.reverse(output, [-1])
    output = tf.saturate_cast(output, tf.uint8)
    # load pretrained model
    vars_list = tf.get_collection(tf.GraphKeys.GLOBAL_VARIABLES)
    assign_ops = []
    for var in vars_list:
        vname = var.name
        from_name = vname
        var_value = tf.contrib.framework.load_variable(args.checkpoint_dir, from_name)
        assign_ops.append(tf.assign(var, var_value))
    sess.run(assign_ops)
    print('Model loaded.')
    result = sess.run(output)
    cv2.imwrite(args.output, result[0][:, :, ::-1])

[Nakasu-ksm]

but run error

[Nakasu-ksm]

can you help me

[Nakasu-ksm]

@JiahuiYu