kvfrans / deepcolor Goto Github PK

View Code? Open in Web Editor NEW

553.0 553.0 86.0 67.06 MB

Automatic coloring and shading of manga-style lineart, using Tensorflow + cGANs

Home Page: http://color.kvfrans.com

Python 64.95% HTML 18.55% JavaScript 15.83% CSS 0.66%

deepcolor's People

Contributors

Stargazers

Watchers

Forkers

stevenlol multipath benjamesbabala allensmile adrianhust wanjinchang burness chagge rillaha cllarence lif3line sheerun codeaudit skur42 kyriex jdc08161063 jhui imesw dezhili iqbal-chowdhury larthas shubhampachori12110095 knightofdawn fmela iamvon lsheiba medhini anwar63 naafx8 jordipala l3dlp-sandbox ivanling92 nagexiucai olivia-ymy msxie92 hccho2 dreamx3012 ocean1211 rockyzyl sandorlevi yiliu77 fqaiser94 zjgirl touchangels sandeep-singamsetty paulpanwang afcarl cangcui lancercomet bio5417 frankiegu fengben aweffr freeah chr2117216003 fastcode3d quantumiracle chenyuxu4n wranai reiisky graysonwu derekdjia drizzleraine hello432369 unmellow dlove1204 yunchangxiaoguan ai-hub-deep-learning-fundamental luciferaaa zaikopes nickfujita arthurg xg86 channinglua zhangnanxi shuchitabanthia xrosliang vishwajeet1 zlh547297421 wenlong66 e-e kowsertusher inthat-management-office vb6hobbyst7

deepcolor's Issues

Is any err in this code?

i clone the repo ,and download 10000imgs with the download_img.py. then i run python main.y train, and a week later with 3 million iterations i got my own model. when i type python main.y sample. the result looks like a noise picture,it can recognize nothing. i did't modify any your code, just want to try it. besize,the model that you pretrained also behaves as mess picture. emmmm, i'm so sad.

what function merge and merge_color mean ?

Can you explain for me what is the mean of function merge() and merge_color() ?

pre-trained model not available

The link to the pre-trained model is not available

Application fails w/ ubuntu 16.04

Command:

python main.py sample

Error:

python main.py sample
Traceback (most recent call last):
  File "main.py", line 238, in <module>
    c = Color(512,1)
  File "main.py", line 37, in __init__
    combined_preimage = tf.concat(3, [self.line_images, self.color_images])
  File "/home/mvillmow/.local/lib/python2.7/site-packages/tensorflow/python/ops/array_ops.py", line 1061, in concat
    dtype=dtypes.int32).get_shape(
  File "/home/mvillmow/.local/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 611, in convert_to_tensor
    as_ref=False)
  File "/home/mvillmow/.local/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 676, in internal_convert_to_tensor
    ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
  File "/home/mvillmow/.local/lib/python2.7/site-packages/tensorflow/python/framework/constant_op.py", line 121, in _constant_tensor_conversion_function
    return constant(v, dtype=dtype, name=name)
  File "/home/mvillmow/.local/lib/python2.7/site-packages/tensorflow/python/framework/constant_op.py", line 102, in constant
    tensor_util.make_tensor_proto(value, dtype=dtype, shape=shape, verify_shape=verify_shape))
  File "/home/mvillmow/.local/lib/python2.7/site-packages/tensorflow/python/framework/tensor_util.py", line 376, in make_tensor_proto
    _AssertCompatible(values, dtype)
  File "/home/mvillmow/.local/lib/python2.7/site-packages/tensorflow/python/framework/tensor_util.py", line 302, in _AssertCompatible
    (dtype.name, repr(mismatch), type(mismatch).__name__))
TypeError: Expected int32, got list containing Tensors of type '_Message' instead.

Repro steps:

git clone https://github.com/kvfrans/deepcolor.git
pip install --user tensorflow numpy
sudo apt-get install python-opencv
python main.py sample

ValueError: Dimension 1 in both shapes must be equal, but are 256 and 16. Shapes are [1,256,256] and [1,16,16]. for 'concat_1' (op: 'ConcatV2') with input shapes: [1,256,256,4], [1,16,16,3], [] and with computed input tensors: input[2] = <3>.

self.real_AB = tf.concat(axis=3, values=[combined_preimage, self.real_images])
self.fake_AB = tf.concat(axis=3, values=[combined_preimage, self.generated_images])

That is mistake,what should i do ?

error occured during downloading dataset

it scrapped around 80 pics then this error occured

File "download_images.py", line 25, in
image = np.asarray(bytearray(resp.read()), dtype="uint8")
File "C:\Python27\lib\socket.py", line 355, in read
data = self._sock.recv(rbufsize)
socket.error: [Errno 10054] An existing connection was forcibly closed by the remote host

Some questions about your code

Thank you for sharing!!

I found that you get color_image through bluring :
batch_colors = np.array([self.imageblur(ba,True) for ba in batch]) / 255.0

Bluring is a good way to get color prior when we have groundtruth images. But if I only have a line map (without groundtruth), bluring can not work because bluring a line image can not get any color informations. As your paper said, a color_predict network can predict the color from a line image. I think it is a very nice idea while I found main.py does not realize this part of functions. Maybe you have tried in guess_color.py.

Good job!!

An error with your code

Hi @kvfrans , when I run your code after upgrade to tensorflow 1.0, It get the following error:

python main_v1.py train
I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcublas.so.7.5 locally
I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcudnn.so.5 locally
I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcufft.so.7.5 locally
I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcuda.so.1 locally
I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcurand.so.7.5 locally
Traceback (most recent call last):
  File "main_v1.py", line 251, in <module>
    c = Color()
  File "main_v1.py", line 73, in __init__
    self.d_optim = tf.train.AdamOptimizer(0.0002, beta1=0.5).minimize(self.d_loss, var_list=self.d_vars)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/optimizer.py", line 289, in minimize
    name=name)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/optimizer.py", line 403, in apply_gradients
    self._create_slots(var_list)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/adam.py", line 117, in _create_slots
    self._zeros_slot(v, "m", self._name)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/optimizer.py", line 647, in _zeros_slot
    named_slots[var] = slot_creator.create_zeros_slot(var, op_name)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/slot_creator.py", line 123, in create_zeros_slot
    colocate_with_primary=colocate_with_primary)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/slot_creator.py", line 101, in create_slot
    return _create_slot_var(primary, val, '')
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/slot_creator.py", line 55, in _create_slot_var
    slot = variable_scope.get_variable(scope, initializer=val, trainable=False)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/variable_scope.py", line 988, in get_variable
    custom_getter=custom_getter)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/variable_scope.py", line 890, in get_variable
    custom_getter=custom_getter)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/variable_scope.py", line 348, in get_variable
    validate_shape=validate_shape)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/variable_scope.py", line 333, in _true_getter
    caching_device=caching_device, validate_shape=validate_shape)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/variable_scope.py", line 657, in _get_single_variable
    "VarScope?" % name)
ValueError: Variable d_h0_conv/w/Adam/ does not exist, or was not created with tf.get_variable(). Did you mean to set reuse=None in VarScope?

Could you help me with it ?

test in python3

my test cord this

def imageblur(img, sampling=False):
    if sampling:
        cimg = cimg * 0.3 + np.ones_like(cimg) * 0.7 * 255
    else:
        for i in range(30):
            randx = randint(0,205)
            randy = randint(0,205)
            cimg[randx:randx+50, randy:randy+50] = 255
    return cv2.blur(cimg,(100,100))

img = get_img(path)
img_b = imageblur(img)
nvc = np.concatenate((img,img_b),axis=1)
cv2.imshow("TEST",nvc)

and result ...

my test cord_2_add deep copy this

def imageblur(img, sampling=False):
    cimg = copy.deepcopy(img) #Add deep copy
    if sampling:
        cimg = cimg * 0.3 + np.ones_like(cimg) * 0.7 * 255
    else:
        for i in range(30):
            randx = randint(0,205)
            randy = randint(0,205)
            cimg[randx:randx+50, randy:randy+50] = 255
    return cv2.blur(cimg,(100,100))

img = get_img(path)
img_b = imageblur(img)
nvc = np.concatenate((img,img_b),axis=1)
cv2.imshow("TEST",nvc)

and result

And one more
why expand edge image dims in placeholder set dim 1
I am curious as to whether it should be expanded

            batch_edge = np.expand_dims(batch_edge, 3)

Thank you again for sharing. !!