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llSourcell / Pokemon_GAN

This is the code for "Generating Pokemon with a Generative Adversarial Network" by Siraj Raval on Youtube
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Confusion in the README #4

Open dvisockas opened 6 years ago

dvisockas commented 6 years ago

Readme says that before running pokeGAN.py one should run resize.py and RGBA2RGB.py. There are few problems here and I'll work backwards from pokeGAN.py to explain them. In pokeGAN.py the height and width of the images are hardcoded to be 128 and 128. However in resize.py resized images height and width are 256. This is the first wtf. Second wtf is that pokeGAN.py reads the data from 'data' directory (line 29), but resize.py puts data in a directory named 'resizedData'. Third thing is that RGBA2RGB.py takes this a step further and puts files from resizedData to resized_black (which is bad naming, but let it be).

To conclude, either the pokeGAN.py reads images from wrong directories or helper scripts put processed images into wrong directories. I understand that this is not your code, but let's fix this if people of YouTube will try to use it :wink:

ErikJungnickel commented 6 years ago

Also, the main pokeGAN.py is resizing the images as well (to 128x128). So the resize and rgb scripts are not really needed I guess.

miranthajayatilake commented 6 years ago

I found this confusing as well! And also I found that the provided images of the data folder are also of two shapes. Some are 1280x1280 and some are 431x431. No clue why this is and if it affects the code.

denniswittich commented 6 years ago

The input images will be scaled using tensorflow functions. Size of input doesn't matter. I guess in the first version they were scaled in pre-proccessing. And of course the input pipeline is faster, if the images don't need to be scaled.

PaawanS commented 6 years ago

I am getting following error while executing pokeGAN.py (log below). Any clues?

runfile('D:/Pokemon_GAN-master/pokeGAN.py', wdir='D:/Pokemon_GAN-master')
15
importing data...
INFO:tensorflow:Restoring parameters from ./model.ckpt
total training sample num:100
batch size: 64, batch num per epoch: 1, epoch num: 5000
start training...
0
0
0
INFO:tensorflow:Error reported to Coordinator: <class 'tensorflow.python.framework.errors_impl.InvalidArgumentError'>, Invalid JPEG data, size 990821
         [[Node: DecodeJpeg = DecodeJpeg[acceptable_fraction=1, channels=3, dct_method="", fancy_upscaling=true, ratio=1, try_recover_truncated=false, _device="/job:localhost/replica:0/task:0/cpu:0"](ReadFile)]]

Caused by op 'DecodeJpeg', defined at:
  File "C:\Anaconda3\lib\site-packages\spyder\utils\ipython\start_kernel.py", line 245, in <module>
    main()
  File "C:\Anaconda3\lib\site-packages\spyder\utils\ipython\start_kernel.py", line 241, in main
    kernel.start()
  File "C:\Anaconda3\lib\site-packages\ipykernel\kernelapp.py", line 477, in start
    ioloop.IOLoop.instance().start()
  File "C:\Anaconda3\lib\site-packages\zmq\eventloop\ioloop.py", line 177, in start
    super(ZMQIOLoop, self).start()
  File "C:\Anaconda3\lib\site-packages\tornado\ioloop.py", line 888, in start
    handler_func(fd_obj, events)
  File "C:\Anaconda3\lib\site-packages\tornado\stack_context.py", line 277, in null_wrapper
    return fn(*args, **kwargs)
  File "C:\Anaconda3\lib\site-packages\zmq\eventloop\zmqstream.py", line 440, in _handle_events
    self._handle_recv()
  File "C:\Anaconda3\lib\site-packages\zmq\eventloop\zmqstream.py", line 472, in _handle_recv
    self._run_callback(callback, msg)
  File "C:\Anaconda3\lib\site-packages\zmq\eventloop\zmqstream.py", line 414, in _run_callback
    callback(*args, **kwargs)
  File "C:\Anaconda3\lib\site-packages\tornado\stack_context.py", line 277, in null_wrapper
    return fn(*args, **kwargs)
  File "C:\Anaconda3\lib\site-packages\ipykernel\kernelbase.py", line 283, in dispatcher
    return self.dispatch_shell(stream, msg)
  File "C:\Anaconda3\lib\site-packages\ipykernel\kernelbase.py", line 235, in dispatch_shell
    handler(stream, idents, msg)
  File "C:\Anaconda3\lib\site-packages\ipykernel\kernelbase.py", line 399, in execute_request
    user_expressions, allow_stdin)
  File "C:\Anaconda3\lib\site-packages\ipykernel\ipkernel.py", line 196, in do_execute
    res = shell.run_cell(code, store_history=store_history, silent=silent)
  File "C:\Anaconda3\lib\site-packages\ipykernel\zmqshell.py", line 533, in run_cell
    return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
  File "C:\Anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 2698, in run_cell
    interactivity=interactivity, compiler=compiler, result=result)
  File "C:\Anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 2808, in run_ast_nodes
    if self.run_code(code, result):
  File "C:\Anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 2862, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-1-de721db22f36>", line 1, in <module>
    runfile('D:/Pokemon_GAN-master/pokeGAN.py', wdir='D:/Pokemon_GAN-master')
  File "C:\Anaconda3\lib\site-packages\spyder\utils\site\sitecustomize.py", line 710, in runfile
    execfile(filename, namespace)
  File "C:\Anaconda3\lib\site-packages\spyder\utils\site\sitecustomize.py", line 101, in execfile
    exec(compile(f.read(), filename, 'exec'), namespace)
  File "D:/Pokemon_GAN-master/pokeGAN.py", line 300, in <module>
    train()
  File "D:/Pokemon_GAN-master/pokeGAN.py", line 215, in train
    image_batch, samples_num = process_data()
  File "D:/Pokemon_GAN-master/pokeGAN.py", line 45, in process_data
    image = tf.image.decode_jpeg(content, channels = CHANNEL)
  File "C:\Anaconda3\lib\site-packages\tensorflow\python\ops\gen_image_ops.py", line 345, in decode_jpeg
    dct_method=dct_method, name=name)
  File "C:\Anaconda3\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 768, in apply_op
    op_def=op_def)
  File "C:\Anaconda3\lib\site-packages\tensorflow\python\framework\ops.py", line 2336, in create_op
    original_op=self._default_original_op, op_def=op_def)
  File "C:\Anaconda3\lib\site-packages\tensorflow\python\framework\ops.py", line 1228, in __init__
    self._traceback = _extract_stack()

InvalidArgumentError (see above for traceback): Invalid JPEG data, size 990821
         [[Node: DecodeJpeg = DecodeJpeg[acceptable_fraction=1, channels=3, dct_method="", fancy_upscaling=true, ratio=1, try_recover_truncated=false, _device="/job:localhost/replica:0/task:0/cpu:0"](ReadFile)]]

Traceback (most recent call last):

  File "<ipython-input-1-de721db22f36>", line 1, in <module>
    runfile('D:/Pokemon_GAN-master/pokeGAN.py', wdir='D:/Pokemon_GAN-master')

  File "C:\Anaconda3\lib\site-packages\spyder\utils\site\sitecustomize.py", line 710, in runfile
    execfile(filename, namespace)

  File "C:\Anaconda3\lib\site-packages\spyder\utils\site\sitecustomize.py", line 101, in execfile
    exec(compile(f.read(), filename, 'exec'), namespace)

  File "D:/Pokemon_GAN-master/pokeGAN.py", line 300, in <module>
    train()

  File "D:/Pokemon_GAN-master/pokeGAN.py", line 243, in train
    train_image = sess.run(image_batch)

  File "C:\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 778, in run
    run_metadata_ptr)

  File "C:\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 982, in _run
    feed_dict_string, options, run_metadata)

  File "C:\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 1032, in _do_run
    target_list, options, run_metadata)

  File "C:\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 1052, in _do_call
    raise type(e)(node_def, op, message)

OutOfRangeError: RandomShuffleQueue '_1_shuffle_batch/random_shuffle_queue' is closed and has insufficient elements (requested 64, current size 0)
     [[Node: shuffle_batch = QueueDequeueManyV2[component_types=[DT_FLOAT], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/cpu:0"](shuffle_batch/random_shuffle_queue, shuffle_batch/n)]]

Caused by op 'shuffle_batch', defined at:
  File "C:\Anaconda3\lib\site-packages\spyder\utils\ipython\start_kernel.py", line 245, in <module>
    main()
  File "C:\Anaconda3\lib\site-packages\spyder\utils\ipython\start_kernel.py", line 241, in main
    kernel.start()
  File "C:\Anaconda3\lib\site-packages\ipykernel\kernelapp.py", line 477, in start
    ioloop.IOLoop.instance().start()
  File "C:\Anaconda3\lib\site-packages\zmq\eventloop\ioloop.py", line 177, in start
    super(ZMQIOLoop, self).start()
  File "C:\Anaconda3\lib\site-packages\tornado\ioloop.py", line 888, in start
    handler_func(fd_obj, events)
  File "C:\Anaconda3\lib\site-packages\tornado\stack_context.py", line 277, in null_wrapper
    return fn(*args, **kwargs)
  File "C:\Anaconda3\lib\site-packages\zmq\eventloop\zmqstream.py", line 440, in _handle_events
    self._handle_recv()
  File "C:\Anaconda3\lib\site-packages\zmq\eventloop\zmqstream.py", line 472, in _handle_recv
    self._run_callback(callback, msg)
  File "C:\Anaconda3\lib\site-packages\zmq\eventloop\zmqstream.py", line 414, in _run_callback
    callback(*args, **kwargs)
  File "C:\Anaconda3\lib\site-packages\tornado\stack_context.py", line 277, in null_wrapper
    return fn(*args, **kwargs)
  File "C:\Anaconda3\lib\site-packages\ipykernel\kernelbase.py", line 283, in dispatcher
    return self.dispatch_shell(stream, msg)
  File "C:\Anaconda3\lib\site-packages\ipykernel\kernelbase.py", line 235, in dispatch_shell
    handler(stream, idents, msg)
  File "C:\Anaconda3\lib\site-packages\ipykernel\kernelbase.py", line 399, in execute_request
    user_expressions, allow_stdin)
  File "C:\Anaconda3\lib\site-packages\ipykernel\ipkernel.py", line 196, in do_execute
    res = shell.run_cell(code, store_history=store_history, silent=silent)
  File "C:\Anaconda3\lib\site-packages\ipykernel\zmqshell.py", line 533, in run_cell
    return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
  File "C:\Anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 2698, in run_cell
    interactivity=interactivity, compiler=compiler, result=result)
  File "C:\Anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 2808, in run_ast_nodes
    if self.run_code(code, result):
  File "C:\Anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 2862, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-1-de721db22f36>", line 1, in <module>
    runfile('D:/Pokemon_GAN-master/pokeGAN.py', wdir='D:/Pokemon_GAN-master')
  File "C:\Anaconda3\lib\site-packages\spyder\utils\site\sitecustomize.py", line 710, in runfile
    execfile(filename, namespace)
  File "C:\Anaconda3\lib\site-packages\spyder\utils\site\sitecustomize.py", line 101, in execfile
    exec(compile(f.read(), filename, 'exec'), namespace)
  File "D:/Pokemon_GAN-master/pokeGAN.py", line 300, in <module>
    train()
  File "D:/Pokemon_GAN-master/pokeGAN.py", line 215, in train
    image_batch, samples_num = process_data()
  File "D:/Pokemon_GAN-master/pokeGAN.py", line 66, in process_data
    min_after_dequeue = 200)
  File "C:\Anaconda3\lib\site-packages\tensorflow\python\training\input.py", line 1214, in shuffle_batch
    name=name)
  File "C:\Anaconda3\lib\site-packages\tensorflow\python\training\input.py", line 784, in _shuffle_batch
    dequeued = queue.dequeue_many(batch_size, name=name)
  File "C:\Anaconda3\lib\site-packages\tensorflow\python\ops\data_flow_ops.py", line 458, in dequeue_many
    self._queue_ref, n=n, component_types=self._dtypes, name=name)
  File "C:\Anaconda3\lib\site-packages\tensorflow\python\ops\gen_data_flow_ops.py", line 1328, in _queue_dequeue_many_v2
    timeout_ms=timeout_ms, name=name)
  File "C:\Anaconda3\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 768, in apply_op
    op_def=op_def)
  File "C:\Anaconda3\lib\site-packages\tensorflow\python\framework\ops.py", line 2336, in create_op
    original_op=self._default_original_op, op_def=op_def)
  File "C:\Anaconda3\lib\site-packages\tensorflow\python\framework\ops.py", line 1228, in __init__
    self._traceback = _extract_stack()

OutOfRangeError (see above for traceback): RandomShuffleQueue '_1_shuffle_batch/random_shuffle_queue' is closed and has insufficient elements (requested 64, current size 0)
     [[Node: shuffle_batch = QueueDequeueManyV2[component_types=[DT_FLOAT], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/cpu:0"](shuffle_batch/random_shuffle_queue, shuffle_batch/n)]]