First off I should mention that I've read this question already:
StopIteration: generator_output = next(output_generator)
But my issue is somewhat different so I don't think this is a duplicate (although the titles are the same!).
I'm running a relatively simple cnn to try and classify images into either [contains head] or [doesn't contain head], I call them [head] and [not] for short.
The issue I'm having is that I don't def my generator the way the other question does (see code below), so I'm not sure how to make my generator able to generate 'infinite' data.
Code:
# Importing the Keras libraries and packages
from keras.models import Sequential
from keras.layers import Conv2D
from keras.layers import MaxPooling2D
from keras.layers import Flatten
from keras.layers import Dense
# Initialising the CNN
classifier = Sequential()
# Step 1 - Convolution
classifier.add(Conv2D(32, (3, 3), input_shape = (40, 40, 3), activation = 'relu'))
# Step 2 - Pooling
classifier.add(MaxPooling2D(pool_size = (2, 2)))
# Adding a second convolutional layer
classifier.add(Conv2D(32, (3, 3), activation = 'relu'))
classifier.add(MaxPooling2D(pool_size = (2, 2)))
# Step 3 - Flattening
classifier.add(Flatten())
# Step 4 - Full connection
classifier.add(Dense(units = 128, activation = 'relu'))
classifier.add(Dense(units = 1, activation = 'sigmoid'))
# Compiling the CNN
classifier.compile(optimizer = 'adam', loss = 'binary_crossentropy', metrics = ['accuracy'])
# Part 2 - Fitting the CNN to the images
from keras.preprocessing.image import ImageDataGenerator
train_datagen = ImageDataGenerator(rescale = 1./255)
test_datagen = ImageDataGenerator(rescale = 1./255)
training_set = train_datagen.flow_from_directory('dataset/training_set',
target_size = (40, 40),
batch_size = 32,
class_mode = 'binary')
test_set = test_datagen.flow_from_directory('dataset/test_set',
target_size = (40, 40),
batch_size = 64,
class_mode = 'binary')
classifier.fit_generator(training_set,
steps_per_epoch = 4000,
epochs = 25,
validation_data = test_set,
validation_steps = 400)
classifier.save("CSGOHeads.h5")
# Part 3 - Making new predictions
import numpy as np
from keras.preprocessing import image
test_image = image.load_img('dataset/single_prediction/1.bmp', target_size = (40, 40))
test_image = image.img_to_array(test_image)
test_image = np.expand_dims(test_image, axis = 0)
result = classifier.predict(test_image)
training_set.class_indices
if result[0][0] == 1:
prediction = 'head'
else:
prediction = 'not'
For completeness here's the entire dump from the cmd:
C:\Anaconda36\envs\tensorflow\lib\site-packages\h5py\__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
from ._conv import register_converters as _register_converters
Using TensorFlow backend.
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\dso_loader.cc:135] successfully opened CUDA library cublas64_80.dll locally
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\dso_loader.cc:135] successfully opened CUDA library cudnn64_5.dll locally
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\dso_loader.cc:135] successfully opened CUDA library cufft64_80.dll locally
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\dso_loader.cc:135] successfully opened CUDA library nvcuda.dll locally
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\dso_loader.cc:135] successfully opened CUDA library curand64_80.dll locally
E c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\framework\op_kernel.cc:943] OpKernel ('op: "BestSplits" device_type: "CPU"') for unknown op: BestSplits
E c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\framework\op_kernel.cc:943] OpKernel ('op: "CountExtremelyRandomStats" device_type: "CPU"') for unknown op: CountExtremelyRandomStats
E c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\framework\op_kernel.cc:943] OpKernel ('op: "FinishedNodes" device_type: "CPU"') for unknown op: FinishedNodes
E c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\framework\op_kernel.cc:943] OpKernel ('op: "GrowTree" device_type: "CPU"') for unknown op: GrowTree
E c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\framework\op_kernel.cc:943] OpKernel ('op: "ReinterpretStringToFloat" device_type: "CPU"') for unknown op: ReinterpretStringToFloat
E c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\framework\op_kernel.cc:943] OpKernel ('op: "SampleInputs" device_type: "CPU"') for unknown op: SampleInputs
E c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\framework\op_kernel.cc:943] OpKernel ('op: "ScatterAddNdim" device_type: "CPU"') for unknown op: ScatterAddNdim
E c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\framework\op_kernel.cc:943] OpKernel ('op: "TopNInsert" device_type: "CPU"') for unknown op: TopNInsert
E c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\framework\op_kernel.cc:943] OpKernel ('op: "TopNRemove" device_type: "CPU"') for unknown op: TopNRemove
E c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\framework\op_kernel.cc:943] OpKernel ('op: "TreePredictions" device_type: "CPU"') for unknown op: TreePredictions
E c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\framework\op_kernel.cc:943] OpKernel ('op: "UpdateFertileSlots" device_type: "CPU"') for unknown op: UpdateFertileSlots
Found 177986 images belonging to 2 classes.
Found 19857 images belonging to 2 classes.
Epoch 1/25
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\gpu\gpu_device.cc:885] Found device 0 with properties:
name: GeForce GTX 1080 Ti
major: 6 minor: 1 memoryClockRate (GHz) 1.582
pciBusID 0000:23:00.0
Total memory: 11.00GiB
Free memory: 9.10GiB
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\gpu\gpu_device.cc:906] DMA: 0
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\gpu\gpu_device.cc:916] 0: Y
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\gpu\gpu_device.cc:975] Creating TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GTX 1080 Ti, pci bus id: 0000:23:00.0)
4000/4000 [==============================] - 109s - loss: 0.0039 - acc: 0.9987 - val_loss: 1.4612e-04 - val_acc: 1.0000
Epoch 2/25
829/4000 [=====>........................] - ETA: 68s - loss: 4.8378e-06 - acc: 1.0000Exception in thread Thread-39:
Traceback (most recent call last):
File "C:\Anaconda36\envs\tensorflow\lib\threading.py", line 914, in _bootstrap_inner
File "C:\Anaconda36\envs\tensorflow\lib\threading.py", line 862, in run
File "C:\Anaconda36\envs\tensorflow\lib\site-packages\keras\utils\data_utils.py", line 568, in data_generator_task
File "C:\Anaconda36\envs\tensorflow\lib\site-packages\keras\preprocessing\image.py", line 737, in __next__
return self.next(*args, **kwargs)
File "C:\Anaconda36\envs\tensorflow\lib\site-packages\keras\preprocessing\image.py", line 1033, in next
target_size=self.target_size)
File "C:\Anaconda36\envs\tensorflow\lib\site-packages\keras\preprocessing\image.py", line 322, in load_img
img = pil_image.open(path)
File "C:\Anaconda36\envs\tensorflow\lib\site-packages\PIL\Image.py", line 2539, in open
prefix = fp.read(16)
OSError: [Errno 22] Invalid argument
Traceback (most recent call last):
File "kerasmod.py", line 47, in <module>
validation_steps = 400)
File "C:\Anaconda36\envs\tensorflow\lib\site-packages\keras\legacy\interfaces.py", line 87, in wrapper
return func(*args, **kwargs)
File "C:\Anaconda36\envs\tensorflow\lib\site-packages\keras\models.py", line 1121, in fit_generator
initial_epoch=initial_epoch)
File "C:\Anaconda36\envs\tensorflow\lib\site-packages\keras\legacy\interfaces.py", line 87, in wrapper
return func(*args, **kwargs)
File "C:\Anaconda36\envs\tensorflow\lib\site-packages\keras\engine\training.py", line 2011, in fit_generator
generator_output = next(output_generator)
StopIteration
