Keras: TypeError: float() argument must be a string or a number, not 'JpegImageFile' when using Model.evaluate_generator()

[andrehsu]

from keras.preprocessing.image import ImageDataGenerator

test_datagen = ImageDataGenerator(rescale=1. / 255)
test_gen = test_datagen.flow_from_directory(test_dir,
                                            target_size=target_size,
                                            batch_size=batch_size,
                                            class_mode='binary')
model = #defined elsewhere

model.evaluate_generator(test_gen)

Results in the exception:

TypeError                                 Traceback (most recent call last)
~\.virtualenvs\ML-WTkM-kxU\lib\site-packages\keras\utils\data_utils.py in get(self)
    577             while self.is_running():
--> 578                 inputs = self.queue.get(block=True).get()
    579                 self.queue.task_done()

C:\Python36\Lib\multiprocessing\pool.py in get(self, timeout)
    643         else:
--> 644             raise self._value
    645 

C:\Python36\Lib\multiprocessing\pool.py in worker(inqueue, outqueue, initializer, initargs, maxtasks, wrap_exception)
    118         try:
--> 119             result = (True, func(*args, **kwds))
    120         except Exception as e:

~\.virtualenvs\ML-WTkM-kxU\lib\site-packages\keras\utils\data_utils.py in get_index(uid, i)
    400     """
--> 401     return _SHARED_SEQUENCES[uid][i]
    402 

~\.virtualenvs\ML-WTkM-kxU\lib\site-packages\keras_preprocessing\image.py in __getitem__(self, idx)
   1262                                        self.batch_size * (idx + 1)]
-> 1263         return self._get_batches_of_transformed_samples(index_array)
   1264 

~\.virtualenvs\ML-WTkM-kxU\lib\site-packages\keras_preprocessing\image.py in _get_batches_of_transformed_samples(self, index_array)
   1734                            interpolation=self.interpolation)
-> 1735             x = img_to_array(img, data_format=self.data_format)
   1736             params = self.image_data_generator.get_random_transform(x.shape)

~\.virtualenvs\ML-WTkM-kxU\lib\site-packages\keras_preprocessing\image.py in img_to_array(img, data_format)
    409     # but original PIL image has format (width, height, channel)
--> 410     x = np.asarray(img, dtype=backend.floatx())
    411     if len(x.shape) == 3:

~\.virtualenvs\ML-WTkM-kxU\lib\site-packages\numpy\core\numeric.py in asarray(a, dtype, order)
    491     """
--> 492     return array(a, dtype, copy=False, order=order)
    493 

TypeError: float() argument must be a string or a number, not 'JpegImageFile'

The above exception was the direct cause of the following exception:

StopIteration                             Traceback (most recent call last)
<ipython-input-4-162faf28a7af> in <module>()
----> 1 model.evaluate_generator(test_gen)

~\.virtualenvs\ML-WTkM-kxU\lib\site-packages\keras\legacy\interfaces.py in wrapper(*args, **kwargs)
     89                 warnings.warn('Update your `' + object_name +
     90                               '` call to the Keras 2 API: ' + signature, stacklevel=2)
---> 91             return func(*args, **kwargs)
     92         wrapper._original_function = func
     93         return wrapper

~\.virtualenvs\ML-WTkM-kxU\lib\site-packages\keras\engine\training.py in evaluate_generator(self, generator, steps, max_queue_size, workers, use_multiprocessing, verbose)
   1478             workers=workers,
   1479             use_multiprocessing=use_multiprocessing,
-> 1480             verbose=verbose)
   1481 
   1482     @interfaces.legacy_generator_methods_support

~\.virtualenvs\ML-WTkM-kxU\lib\site-packages\keras\engine\training_generator.py in evaluate_generator(model, generator, steps, max_queue_size, workers, use_multiprocessing, verbose)
    307 
    308         while steps_done < steps:
--> 309             generator_output = next(output_generator)
    310             if not hasattr(generator_output, '__len__'):
    311                 raise ValueError('Output of generator should be a tuple '

~\.virtualenvs\ML-WTkM-kxU\lib\site-packages\keras\utils\data_utils.py in get(self)
    582         except Exception as e:
    583             self.stop()
--> 584             six.raise_from(StopIteration(e), e)
    585 
    586     def _send_sequence(self):

~\.virtualenvs\ML-WTkM-kxU\lib\site-packages\six.py in raise_from(value, from_value)

StopIteration: float() argument must be a string or a number, not 'JpegImageFile'

[andraugust]

@dareal-andre I had the same error. It was because one of my jpeg images was corrupt. Not a problem with keras (other than hard to decode error message).

Try $ jpeginfo -c /image/folder/path/*.jpg | grep 'WARNING' to find corrupt images.

[soufianesabiri]

My Images are all OK, I am still getting this error please help!

[frankcoumans]

I have the same issue, but with 'TiffImageFile'. My script runs in one anaconda environment, but not in another. The keras version is 2.1.5 in both environments, tensorflow is 1.05 in the 'good' environment, 1.10 in the 'bad' environment. I'm sure there are other differences between the two environments.

[csitaula]

TypeError: float() argument must be a string or a number, not 'TiffImageFile'
I am facing this type of problem? How did you people solve it? I think it is similar types of error

[csitaula]

I have the same issue, but with 'TiffImageFile'. My script runs in one anaconda environment, but not in another. The keras version is 2.1.5 in both environments, tensorflow is 1.05 in the 'good' environment, 1.10 in the 'bad' environment. I'm sure there are other differences between the two environments.

did you solve it? I am facing same problem.

[frankcoumans]

No, unfortunately the only way for me is to clone the good environment.

On Sun, Feb 16, 2020, 08:22 Chiranjibi Sitaula [e-mail]
wrote:

I have the same issue, but with 'TiffImageFile'. My script runs in one
anaconda environment, but not in another. The keras version is 2.1.5 in
both environments, tensorflow is 1.05 in the 'good' environment, 1.10 in
the 'bad' environment. I'm sure there are other differences between the two
environments.

did you solve it? I am facing same problem.

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