how to use python predict on image?

Question

mikhail_p OP

Created Jun ’17

Replies 4

Boosts 0

Views 5.2k

Participants 4

I've converted model from caffe and trying to run predict like this:

e = np.zeros((1,3,224,224))
d = {}
d['data'] = e
r = coreml_model.predict(d)

And have

RuntimeError: {

NSLocalizedDescription = "The model expects input feature data to be an image, but the input is of type 5.";

}

Any ideas?

Thanks!

Answered by in 236602022

For Images, CoreML uses python's Pillow library (pip install Pillow). Here is the code snippet that should work for you

import coremltools

# Load an image using PIL
from PIL import Image
rose = Image.open('rose.jpg')

coreml_model.predict({'data': rose})

An example of doing this is also availiable in Session 710's video (https://developer.apple.com/videos/play/wwdc2017/710/)

Note that in your code above, you were passing a Numpy object which gets converted to an MLMultiArray in CoreML.

Boost

Answer 1

OP

Apple

Jun ’17

Accepted Answer

For Images, CoreML uses python's Pillow library (pip install Pillow). Here is the code snippet that should work for you

import coremltools

# Load an image using PIL
from PIL import Image
rose = Image.open('rose.jpg')

coreml_model.predict({'data': rose})

An example of doing this is also availiable in Session 710's video (https://developer.apple.com/videos/play/wwdc2017/710/)

Note that in your code above, you were passing a Numpy object which gets converted to an MLMultiArray in CoreML.

0

Answer 2

mikhail_p OP

Jun ’17

It works, thanks!

0

Answer 3

gbonesso OP

Jul ’17

I'm trying to do the same, following the WWDC video, but I'm receiving an error:

Error: value type not convertible:
<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=200x200 at 0x121AC04D0>
---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
<ipython-input-38-82fd85392a7f> in <module>()
----> 1 model.predict({'stampImage': image})


/anaconda/envs/coremltools_py2/lib/python2.7/site-packages/coremltools/models/model.pyc in predict(self, data, **kwargs)
    236         """
    237         if self.__proxy__:
--> 238             return self.__proxy__.predict(data)
    239         else:
    240             if _sys.platform != 'darwin' or float('.'.join(_platform.mac_ver()[0].split('.')[:2])) < 10.13:


RuntimeError: value type not convertible

The Keras model works fine... Do you have any idea about what is going wrong?

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Answer 4

Raimi OP

Mar ’19

e = np.zeros((3,224,224)) 
d = {} 
d['data'] = e 
r = coreml_model.predict(d)

The model expects the input to be of size 1, 3 or 5. So just change (1,3,224,224) which is of size 4 to (3,224,224) which is of size 3.

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