Prediction on Core ML model with PIL image input

predictionOnCoreML.py

##https://github.com/apple/coremltools/blob/master/examples/APIExamples.md
import coremltools
import numpy as np
import PIL.Image

# load a model whose input type is "Image"
model = coremltools.models.MLModel('path/to/the/saved/model.mlmodel')

Height = 20  # use the correct input image height
Width = 60  # use the correct input image width


# Scenario 1: load an image from disk
def load_image(path, resize_to=None):
    # resize_to: (Width, Height)
    img = PIL.Image.open(path)
    if resize_to is not None:
        img = img.resize(resize_to, PIL.Image.ANTIALIAS)
    img_np = np.array(img).astype(np.float32)
    return img_np, img


# load the image and resize using PIL utilities
_, img = load_image('/path/to/image.jpg', resize_to=(Width, Height))
out_dict = model.predict({'image': img})

# Scenario 2: load an image from a numpy array
shape = (Height, Width, 3)  # height x width x RGB
data = np.zeros(shape, dtype=np.uint8)
# manipulate numpy data
pil_img = PIL.Image.fromarray(data)
out_dict = model.predict({'image': pil_img})