I'm trying to load keras model using the code snippet below:
from tensorflow import keras
from PIL import Image, ImageOps
import numpy as np
# Disable scientific notation for clarity
np.set_printoptions(suppress=True)
# Load the model
model = keras.models.load_model('keras_model.h5')
# Create the array of the right shape to feed into the keras model
# The 'length' or number of images you can put into the array is
# determined by the first position in the shape tuple, in this case 1.
data = np.ndarray(shape=(1, 224, 224, 3), dtype=np.float32)
# Replace this with the path to your image
image = Image.open("YES/1.jpg")
#resize the image to a 224x224 with the same strategy as in TM2:
#resizing the image to be at least 224x224 and then cropping from the center
size = (224, 224)
image = ImageOps.fit(image, size, Image.ANTIALIAS)
#turn the image into a numpy array
image_array = np.asarray(image)
# display the resized image
image.show()
# Normalize the image
normalized_image_array = (image_array.astype(np.float32) / 127.0) - 1
# Load the image into the array
data[0] = normalized_image_array
# run the inference
prediction = model.predict(data)
print(prediction)
When I execute the above code I get following error:
File "C:\ProgramData\Anaconda3\lib\site-packages\tensorflow\python\keras\engine\base_layer.py", line 446, in from_config return cls(**config)
File "C:\ProgramData\Anaconda3\lib\site-packages\tensorflow\python\keras\engine\input_layer.py", line 80, in init raise ValueError('Unrecognized keyword arguments:', kwargs.keys())
ValueError: ('Unrecognized keyword arguments:', dict_keys(['ragged']))
import tensorflow as tf; print(tf.__version__)– Vlad