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import tensorflow as tf
from tensorflow.keras.preprocessing import image
import numpy as np
# Load the model
model = tf.keras.models.load_model('nsfw_classifier.h5')
# Load an image file to test, resizing it to 150x150 pixels (as required by this model)
img = image.load_img('', target_size=(512, 512))
# Convert the image to a numpy array
img_array = image.img_to_array(img)
# Add a fourth dimension to the image (since Keras expects a list of images, not a single image)
img_array = np.expand_dims(img_array, axis=0)/
# Normalize the image
img_array /= 255.
# Use the model to predict the image's class
pred = model.predict(img_array)
# The model returns a probability between 0 and 1
# You can convert this to the class label like this:
label = 'NSFW' if pred[0][0] > 0.5 else 'SFW'
print(pred[0][0])
print("The image is classified as:", label)
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