Create Estallie_Interpretor.py

Estallie_Interpretor.py

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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)