Create predictor.py

predictor.py

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+import tensorflow as tf
+from tensorflow.keras.preprocessing import image
+import numpy as np
+from huggingface_hub import from_pretrained_keras
+model = from_pretrained_keras("okeowo1014/catsanddogs")
+
+# Load the saved model
+loaded_model = tf.keras.models.load_model('fingerprint_recognition_model.keras')
+
+# Define the image path for the new image you want to predict
+image_path = 'path_to_your_new_image.jpg'
+
+# Load and preprocess the image
+img = image.load_img(image_path, target_size=(224, 224), color_mode='grayscale')
+img_array = image.img_to_array(img)
+img_array = np.expand_dims(img_array, axis=0)
+img_array /= 255.  # Normalize the image data
+
+# Make predictions
+predictions = loaded_model.predict(img_array)
+
+# Get the predicted class label
+predicted_class = np.argmax(predictions[0])
+
+# Print the predicted class label
+print(f'Predicted class label: {predicted_class}')