Upload app.py

app.py

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+import gradio as gr
+import tensorflow as tf
+from PIL import Image
+import numpy as np
+
+# Load your pre-trained model (e.g., TensorFlow Keras model)
+# Replace "currency_model.h5" with the actual path to your model
+model = tf.keras.models.load_model("counterfeitmodel.h5")
+
+# Define the prediction function
+def detect_currency(image):
+    """
+    Function to detect if the input image is of a real or fake currency note.
+    :param image: Uploaded image (.jpg)
+    :return: String indicating 'Real' or 'Fake'
+    """
+    # Resize the image to match the input size expected by the model
+    input_size = (200, 200)  # Replace with your model's expected input size
+    image = image.resize(input_size)
+    
+    # Convert the image to a NumPy array
+    image_array = np.array(image) / 255.0  # Normalize pixel values to [0, 1]
+    
+    # Add batch dimension
+    image_array = np.expand_dims(image_array, axis=0)
+    
+    # Perform prediction
+    prediction = model.predict(image_array)
+    
+    # Assume the model outputs a probability for 'Real' (1) and 'Fake' (0)
+    is_real = prediction[0][0] > 0.5
+    return "Real Currency Note" if is_real else "Fake Currency Note"
+css ="""
+#currency-image {
+    border: 2px solid #00BFFF;
+    border-radius: 10px;
+    padding: 10px;
+}
+
+#prediction-output {
+    font-size: 20px;
+    font-weight: bold;
+    color: #2c3e50;
+    margin-top: 20px;
+    text-align: center;
+    background-color: #ecf0f1;
+    border: 2px solid #00BFFF;
+    border-radius: 10px;
+    padding: 10px;
+}
+"""
+# Create the Gradio interface
+interface = gr.Interface(
+    fn=detect_currency,  # The function to run
+    inputs=gr.Image(type="pil", label="Upload Currency Image (.jpg)"),  # Input type
+    outputs="text",  # Output type
+    title="Currency Note Detector",
+    description="Upload a .jpg image of a currency note to check if it's real or fake.",
+    theme=gr.themes.Base(),  # Hugging Face theme for a professional look
+    live=True,
+    css=css,
+)
+
+# Add the custom CSS to the interface
+
+# Launch the app
+interface.launch(share=True)