Create Gradio

Gradio

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+import gradio as gr
+import tensorflow as tf
+from tensorflow.keras.models import load_model
+import numpy as np
+
+# Load your model
+model = load_model('vgg19_binary_nonbinary.h5')
+
+def predict(image):
+    image = image.resize((224, 224))  # Resize to match model input
+    image = np.array(image) / 255.0
+    image = np.expand_dims(image, axis=0)
+    prediction = model.predict(image)
+    return "Non-binary" if prediction[0][0] > 0.5 else "Binary"
+
+iface = gr.Interface(fn=predict, inputs="image", outputs="text", title="Non-binary Image Classifier")
+iface.launch()