initial commit

app.py

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+import gradio as gr
+from gradio import inputs
+from tensorflow.keras.models import load_model
+from tensorflow.keras.preprocessing import image
+import numpy as np
+from keras.applications.imagenet_utils import preprocess_input
+
+
+# Load the model
+model = load_model('best_model.h5')
+
+def classify_image(inp):
+    inp = inp.reshape((-1, 224, 224, 3))
+    inp = preprocess_input(inp)
+    prediction = model.predict(inp).flatten()
+    return {"Dementia not Detected": float(prediction[0]), "Dementia Detected": float(prediction[1])}
+
+image = gr.inputs.Image(shape=(224, 224))
+
+interface = gr.Interface(
+    fn=classify_image,
+    inputs=image,
+    outputs="label",
+    title="DementAI",
+)
+
+interface.launch()