Create app.py

app.py

@@ -0,0 +1,45 @@
+import pandas as pd
+import numpy as np
+from tensorflow.keras.models import load_model
+import gradio as gr
+
+action_map = {
+    1: "Hand at rest",
+    2: "Hand clenched in a fist",
+    3: "Wrist flexion",
+    4: "Wrist extension",
+    5: "Radial deviations",
+    6: "Ulnar deviations",
+}
+
+def action(e1, e2, e3, e4, e5, e6, e7, e8):
+  input_data = np.array([[e1, e2, e3, e4, e5, e6, e7, e8]])
+  prediction = model.predict(input_data)
+  predicted_class = np.argmax(prediction, axis=-1)
+  return action_map.get(predicted_class[0]+1, "Unknown action")
+
+inputs = [
+    gr.Number(label="e1"),
+    gr.Number(label="e2"),
+    gr.Number(label="e3"),
+    gr.Number(label="e4"),
+    gr.Number(label="e5"),
+    gr.Number(label="e6"),
+    gr.Number(label="e7"),
+    gr.Number(label="e8"),
+]
+
+output = gr.Textbox(label="Prediction")
+
+def func(e1, e2, e3, e4, e5, e6, e7, e8):
+  return action(e1, e2, e3, e4, e5, e6, e7, e8)
+
+iface = gr.Interface(
+    fn=func,
+    inputs=inputs,
+    outputs=output,
+    title="ML Model Predictor",
+    description="Enter the 8 feature values to get a prediction."
+)
+
+iface.launch()