app.py

import gradio as gr
import numpy as np
import tensorflow as tf

# Assuming your model is loaded here
model = tf.keras.models.load_model("pain_analysis.h5")

def predict(image):
    image = np.array(image) / 255.0  # Normalize the image
    # Make predictions using your model here
    # result = model.predict(image)
    return result

# Change this line to use gr.Image directly
iface = gr.Interface(
    fn=predict,
    inputs=gr.Image(type="numpy"),  # Use gr.Image directly
    outputs="label"  # Specify the output type as needed
)

iface.launch()