JanardhanM/no-reference-iqa

1import gradio as gr2import cv23import numpy as np4import tensorflow as tf5 6# Load the trained model (Fixed path issue)7model = tf.keras.models.load_model("model/modelnriqa_model.keras")8 9# Function to classify image quality10def predict_quality(image):11    img = cv2.resize(image, (224, 224))  # Resize to model input size12    img = img / 255.0  # Normalize13    img = np.expand_dims(img, axis=0)  # Add batch dimension14    mos_score = model.predict(img)[0][0]  # Get predicted score15    print(mos_score)16    # Convert MOS Score to Category17    if mos_score >= 4.5:18        category = "🌟 Excellent"19    elif mos_score > 4.2:20        category = "Average"21    elif mos_score > 3:22        category = "Poor"23    else:24        category = "🚨 Very Poor"25 26    return f"Predicted Quality: {category}"27 28# Create Gradio UI29iface = gr.Interface(30    fn=predict_quality,31    inputs=gr.Image(type="numpy"),32    outputs="text",33    title="📸 No-Reference Image Quality Classifier",34    description="Upload an image and get its quality category."35)36 37# Launch the app (Fix if localhost issue occurs)38iface.launch(share=True)  # Use share=True to get a public link39