app.py

import gradio as gr
import torch
from transformers import pipeline
from PIL import Image
import numpy as np

# Load emotion model from Hugging Face
emotion_pipeline = pipeline(
    "image-classification",
    model="dima806/facial_emotions_image_detection"
)

def predict_mood(image):

    if image is None:
        return "No image uploaded"

    img = Image.fromarray(image.astype('uint8'), 'RGB')

    results = emotion_pipeline(img)

    top_result = max(results, key=lambda x: x["score"])

    label = top_result["label"]
    confidence = round(top_result["score"] * 100, 2)

    return f"Detected Emotion: {label} ({confidence}%)"

interface = gr.Interface(
    fn=predict_mood,
    inputs=gr.Image(type="numpy"),
    outputs="text",
    title="AI Mood Identifier",
    description="Upload a face image to detect emotion using Deep Learning."
)

interface.launch()