import numpy as np
from PIL import Image
import gradio as gr
from deepface import DeepFace
from datasets import load_dataset

# Cargar el dataset de Hugging Face
dataset = load_dataset("Segizu/dataset_faces")
if "train" in dataset:
    dataset = dataset["train"]

# Cargar embeddings de todas las imágenes del dataset
def build_database():
    database = []
    for i, item in enumerate(dataset):
        try:
            img = item["image"]
            # Convertir a RGB y np.array
            img_rgb = img.convert("RGB")
            img_np = np.array(img_rgb)
            # Obtener representación (embedding)
            representation = DeepFace.represent(img_path=img_np, model_name="Facenet", enforce_detection=False)[0]["embedding"]
            database.append((f"image_{i}", img_rgb, representation))
        except Exception as e:
            print(f"❌ No se pudo procesar imagen {i}: {e}")
    return database

# Inicializamos base de datos de embeddings
database = build_database()

# Comparar imagen cargada con la base
def find_similar_faces(uploaded_image):
    try:
        img_np = np.array(uploaded_image.convert("RGB"))
        query_representation = DeepFace.represent(img_path=img_np, model_name="Facenet", enforce_detection=False)[0]["embedding"]
    except:
        return [], "⚠ No se detectó un rostro válido en la imagen."

    similarities = []
    for name, db_img, rep in database:
        distance = np.linalg.norm(np.array(query_representation) - np.array(rep))
        similarity = 1 / (1 + distance)  # Normalizado
        similarities.append((similarity, name, db_img))

    similarities.sort(reverse=True)
    top_matches = similarities[:5]

    gallery_items = []
    text_summary = ""
    for sim, name, img in top_matches:
        caption = f"{name} - Similitud: {sim:.2f}"
        gallery_items.append((img, caption))
        text_summary += caption + "\n"

    return gallery_items, text_summary

# Interfaz Gradio
demo = gr.Interface(
    fn=find_similar_faces,
    inputs=gr.Image(label="📤 Sube una imagen", type="pil"),
    outputs=[
        gr.Gallery(label="📸 Rostros más similares"),
        gr.Textbox(label="🧠 Similitud", lines=6)
    ],
    title="🔍 Buscador de Rostros con DeepFace",
    description="Sube una imagen y se comparará contra los rostros del dataset alojado en Hugging Face (`Segizu/dataset_faces`)."
)

demo.launch()