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Build error
Build error
Excluyendo imágenes grandes
Browse files- .gitignore +3 -0
- app.py +71 -0
- requirements.txt +4 -0
.gitignore
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dataset_faces/
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*.jpg
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*.png
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app.py
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import streamlit as st
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import face_recognition
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import cv2
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import numpy as np
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import os
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from PIL import Image
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# 📂 Ruta donde están las imágenes
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IMAGE_DIRECTORY = "dataset_faces/"
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# 📌 Función para cargar imágenes y extraer embeddings
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def load_images_and_encodings(directory):
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known_encodings = []
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known_images = []
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known_names = []
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for filename in os.listdir(directory):
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if filename.endswith((".jpg", ".png", ".jpeg")):
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path = os.path.join(directory, filename)
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image = face_recognition.load_image_file(path)
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encodings = face_recognition.face_encodings(image)
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if encodings: # Si encontró una cara
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known_encodings.append(encodings[0])
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known_images.append(path)
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known_names.append(filename)
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return known_encodings, known_images, known_names
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# 📌 Cargar imágenes y sus embeddings al inicio
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known_encodings, known_images, known_names = load_images_and_encodings(IMAGE_DIRECTORY)
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# 📌 Función para encontrar imágenes similares
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def find_similar_faces(uploaded_image):
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# Convertir a array de NumPy
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image_np = np.array(uploaded_image)
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face_encodings = face_recognition.face_encodings(image_np)
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if not face_encodings:
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return [], [] # Si no encuentra caras en la imagen subida
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query_encoding = face_encodings[0]
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distances = face_recognition.face_distance(known_encodings, query_encoding)
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# Ordenar las imágenes por similitud
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sorted_indices = np.argsort(distances)
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return [known_images[i] for i in sorted_indices], [distances[i] for i in sorted_indices]
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# 📌 Interfaz en Streamlit
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st.title("🔍 Buscador de Rostros en un Directorio")
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st.write("Sube una imagen y te mostraremos las fotos más similares en el directorio.")
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uploaded_file = st.file_uploader("📤 Sube una imagen", type=["jpg", "png", "jpeg"])
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if uploaded_file:
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# Mostrar imagen subida
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uploaded_image = Image.open(uploaded_file)
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st.image(uploaded_image, caption="Imagen subida", use_column_width=True)
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# Buscar rostros similares
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similar_images, distances = find_similar_faces(uploaded_image)
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# Mostrar resultados
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if similar_images:
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st.subheader("📸 Imágenes más similares:")
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for idx, image_path in enumerate(similar_images[:5]): # Mostrar las 5 más similares
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st.image(image_path, caption=f"Similitud: {1 - distances[idx]:.2f}", use_column_width=True)
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else:
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st.warning("⚠ No se detectó ningún rostro en la imagen subida.")
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requirements.txt
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streamlit
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face_recognition
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opencv-python
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numpy
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