Spaces:
Sleeping
Sleeping
File size: 2,146 Bytes
4d4d4eb | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 | import gradio as gr
import numpy as np
from PIL import Image
import cv2
import os
import pickle # For loading the face embeddings database
# Import your face detection and recognition functions
from face_detection import detect_faces
from face_recognition import recognize_face # Assuming you have this
# --- Configuration ---
DATABASE_PATH = "face_database.pkl" # Path to your stored face embeddings
THRESHOLD = 0.6 # Similarity threshold for recognition
# --- Load the face embeddings database (if it exists) ---
face_embeddings_db = {}
if os.path.exists(DATABASE_PATH):
with open(DATABASE_PATH, 'rb') as f:
face_embeddings_db = pickle.load(f)
# --- Function to process an input image ---
def recognize_faces_in_image(image):
img_array = np.array(image)
detected_faces = detect_faces(img_array) # Returns a list of (box, confidence)
output_image = img_array.copy()
results = []
for box, _ in detected_faces:
x1, y1, w, h = box
x2, y2 = x1 + w, y1 + h
face_roi = img_array[y1:y2, x1:x2]
if face_roi.shape[0] > 0 and face_roi.shape[1] > 0:
identity = recognize_face(face_roi, face_embeddings_db, THRESHOLD)
if identity:
color = (0, 255, 0) # Green for recognized
text = identity
else:
color = (255, 0, 0) # Red for unknown
text = "Unknown"
cv2.rectangle(output_image, (x1, y1), (x2, y2), color, 2)
cv2.putText(output_image, text, (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.9, color, 2)
results.append(f"Face detected at ({x1}, {y1}) - {text}")
else:
results.append(f"Small or invalid face detected.")
return [Image.fromarray(output_image), "\n".join(results)]
# --- Gradio Interface ---
iface = gr.Interface(
fn=recognize_faces_in_image,
inputs=gr.Image(label="Upload an Image"),
outputs=[gr.Image(label="Detected Faces"), gr.Textbox(label="Recognition Results")],
title="Face Recognition App",
description="Upload an image and see the detected and recognized faces."
)
iface.launch() |