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import os
import cv2
import face_recognition
import pickle
import pyrebase
# Initialize Firebase using Pyrebase
config = {
"apiKey": "AIzaSyClnRJAnrJgAgkYjuYnlvu-CJ6Cxyklebo",
"databaseURL": "https://console.firebase.google.com/project/socioverse-2025/database/socioverse-2025-default-rtdb/data/~2F",
"authDomain": "socioverse-2025.firebaseapp.com",
"projectId": "socioverse-2025",
"storageBucket": "socioverse-2025.appspot.com",
"messagingSenderId": "689574504641",
"appId": "1:689574504641:web:a22f6a2fa343e4221acc40",
"serviceAccount":"socioverse-2025-firebase-adminsdk-gcc6m-6bfb53e6d9.json"
}
firebase = pyrebase.initialize_app(config)
storage = firebase.storage()
# Define the folder containing face images in the Firebase Storage bucket
storage_folder = "Faces/"
# Create an array to store encodings and corresponding labels
face_encodings = []
labels = []
# List all files in the Firebase Storage folder
blobs = storage.child(storage_folder).list_files()
for blob in blobs:
if blob.name.startswith(storage_folder) and (blob.name.endswith(".jpeg") or blob.name.endswith(".jpg") or blob.name.endswith(".png")):
# Download the image to a local file
url = storage.child(f"{blob.name}").get_url(None)
storage.child(url).download(f"{blob.name}","temp.jpeg")
# Load the image using OpenCV
img = cv2.imread("temp.jpeg")
# Convert the BGR image to RGB
rgb_img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
encode = face_recognition.face_encodings(img)[0]
face_encodings.append(encode)
name_parts = blob.name.split('/')
name = name_parts[-1]
name_parts = name.split('$')
name = name_parts[0]
labels.append(name)
# Delete the temporary downloaded image
os.remove("temp.jpeg")
# Save the encodings and labels to a pickle file
data = {"encodings": face_encodings, "labels": labels}
with open("face_encodings.pkl", "wb") as file:
pickle.dump(data, file)
# Upload the pickle file to Firebase Storage
pkl_blob = storage.child(f"{storage_folder}pkl/face_encodings.pkl")
pkl_blob.put("face_encodings.pkl")
print("Face encodings and labels saved to Firebase Storage in 'faces/pkl' folder as 'face_encodings.pkl'.") |