encodings.py

import os
import pickle
import cv2
import face_recognition
import numpy as np

# Dataset path
dataset_folder = r"C:\Users\admin\Desktop\FR_1\dataset"
encoding_file = "encodings.pkl"

def process_image(image_path):
    """Loads an image, converts it, resizes, detects face & encodes it."""
    try:
        # Load image using OpenCV
        image = cv2.imread(image_path)
        if image is None:
            print(f"❌ Failed to load {image_path}")
            return None, None
        # Resize image for better face detection
        image = cv2.resize(image, (600, 600))
        rgb_image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
        # Detect faces using CNN model
        face_locations = face_recognition.face_locations(rgb_image, model="cnn") 
        if not face_locations:
            print(f"❌ No face detected in {os.path.basename(image_path)}")
            return None, None
        # Encode the first face found
        face_encodings = face_recognition.face_encodings(rgb_image, face_locations)
        if face_encodings:
            print(f"✅ Face encoded: {os.path.basename(image_path)}")
            return os.path.basename(image_path), face_encodings[0]
        else:
            print(f"❌ No encoding found in {os.path.basename(image_path)}")
            return None, None
    except Exception as e:
        print(f"❌ Error processing {os.path.basename(image_path)}: {e}")
        return None, None

def save_encodings():
    """Loads dataset images, encodes faces, and saves to a file."""
    encodings, filenames = [], []
    image_files = [os.path.join(dataset_folder, f) for f in os.listdir(dataset_folder) if f.lower().endswith((".jpg", ".jpeg", ".png", ".gif"))]
    print(f"📂 Found {len(image_files)} images in dataset.")
    for image_path in image_files:
        filename, encoding = process_image(image_path)
        if encoding is not None:
            filenames.append(filename)
            encodings.append(encoding)
        else:
            print(f"🔍 Skipping {os.path.basename(image_path)} due to encoding failure.")
    # Save encodings
    with open(encoding_file, "wb") as f:
        pickle.dump((np.array(encodings, dtype=np.float32), filenames), f)
    print(f"✅ Saved {len(encodings)} encodings.")

# Run encoding process
save_encodings()