Skip to content

Instantly share code, notes, and snippets.

@Rishbah-76
Last active June 23, 2021 05:04
Show Gist options
  • Star 0 You must be signed in to star a gist
  • Fork 0 You must be signed in to fork a gist
  • Save Rishbah-76/8f7b559aa18f019dd5d30ce40ce9bb21 to your computer and use it in GitHub Desktop.
Save Rishbah-76/8f7b559aa18f019dd5d30ce40ce9bb21 to your computer and use it in GitHub Desktop.
Creating a Face Recognization model using LBPH Algo.
# Training the Model
cap.release()
import cv2
import numpy as np
from os import listdir
from os.path import isfile, join
# Get the training data we previously made
data_path = './faces/user/'
onlyfiles = [f for f in listdir(data_path) if isfile(join(data_path, f))]
# Create arrays for training data and labels
Training_Data, Labels = [], []
# Open training images in our datapath
# Create a numpy array for training data
for i, files in enumerate(onlyfiles):
image_path = data_path + onlyfiles[i]
images = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)
Training_Data.append(np.asarray(images, dtype=np.uint8))
Labels.append(i)
# Create a numpy array for both training data and labels
Labels = np.asarray(Labels, dtype=np.int32)
# Initialize facial recognizer
# model = cv2.face.createLBPHFaceRecognizer()
# NOTE: For OpenCV 3.0 use cv2.face.createLBPHFaceRecognizer()
# pip install opencv-contrib-python
# model = cv2.createLBPHFaceRecognizer()
vimal_model = cv2.face_LBPHFaceRecognizer.create()
# Let's train our model
vimal_model.train(np.asarray(Training_Data), np.asarray(Labels))
print("Model trained sucessefully")
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment