Hello @codingforentrepreneurs ,
I am using the same code as of yours and when I run it it shows me the following
Here is the code
`import cv2
import os
import numpy as np
from PIL import Image
import pickle
BASE_DIR = os.path.dirname(os.path.abspath(file))
image_dir = os.path.join(BASE_DIR, "images")
face_cascade = cv2.CascadeClassifier('cascades/data/haarcascade_frontalface_alt2.xml')
recognizer = cv2.face.LBPHFaceRecognizer_create()
current_id = 0
label_ids = {}
y_labels =[]
x_train = []
for root, dirs, files in os.walk(image_dir):
for file in files:
if file.endswith(".png") or file.endswith(".jpg"):
path = os.path.join(root, file)
label = os.path.basename(os.path.dirname(path)).replace(" ", "-"). lower()
#print(label, path)
if not label in label_ids:
label_ids[label] = current_id
current_id +=1
id_ = label_ids[label]
pil_image = Image.open(path).convert("L")
image_array = np.array(pil_image, "uint8")
#print(image_array)
faces = face_cascade.detectMultiScale(image_array, scaleFactor=1.5, minNeighbors=5)
for (x,y,w,h) in faces:
roi = image_array[y:y+h, x:x+w]
x_train.append(roi)
y_labels.append(id)
with open("labels.pickle", 'wb') as f:
pickle.dump(label_ids, f)
recognizer.train(x_train, np.array(y_labels))
recognizer.save("trainner.yml")`