Collecting_Data.py

import cv2
import numpy as np
import requests

# Load HAAR face classifier
face_classifier = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')

# Load functions
def face_extractor(img):
    # Function detects faces and returns the cropped face
    # If no face detected, it returns the input image
    
    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    faces = face_classifier.detectMultiScale(gray, 1.3, 5)
    
    if faces is ():
        return None
    
    # Crop all faces found
    for (x,y,w,h) in faces:
        cropped_face = img[y:y+h, x:x+w]

    return cropped_face

# Initialize Webcam
url = "https://192.168.43.1:8080/shot.jpg"
count = 0

# Collect 100 samples of your face from webcam input
while True:

    data = requests.get(url)
    image = data.content
    imageArray = bytearray(image)
    imageID = np.array(imageArray)
    img = cv2.imdecode(imageID, -1)
    face_coord = face_classifier.detectMultiScale(img)
    
    if face_extractor(face_coord) is not None:
        count += 1
        face = cv2.resize(face_extractor(face_coord), (200, 200))
        face = cv2.cvtColor(face, cv2.COLOR_BGR2GRAY)

        # Save file in specified directory with unique name
        file_name_path = '/root/new/face' + str(count) + '.jpg'
        cv2.imwrite(file_name_path, face)

        # Put count on images and display live count
        cv2.putText(face, str(count), (50, 50), cv2.FONT_HERSHEY_COMPLEX, 1, (0,255,0), 2)
        cv2.imshow('Face Cropper', face)
        
    else:
        print("Face not found")
        pass

    if cv2.waitKey(1) == 13 or count == 100: #13 is the Enter Key
        break
        
cv2.destroyAllWindows()      
print("Collecting Samples Complete")