train.py

import cv2, sys, numpy, os
size = 4
fn_haar = 'haarcascade_frontalface_default.xml'
fn_dir = '/home/pi/Desktop/Camcalt/Program_Files/Poacher Detection/db'
fn_name = raw_input("Name of Person")
type(fn_name)
path = os.path.join(fn_dir, fn_name)
if not os.path.isdir(path):
    os.mkdir(path)
(im_width, im_height) = (112, 92)
haar_cascade = cv2.CascadeClassifier(fn_haar)
webcam = cv2.VideoCapture(0)

# The program loops until it has 20 images of the face.
count = 0
while count < 50:
    (rval, im) = webcam.read()
    if rval:
        #im = cv2.flip(im, 1, 0)
        gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
        mini = cv2.resize(gray, (gray.shape[1] / size, gray.shape[0] / size))
        faces = haar_cascade.detectMultiScale(mini)
        faces = sorted(faces, key=lambda x: x[3])
        if faces:
            face_i = faces[0]
            (x, y, w, h) = [v * size for v in face_i]
            face = gray[y:y + h, x:x + w]
            face_resize = cv2.resize(face, (im_width, im_height))
            pin=sorted([int(n[:n.find('.')]) for n in os.listdir(path)
                   if n[0]!='.' ]+[0])[-1] + 1
            cv2.imwrite('%s/%s.pgm' % (path, pin), face_resize)
            cv2.rectangle(im, (x, y), (x + w, y + h), (0, 255, 0), 3)
            cv2.putText(im, fn_name, (x - 10, y - 10), cv2.FONT_HERSHEY_PLAIN,
                1,(0, 255, 0))
            count += 1
    cv2.imshow('face recon', im)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break
webcam.release()
cv2.destroyAllWindows()