gokuhair.py

import cv2
import sys
import logging as log
import datetime as dt
from time import sleep
import numpy as np
import os
import subprocess

cascPath = "haarcascade_frontalface_default.xml"  # for face detection

# if 404 use sh script to download training data
if not os.path.exists(cascPath):
    subprocess.call(['./download_filters.sh'])
else:
    print('Filters already exist!')

faceCascade = cv2.CascadeClassifier(cascPath)
log.basicConfig(filename='webcam.log',level=log.INFO)

video_capture = cv2.VideoCapture(0)
anterior = 0
hair = cv2.imread('hair3.png')

def dbz_me(hair, fc, x, y, w, h):

    face_width = w
    face_height = h

    hair_width = face_width + 5
    hair_height = face_height + 10

    hair = cv2.resize(hair,(hair_width,hair_height))

    for i in range(hair_height):
        for j in range(hair_width):
            for k in range(3):
                if hair[i][j][k]<235:
                    fc[y+i-int(0.75*face_height)][x+j][k] = hair[i][j][k]
    return fc

while True:
    if not video_capture.isOpened():
        print('Unable to load camera.')
        sleep(5)
        pass

    # Capture frame-by-frame
    ret, frame = video_capture.read()

    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    faces = faceCascade.detectMultiScale(
        gray,
        scaleFactor=1.1,
        minNeighbors=5,
        minSize=(40,40)
    )

    # Draw a rectangle around the faces
    for (x, y, w, h) in faces:
        #cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
        #cv2.putText(frame,"face",(x,y),cv2.FONT_HERSHEY_SIMPLEX,1,(0,0,255),2)
        frame = dbz_me(hair,frame,x,y,w,h)



    if anterior != len(faces):
        anterior = len(faces)
        log.info("faces: "+str(len(faces))+" at "+str(dt.datetime.now()))


    # Display the resulting frame
    cv2.imshow('Video', frame)


    if cv2.waitKey(1) & 0xFF == ord('q'):
        break



# When everything is done, release the capture
video_capture.release()
cv2.destroyAllWindows()