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# Module to crop images from the subfolders of the given folder (--data-dir).

# We can think of given folder as the dataset collected from different resources (web, other datasets, etc.)

# with folder names as the names of people in Name_Surname format

# each folder containing the images of that person where each image can contain either individual person

# or multiple people. In second case we have to crop each person in this image and save each person as

# different image in our target directory (--target-dir). Code uses Python 2.7

import dlib

from PIL import Image

from skimage import io

import matplotlib

matplotlib.use('agg')

import matplotlib.pyplot as plt

import pathlib

import os

import argparse

import fnmatch

import random

import time

parser = argparse.ArgumentParser(description='Crop faces from jpeg images in folders containing collected data')

# general

parser.add_argument('--data-dir', default='', help='full path to the directory with collected images without folmatting of folder names')

parser.add_argument('--target-dir', default='', help='full path to the directory where our cropped images dataset should be saved')

args = parser.parse_args()

dataset_dir = args.data_dir

target_dir = args.target_dir

# code below is used to detec faces in each input image

# returns a list with face frames for each person in the input image

def detect_faces(image):

# Create a face detector

face_detector = dlib.get_frontal_face_detector()

# Run detector and get bounding boxes of the faces on image.

detected_faces = face_detector(image, 1)

face_frames = [(x.left()-30, x.top()-30,

x.right()+30, x.bottom()+30) for x in detected_faces] #x.right(), x.bottom()

return face_frames

'''

face_frames = [(x.left()-30, x.top()-40,

(x.left()-30) + 112, (x.top()-40) + 112) for x in detected_faces] #x.right(), x.bottom()

'''

# code below parses the given folders' subfolders and taking each input crops individual person

for folderi in os.listdir(dataset_dir):

folder = dataset_dir + '/' + folderi

print(dataset_dir + '/' + folderi)

target_folder = target_dir + '/' + folderi

print(target_folder)

try:

os.mkdir(target_folder)

except:

print('Directory ', folderi, ' exists')

for image in os.listdir(folder):

print(image)

# Load image

img_path = folder + '/' + image # getting an image from current folder and cropping faces from it '/home/ti/Downloads/crop_and_find/faces/bekmurat_anarbayev/BrX4cAgDlX_.jpg'

image = io.imread(img_path)

# Detect face_frames

detected_faces = detect_faces(image)

size = 112,112

# Crop faces and plot

print(len(detected_faces))

path_to_save = target_folder + '/'

for n, face_rect in enumerate(detected_faces):

face = Image.fromarray(image).crop(face_rect)

face.thumbnail(size)

face.save(path_to_save + str(random.randint(0,99)) + str(random.randint(0,99)), 'jpeg')