(For Vani) face_cropper.py

#import dlib
from PIL import Image
from skimage import io
import matplotlib.pyplot as plt
import os
import pandas as pd
import glob 

dataset = "C:\Documents (Austin)\P-ai\Kaggle\SET_00_OUTPUT_TRAIN_SAMPLE_VIDEOS"

def clear_folder():
  mydir = "C:\Documents (Austin)\P-ai\Kaggle\cropped-faces"
  filelist = [ f for f in os.listdir(mydir) if f.endswith(".jpg") ]
  for f in filelist:
    os.remove(os.path.join(mydir, f))



def detect_faces(image):
    face_detector = dlib.get_frontal_face_detector()

    detected_faces = face_detector(image, 1)
    face_frames = [(x.left(), x.top(),
                    x.right(), x.bottom()) for x in detected_faces]
    return face_frames

df = pd.DataFrame(columns=['filename', 'faces'])
all_filename = []
all_faces = []

individual_imagesets = os.listdir(dataset)
print(individual_imagesets)
for filenames in individual_imagesets:
    filename = dataset + '\\' + filenames
    print(filename)
    counter = 0
    if filename.endswith(".jpg"):
        img_path = dataset + filename
        image = io.imread(img_path)
        detected_faces = detect_faces(image)

        all_filename.append(filename)
        all_faces.append(len(detected_faces))

        for n, face_rect in enumerate(detected_faces):
            face = Image.fromarray(image).crop(face_rect)
            plt.subplot(1, len(detected_faces), n+1)
            plt.axis('off')
            new_path = "C:\Documents (Austin)\P-ai\Kaggle\cropped" + str(counter) + "-" + filename 
            counter += 1;  
            plt.savefig(new_path, dpi=300, bbox_inches='tight')

df['filename'] = all_filename
df['faces'] = all_faces

df.to_csv('all-data.csv')