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face_crop.py
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face_crop.py
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import os
import shutil
import glob
import natsort
import dlib
import cv2
face_detector = dlib.get_frontal_face_detector()
def face_crop(dataset_name):
print('Running Face Detection & Face Cropping for', dataset_name)
# For dataset CASME_sq
if(dataset_name == 'CASME_sq'):
# Create new directory for 'rawpic_crop'
dir_crop = dataset_name + '\\rawpic_crop\\'
if os.path.exists(dir_crop)==False:
os.mkdir(dir_crop)
# Read all images from 'rawpic' then preprocess into 'rawpic_crop'
for subjectName in glob.glob(dataset_name + '\\rawpic\\*'):
dataset_rawpic = dataset_name + '\\rawpic\\' + str(subjectName.split('\\')[-1]) + '\\*'
print('Running Subject', subjectName.split('\\')[-1])
# Create new directory for each subject in 'rawpic_crop'
dir_crop_sub = dataset_name + '\\rawpic_crop\\' + str(subjectName.split('\\')[-1]) + '\\'
if os.path.exists(dir_crop_sub):
shutil.rmtree(dir_crop_sub)
os.mkdir(dir_crop_sub)
# Read videos from 'rawpic'
for vid in glob.glob(dataset_rawpic):
# Create new directory for each video in 'rawpic_crop'
dir_crop_sub_vid = dir_crop_sub + vid.split('\\')[-1]
if os.path.exists(dir_crop_sub_vid):
shutil.rmtree(dir_crop_sub_vid)
os.mkdir(dir_crop_sub_vid)
# Read images from 'raw_pic'
for dir_crop_sub_vid_img in natsort.natsorted(glob.glob(vid+'\\img*.jpg')):
img = dir_crop_sub_vid_img.split('\\')[-1]
# Get img num Ex 001,002,...,2021
count = img[3:-4]
# Load the image
image = cv2.imread(dir_crop_sub_vid_img)
# Dlib face detection
detected_faces = face_detector(image, 1)
# Use first frame as reference frame for face cropping
if (count == '001'):
for face_rect in detected_faces:
face_top = face_rect.top()
face_bottom = face_rect.bottom()
face_left = face_rect.left()
face_right = face_rect.right()
# Crop and resize to 128x128
face = image[face_top:face_bottom, face_left:face_right]
face = cv2.resize(face, (128, 128))
# Write image into 'rawpic_crop'
cv2.imwrite(dir_crop_sub_vid + "\\img{}.jpg".format(count), face)
print('Done Video', vid.split('\\')[-1])
# For dataset SAMM Long Videos
elif(dataset_name == 'SAMMLV'):
# Create new directory for 'SAMM_longvideos_crop'
if os.path.exists(dataset_name + '\\SAMM_longvideos_crop'):
shutil.rmtree(dataset_name + '\\SAMM_longvideos_crop')
os.mkdir(dataset_name + '\\SAMM_longvideos_crop')
# Read all images from 'SAMM_longvideos' then preprocess into 'SAMM_longvideos_crop'
for vid in glob.glob(dataset_name + '\\SAMM_longvideos\\*'):
count = 0
dir_crop = dataset_name + '\\SAMM_longvideos_crop\\' + vid.split('\\')[-1]
# Create new directory for each video in 'SAMM_longvideos_crop'
if os.path.exists(dir_crop):
shutil.rmtree(dir_crop)
os.mkdir(dir_crop)
print('Video', vid.split('\\')[-1])
# Read videos from 'SAMM_longvideos'
for img_count, dir_crop_img in enumerate(natsort.natsorted(glob.glob(vid+'\\*.jpg'))):
img = dir_crop_img.split('\\')[-1].split('.')[0]
# Get img num Ex 0001,0002,...,2021
count = img.split('_')[-1]
# Load the image
image = cv2.imread(dir_crop_img)
# Dlib face detection
detected_faces = face_detector(image, 1)
# Use first frame as reference frame for face cropping
if (img_count == 0):
for i, face_rect in enumerate(detected_faces):
face_top = face_rect.top()
face_bottom = face_rect.bottom()
face_left = face_rect.left()
face_right = face_rect.right()
# Crop and resize to 128x128
face = image[face_top:face_bottom, face_left:face_right]
face = cv2.resize(face, (128, 128))
# Write image into 'rawpic_crop'
cv2.imwrite(dir_crop + "\\{}.jpg".format(count), face)
print('Done Video', vid.split('\\')[-1])
# For dataset SMIC_HS/SMIC_VIS/SMIC_NIR, *Note there might be slightly difference in file structure obtained from original authors
if('SMIC' in dataset_name):
# Get video type, HS/VIS/NIR
video_type = dataset_name.split('_')[1]
dataset_type = dataset_name.split('_')[0]
# Create new directory for 'SMIC_E_{video_type}_crop'
dir_crop = dataset_type + '\\SMIC-E_raw image\\' + video_type + '\\'
if os.path.exists(dataset_type + '\\SMIC_E_' + video_type + '_crop'):
shutil.rmtree(dataset_type + '\\SMIC_E_' + video_type + '_crop')
os.mkdir(dataset_type + '\\SMIC_E_' + video_type + '_crop')
# Read all images from 'SMIC-E_raw image\\{video_type}_long\\SMIC-{video_type}-E\\{video_type}' image then preprocess into 'SMIC_E_{video_type}_crop'
for subjectName in natsort.natsorted(glob.glob(dataset_type + '\\SMIC-E_raw image\\' + video_type + '_long\\SMIC-' + video_type + '-E\\' + video_type + '\\*')):
dataset_rawpic = dataset_type + '\\SMIC-E_raw image\\' + video_type + '_long\\SMIC-' + video_type + '-E\\' + video_type + '\\' + str(subjectName.split('\\')[-1]) + '\\*'
# Create new directory for each subject in 'SMIC_E_{video_type}_crop'
dir_crop_sub = dataset_type + '\\SMIC_E_' + video_type + '_crop\\' + str(subjectName.split('\\')[-1]) + '\\' # Ex: SMIC\SMIC_E_HS_crop\s01
if(str(subjectName.split('\\')[-1])[0] == 's'): # Prevent from creating directory for .xlsx files
if os.path.exists(dir_crop_sub):
shutil.rmtree(dir_crop_sub)
os.mkdir(dir_crop_sub)
print('Subject', subjectName.split('\\')[-1])
# Read videos from 'SMIC-E_raw image\\{video_type}_long\\SMIC-{video_type}-E\\{video_type}'
for vid in natsort.natsorted(glob.glob(dataset_rawpic)):
# Create new directory for each video in 'SMIC-E_raw image\\{video_type}_long\\SMIC-{video_type}-E\\{video_type}'
dir_final_vid = dir_crop_sub + vid.split('\\')[-1] + '\\' # Ex: SMIC\SMIC_E_HS_crop\s01\s1_ne_01
if os.path.exists(dir_final_vid):
shutil.rmtree(dir_final_vid)
os.mkdir(dir_final_vid)
print('Video', vid.split('\\')[-1])
# Read images from 'SMIC-E_raw image\\{video_type}_long\\SMIC-{video_type}-E\\{video_type}'
for img_count, dir_final_img in enumerate(natsort.natsorted(glob.glob(vid+'\\*.jpg'))):
img = dir_final_img.split('\\')[-1]
# Conditions to get img num Ex 559700, 559701..., please change according to file structure
if(video_type == 'HS'):
img_index = img.split('.')[0].split('image')[1]
else:
if(' ' in img):
img_index = img.split('.')[0].split(' ')[1]
else:
img_index = img
# Load the image
image = cv2.imread(dir_final_img)
# Dlib face detection
detected_faces = face_detector(image, 1)
# Use first frame as reference frame for face cropping
if (img_count == 0):
for face_rect in detected_faces:
face_top = face_rect.top()
face_bottom = face_rect.bottom()
face_left = face_rect.left()
face_right = face_rect.right()
# Crop and resize to 128x128
face = image[face_top:face_bottom, face_left:face_right]
face = cv2.resize(face, (128, 128))
# Write image into 'SMIC_E_{video_type}_crop'
cv2.imwrite(dir_final_vid + "\\image{}.jpg".format(img_index), face)
print('Done Video', vid.split('\\')[-1])
# For dataset CASME2
if(dataset_name == 'CASME2'):
# Create new directory for 'CASME2-RAW_crop'
dir_crop = dataset_name + '\\CASME2\\CASME2-RAW_crop\\'
if os.path.exists(dataset_name + '\\CASME2\\CASME2-RAW_crop'):
shutil.rmtree(dataset_name + '\\CASME2\\CASME2-RAW_crop')
os.mkdir(dataset_name + '\\CASME2\\CASME2-RAW_crop')
# Read all images from 'CASME2-RAW' then preprocess into 'CASME2-RAW_crop'
for subjectName in glob.glob(dataset_name + '\\CASME2\\CASME2-RAW\\*'):
dataset_rawpic = dataset_name + '\\CASME2\\CASME2-RAW\\' + str(subjectName.split('\\')[-1]) + '\\*'
# Create new directory for each subject in 'CASME2-RAW_crop'
dir_crop_sub = dataset_name + '\\CASME2\\CASME2-RAW_crop\\' + str(subjectName.split('\\')[-1]) + '\\'
if os.path.exists(dir_crop_sub):
shutil.rmtree(dir_crop_sub)
os.mkdir(dir_crop_sub)
print('Subject', subjectName.split('\\')[-1])
# Read videos from 'CASME2-RAW'
for vid in glob.glob(dataset_rawpic):
# Create new directory for each video in 'CASME2-RAW_crop'
dir_crop_sub_vid = dir_crop_sub + vid.split('\\')[-1]
if os.path.exists(dir_crop_sub_vid):
shutil.rmtree(dir_crop_sub_vid)
os.mkdir(dir_crop_sub_vid)
print('Video', vid.split('\\')[-1])
# Read images from 'CASME2-RAW'
for dir_crop_sub_vid_img in natsort.natsorted(glob.glob(vid+'\\img*.jpg')):
img = dir_crop_sub_vid_img.split('\\')[-1]
# Get img num Ex 001,002,...,290
img_index = img.split('.')[0].split('img')[1]
# Load the image
image = cv2.imread(dir_crop_sub_vid_img)
# Dlib face detection
detected_faces = face_detector(image, 1)
# Use first frame as reference frame for face cropping
if (int(img_index) == 1):
for face_rect in detected_faces:
face_top = face_rect.top()
face_bottom = face_rect.bottom()
face_left = face_rect.left()
face_right = face_rect.right()
# Crop and resize to 128x128
face = image[face_top:face_bottom, face_left:face_right]
face = cv2.resize(face, (128, 128))
# Write image into 'CASME2-RAW_crop'
cv2.imwrite(dir_crop_sub_vid + "\\img{}.jpg".format(img_index), face)
print('Done Video', vid.split('\\')[-1])
print('Face Detection and Face Cropping for', dataset_name, 'All Done!!')
if __name__ == "__main__":
# face_crop('CASME2')
face_crop('SMIC_HS') # Change dir
face_crop('SMIC_NIR')
face_crop('SMIC_VIS')