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image_preprocess.py
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from PIL import Image
import numpy as np
import random
def IoUofTwoSameImages(region1, region2):
#clock-wise
m1 = ((region1[0], region1[1]), (region1[2], region1[1]), (region1[2],region1[3]),(region1[0], region1[3]))
m2 = ((region2[0], region2[1]), (region2[2], region2[1]), (region2[2],region2[3]), (region2[0], region2[3]))
result = []
intersection = 0.0
area = 2*abs((m1[1][0] - m1[0][0]) * (m1[3][1] - m1[0][1]))
for p in m1:
if(p[0] >= m2[0][0] and p[0] <= m2[1][0] and p[1] >= m2[0][1] and p[1] <= m2[3][1]):
result.append(p)
for p in m2:
if(p[0] >= m1[0][0] and p[0] <= m1[1][0] and p[1] >= m1[0][1] and p[1] <= m1[3][1]):
result.append(p)
#print "len:", len(result)
if(len(result) == 2):
intersection = abs((result[1][0] - result[0][0]) * (result[1][1] - result[0][1]))
elif(len(result) == 4):
#find the duijiao
if(result[0][0] != result[1][0] and result[0][1] != result[1][1]):
intersection = abs((result[1][0] - result[0][0]) * (result[1][1] - result[0][1]))
elif(result[0][0] != result[2][0] and result[0][1] != result[2][1]):
intersection = abs((result[2][0] - result[0][0]) * (result[2][1] - result[0][1]))
elif(result[0][0] != result[3][0] and result[0][1] != result[3][1]):
intersection = abs((result[3][0] - result[0][0]) * (result[3][1] - result[0][1]))
#print region1, region2, intersection/float(area - intersection)
return intersection/float(area - intersection)
if __name__ == "__main__":
#write to file
output = open('aflw.list', 'w')
#read faces rect from file
faces_file = open('face_rect.txt', 'r')
imageFaces = {}
for line in faces_file.readlines():
if(not line.startswith('#')):
imagePath = line.split('\t')[1].strip()
if(imagePath in imageFaces):
imageFaces[imagePath].append(line)
else:
imageFaces[imagePath] = [line]
faces_file.close()
#del the proprocess image.
###########################################
#has_pro = open('aflw.list5', 'r')
# for line in has_pro.readlines():
# has_image = line.split(' ')[0].split('/')[-1].split('_')[0] + '.jpg'
# if('flickr/3/' + has_image in imageFaces):
# print has_image
# imageFaces.pop('flickr/3/' + has_image, None)
# elif('flickr/0/' + has_image in imageFaces):
# print has_image
# imageFaces.pop('flickr/0/' + has_image, None)
# elif('flickr/2/' + has_image in imageFaces):
# print has_image
# imageFaces.pop('flickr/2/' + has_image, None)
#####################################
count = 0
for imagePath, faces in imageFaces.iteritems():
imagePath = 'aflw/data/' + imagePath
try:
im = Image.open(imagePath)
face_regions = []
for item in faces:
face_id = item.split('\t')[0].strip()
imageName = item.split("\t")[1].split("/")[-1].replace(".jpg", "").strip()
face_x = int(item.split('\t')[2].strip())
face_y = int(item.split('\t')[3].strip())
face_w = int(item.split('\t')[4].strip())
face_h = int(item.split('\t')[5].strip())
#crop the face.
face_region_x = face_x + face_w
face_region_y = face_y + face_h
if(face_region_x > im.size[0]):
face_region_x = im.size[0]
if(face_region_y > im.size[1]):
face_region_y = im.size[1]
face_region = (face_x, face_y, face_region_x, face_region_y)
face_regions.append(face_region)
#use sliding windows of the same size with face, select the IoU >= 0.5 as face, IoU <=0.3 as non-face.
face_width = face_regions[0][2]-face_regions[0][0]
face_height = face_regions[0][3]-face_regions[0][1]
step = face_width/ 5
for i in range(0, im.size[0]- face_width + 1, step):
for j in range(0, im.size[1] - face_height + 1, step):
#crop the image.
# crop = im.crop((i,j, i + face_width, j+face_height))
iou_face = False
for face_region in face_regions:
IoU = IoUofTwoSameImages((i,j, i + face_width, j+face_height), (face_region[0], face_region[1], face_region[2], face_region[3]))
if(IoU >= 0.5):
crop = im.crop((i,j, i + face_width, j+face_height))
crop.save("crop_images/face/" + imageName + "_" + str(count) + ".jpg")
output.write("crop_images/face/" + imageName + "_" + str(count) + ".jpg" + " " + str(IoU) + "\n")
count += 1
iou_face = True
if(iou_face):
continue
IoUCount = 0
for face_region in face_regions:
IoU = IoUofTwoSameImages((i,j, i + face_width, j+face_height), (face_region[0], face_region[1], face_region[2], face_region[3]))
if(IoU <= 0.2):
IoUCount += 1
if(IoUCount == len(face_regions)):
pixels = list(crop.getdata())
array = np.array(pixels)
remove = 0
if(type(array.std(axis=0)) is np.float64):
if(array.std(axis=0) < 8 and random.random() < 0.05):
crop = im.crop((i,j, i + face_width, j+face_height))
crop.save("crop_images/non-face/" + imageName + "_" + str(count) + ".jpg")
output.write("crop_images/non-face/" + imageName + "_" + str(count) + ".jpg" + " " + str(IoU) + "\n")
count += 1
continue
elif(type(array.std(axis=0)) is not np.float64):
#print array.std(axis=0)
for k in array.std(axis=0):
if(k < 8):
remove += 1
if(remove == 3 and random.random() < 0.05):
crop = im.crop((i,j, i + face_width, j+face_height))
crop.save("crop_images/non-face/" + imageName + "_" + str(count) + ".jpg")
output.write("crop_images/non-face/" + imageName + "_" + str(count) + ".jpg" + " " + str(IoU) + "\n")
count += 1
continue
if(random.random() < 0.1):
crop = im.crop((i,j, i + face_width, j+face_height))
crop.save("crop_images/non-face/" + imageName + "_" + str(count) + ".jpg")
output.write("crop_images/non-face/" + imageName + "_" + str(count) + ".jpg" + " " + str(IoU) + "\n")
count += 1
print count
except IOError:
print "No such file", imagePath