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get_face.py
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get_face.py
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# -*- coding: utf8
# import scipy.misc
import os
import scipy.misc
import numpy as np
__author__ = 'haizhu'
import face_recognition
from PIL import Image, ImageDraw
import math
def recognition_landmarks(image):
image = scipy.misc.fromimage(image, flatten=False, mode='RGB')
face_landmarks_list = face_recognition.face_landmarks(image)
print(face_landmarks_list)
for face_landmarks in face_landmarks_list:
# Print the location of each facial feature in this image
facial_features = [
'chin',
'left_eyebrow',
'right_eyebrow',
'nose_bridge',
'nose_tip',
'left_eye',
'right_eye',
'top_lip',
'bottom_lip'
]
for facial_feature in facial_features:
print("The {} in this face has the following points: {}".format(facial_feature,
face_landmarks[facial_feature]))
# Let's trace out each facial feature in the image with a line!
image = Image.fromarray(image)
d = ImageDraw.Draw(image)
for facial_feature in facial_features:
d.line(face_landmarks[facial_feature], width=5)
image.show()
pass
def resizeFaceCenter(image):
"""
把图像摆正
:param image:
:return:
"""
image = scipy.misc.fromimage(image, flatten=False, mode='RGB')
face_landmarks_list = face_recognition.face_landmarks(image)
if len(face_landmarks_list) < 1:
return None
face_landmarks = face_landmarks_list[0]
# for face_landmarks in face_landmarks_list:
# Print the location of each facial feature in this image
facial_features = [
# 'chin',
# 'left_eyebrow',
# 'right_eyebrow',
# 'nose_bridge',
# 'nose_tip',
'left_eye',
'right_eye',
# 'top_lip',
# 'bottom_lip'
]
# for facial_feature in facial_features:
# print("The {} in this face has the following points: {}".format(facial_feature,
# face_landmarks[facial_feature]))
# Let's trace out each facial feature in the image with a line!
left_eye = face_landmarks['left_eye']
right_eye = face_landmarks['right_eye']
image = Image.fromarray(image)
# d = ImageDraw.Draw(image)
# d.line(left_eye, width=5)
# d.line(right_eye, width=5)
# print('left_eye', left_eye)
center_leye = np.sum(left_eye, axis=0) / len(left_eye)
center_reye = np.sum(right_eye, axis=0) / len(right_eye)
# print('center_leye', center_leye)
# print('center_reye', center_reye)
# center = np.add(center_reye, center_leye) / 2
# print('center', center)
cons = np.subtract(center_reye, center_leye)
sin_value = cons[1] / cons[0]
degree = math.degrees(math.atan(sin_value))
image = image.rotate(degree).copy()
# .save('/Users/haizhu/Desktop/jiemo/test_male/tmp/rotate.jpg')
# image.show()
return image
pass
class Faces(object):
def getFaceImage(self, name='', padding_rate=0.12):
"""
:param name:
:return: image,location (top, right, bottom, left)
"""
# path = '/Users/haizhu/Desktop/jiemo/test/khKSUTBpHJsD8s41TXBPxw.jpg'
im = Image.open(name)
resize_img = resizeFaceCenter(im)
if resize_img is not None:
im = resize_img
# image = face_recognition.load_image_file(path)
image = scipy.misc.fromimage(im, flatten=False, mode='RGB')
face_locations = face_recognition.face_locations(image) # (top, right, bottom, left)
if len(face_locations) > 0:
loc = face_locations[0]
padding = padding_rate * (loc[2] - loc[0])
print('padding=', padding)
# im = im.crop((loc[0],loc[1],loc[2]+loc[0],loc[3]+loc[1]))#(left, upper, right, lower)
# (left, upper, right, lower)
left = loc[3] - padding
upper = loc[0] - padding
right = loc[1] + padding
lower = loc[2] + padding
padding_y = 0
padding_x = 0
if right - left > lower - upper:
padding_y = ((right - left) - (lower - upper)) / 2
elif right - left < lower - upper:
padding_x = ((lower - upper) - (right - left)) / 2
width = im.size[0]
height = im.size[1]
im = im.crop((0 if left - padding_x < 0 else left - padding_x, #
0 if upper - padding_y < 0 else (upper - padding_y), #
width if right + padding_x > width else right + padding_x, #
height if lower + padding_y > height else lower + padding_y))
elif len(face_locations) == 0:
return None, None
return im, face_locations[0]
def getFaceLocations(self, name=''):
"""
:param name:
:return: 坐标数组,注意坐标点排布[(top, right, bottom, left),...]
"""
# path = '/Users/haizhu/Desktop/jiemo/test/khKSUTBpHJsD8s41TXBPxw.jpg'
im = Image.open(name)
# image = face_recognition.load_image_file(path)
image = scipy.misc.fromimage(im, flatten=False, mode='RGB')
face_locations = face_recognition.face_locations(image) # (top, right, bottom, left)
return face_locations
def getFaceImageInfo(self, dir):
temDir = os.path.join(dir, 'tmp')
if not os.path.exists(temDir):
os.makedirs(temDir)
images_map = {}
for f in os.listdir(dir):
if f.find('.jp') > 0:
image_path = os.path.join(dir, f)
faceImage, local = self.getFaceImage(image_path)
if faceImage is None:
continue
tmp_path = os.path.join(temDir, '%d_tmp_face.jpg' % (len(images_map)))
faceImage.save(tmp_path)
images_map[image_path] = {'tmp': tmp_path, 'loc': local}
# break
# if len(images_map) > 0:
#
return images_map
def opsFaceImages(self, dir):
"""
预处理图片,也就是我们收集到的图片
:param dir:
:return:
"""
temDir = os.path.join(dir, 'tmp')
if not os.path.exists(temDir):
os.makedirs(temDir)
num = 0
for f in os.listdir(dir):
if f.find('.jp') > 0:
image_path = os.path.join(dir, f)
faceImage, local = self.getFaceImage(image_path)
if faceImage is None:
continue
tmp_path = os.path.join(temDir, f)
num += 1
print('save=', tmp_path, " num=", num)
faceImage.resize((200, 200)).save(tmp_path)
# if num > 2:
# break
# if len(images_map) > 0:
#
if __name__ == '__main__':
faces = Faces()
# dir = '/Users/haizhu/Desktop/jiemo/test'
# dir = '/Users/haizhu/Desktop/jiemo/test_female'
dir = '/Users/haizhu/Downloads/ml/drive-download-20170824T030713Z-001/part2'
images_map = faces.opsFaceImages(dir)
# images = list(v['tmp'] for v in images_map.values())