问题描述
rakshith_96@Panega:~/Master/files/Age-Gender-Pred-master$ python3 preprocess.py 回溯（最近一次调用最后一次）： 文件“preprocess.py”，第 120 行，在 FL = FaceAligner() init 中的文件“/home/rakshith_96/Master/files/Age-Gender-Pred-master/align_faces.py”，第 25 行 self.predictor = dlib.shape_predictor(self.Path2ShapePred) RuntimeError: basic_filebuf::underflow error reading the file: Is a directory
import os
import cv2
import re
import time
import random
import shutil
import glob
import scipy.io
import numpy as np
from shutil import copyfile
from datetime import datetime,timedelta
from multiprocessing import Pool
from config import config,parser
from align_faces import FaceAligner
parser = parser['DATA']
def parse_matlab_date(x):
"""
:param x: date string in matlab format
:return: int,year
"""
x,date = int(x),-1
try:
date = (datetime.fromordinal(int(x))
+ timedelta(days=x % 1)
- timedelta(days=366)).year
except:
print("[convertMatlabDate] Failed to parse string {}".format(x))
return date
def clear_dir(path):
"""
remove all files in this directionary
:param path: path to dir
:return:
"""
if os.path.exists(path):
shutil.rmtree(path)
os.mkdir(path)
return
def addlabels(data = 'wiki',clean = False):
"""
move pictures to labled dir and rename to [Age]_[Gender]_[Name].jpg format
:param data: 'wiki' or 'imdb'
:return:
"""
# 1,clean prevIoUs
origin_dir = config.wiki_raw if data == 'wiki' else config.imdb_raw
if clean: clear_dir(config.labeled)
# 2,read Meta data
mat = scipy.io.loadmat(origin_dir + data + '.mat')[data][0][0]
# records
no_face_image = 0
multiple_face_image = 0
wrong_age = 0
wrong_gender = 0
successful = 0
for dob,dop,path,gender,name,face_score,face_score2 \
in zip(mat[0][0],mat[1][0],mat[2][0],mat[3][0],mat[4][0],mat[6][0],mat[7][0]):
if face_score < 0 or not np.isnan(face_score2):
if face_score < 0: no_face_image += 1
if not np.isnan(face_score2): multiple_face_image += 1
continue
age = dop - parse_matlab_date(dob)
if age < int(parser['age_lower']) or age > int(parser['age_upper']):
wrong_age += 1
continue
if gender not in [1.0,0.0]:
wrong_gender += 1
continue
newName = "{}_{}_{}.jpg".format(age,int(gender),name[0]
.replace(' ','')
.replace('/','')
.replace(':',''))
# 2.1 check duplicate
# 2.1 if duplicate exist,append a random number to it name
newNameNoDupli = newName
while os.path.exists(config.labeled + newNameNoDupli):
newNameNoDupli = "{}{}{}".format(newName[:-4],random.randint(1,9999),newName[-4:])
# 2.2 save as a new file
copyfile(origin_dir + path[0],config.labeled + newNameNoDupli)
successful += 1
print("{} Successful,{} no_face_image,{} multiple_face_image,{} wrong_age,{} wrong_gender"
.format(successful,no_face_image,multiple_face_image,wrong_age,wrong_gender))
return
# sort photos by their names
def sort_out_by_name(clean = False):
pwd = os.getcwd()
if clean:
clear_dir(config.named)
os.chdir(config.aligned)
for img in glob.glob("*.jpg"):
name = re.findall(r'[^_]*_[^_]*_([\D]*)[0-9]*.jpg',img)
if not len(name): continue
name = name[0].lower()
if not os.path.exists(config.named + name + '/'):
os.mkdir(config.named + name + '/')
copyfile(img,config.named + name + '/' + img)
os.chdir(pwd)
# Todo: any other ways to get around this public variable?
FL = FaceAligner()
def sub_align_face(picname):
"""
sub thread function to get and store aligned faces
:param picname: pic names
:return:
"""
aligned = FL.getAligns(picname)
if len(aligned) == 0:
return
# copyfile(picname,config.aligned + picname)
cv2.imwrite(config.aligned + picname,aligned[0])
def creat_fgnet_val(clean = False):
if clean:
clear_dir(config.val)
pwd = os.getcwd()
os.chdir(config.fgnet_raw)
for pic in glob.glob("*"):
name,age = re.findall(r'(\d)*A(\d*).*',pic)[0]
newName = "{}_1_{}.jpg".format(age,newName[-4:])
# 2.2 save as a new file
copyfile(config.fgnet_raw + pic,config.val + newNameNoDupli)
os.chdir(pwd)
def align_faces(clean = False):
"""
get aligned faces from labeled folder and store it in aligned folder for training
:param data: 'wiki' or 'imdb'
:param clean: if set,clean aligned folder,else append or rewrite to it
:return:
"""
if clean: clear_dir(config.aligned)
os.chdir(config.labeled)
jobs = glob.glob("*.jpg")
# un-parallel
# for picname in jobs:
# aligned = FL.getAligns(picname)
# if len(aligned) != 1: return
# cv2.imwrite(config.aligned + picname,aligned[0])
# parallel
with Pool() as pool:
try:
pool.map(sub_align_face,jobs)
finally:
pool.close()
return
def sub_divideTrainVal(img):
"""
distribute images randomly to train or test foled by 95% train prob
:param img: image path
:return:
"""
if np.random.rand() < float(parser['train_test_div']):
copyfile(config.aligned + img,config.train + img)
else:
copyfile(config.aligned + img,config.val + img)
return
def divideTrainVal():
"""
distribute images randomly to train or test foled by 95% train prob
:return:
"""
pwt = os.getcwd()
os.chdir(config.aligned)
# clean
clear_dir(config.train)
clear_dir(config.val)
# read into mem
# train,val = [],[]
# parallel
with Pool() as pool:
try:
pool.map(sub_divideTrainVal,glob.glob("*.jpg"))
finally:
pool.close()
# for img in glob.glob("*.jpg"):
# if np.random.rand() < float(parser['train_test_div']):
# cv2.imwrite(config.train + img,cv2.imread(img))
# train.append([cv2.imread(img),img])
# else:
# cv2.imwrite(config.val + img,cv2.imread(img))
# val.append([cv2.imread(img),img])
# dump out of mem
# for img,name in train:
# cv2.imwrite(config.train + img,name)
# for img,name in val:
# cv2.imwrite(config.val + img,name)
os.chdir(pwt)
return
if __name__ == "__main__":
print("labeling..")
addlabels(data='imdb',clean=True)
print("aligning..")
align_faces(clean = True)
print("dividing..")
divideTrainVal()
# creat_fgnet_val(clean=True)
pass
解决方法
一个问题是你在 remove all files in this directionary 中有一个错字，应该是 remove all files in this directory