# coding: utf-8
# In[1]:
import sys
import os
sys.path.append(os.path.abspath(os.path.join(os.path.abspath('.'), '../../')))
from keras.models import load_model
from src.limit import limitUsage
limitUsage("3")
# In[2]:
import pandas as pd
import random
import numpy as np
import cv2
import os
from concurrent.futures import ThreadPoolExecutor, ProcessPoolExecutor
import threading
import shutil
def get_train_data(train_file):
## 20% for testing
df = pd.read_csv(train_file)
n = int(df.shape[0] * .8)
label_train = df.iloc[:n, -1]
df_train = df.iloc[:n, :]
df_test = df.iloc[n:, :]
label_test = df.iloc[n:, -1]
## clean the test and train file
import csv
from src.config.staticConfig import StaticConfig
from src.data.dataRep import Image
import os
from src.limit import limitUsage
## to avoid accidental gpu usage
limitUsage("5,6")
def is_valid(urls, is_train):
for url in urls:
if not os.path.exists(StaticConfig.getImagePath(url, is_train)):
return False
return True
all_valid_entries = {}
def get_key(is_train, row, index):
return '_'.join(row[index:index + 5]) + '_' + str(is_train)
def get_processed_file_name(is_train, row, index):
key = get_key(is_train, row, index)
if (key in all_valid_entries):
return all_valid_entries[key]
start_index = index * 5
img = Image(row[start_index], row[start_index + 1], row[start_index + 2],
row[start_index + 3], row[start_index + 4], False)
import sys
sys.path.append('..')
from data.dataRep import FCEXPDataSet
from config.staticConfig import StaticConfig
from src.limit import limitUsage
### Command line options should be added in future
limitUsage("7")
## download images from the url
trainEntries = FCEXPDataSet(StaticConfig.getTrainCSVPath())
#trainEntries.downloadImages()
trainEntries.cutImages()
del trainEntries
testEntries = FCEXPDataSet(StaticConfig.getTestCSVPath(), "test")
testEntries.cutImages()
#testEntries.downloadImages()
del testEntries
# coding: utf-8
# In[16]:
import sys
import os
sys.path.append(os.path.abspath(os.path.join(os.path.abspath('.'), '../../')))
from keras.models import load_model
from src.limit import limitUsage
limitUsage("2")
# In[17]:
modelFile = '../model/keras/model/facenet_keras.h5'
# faceNetModel = load_model(modelFile)
# In[18]:
#faceNetModel.summary()
# In[19]:
facenet_model = load_model(modelFile)
# In[20]:
#!pip install git+https://www.github.com/keras-team/keras-contrib.git
#!pwd
# coding: utf-8
# In[16]:
import sys
import os
sys.path.append(os.path.abspath(os.path.join(os.path.abspath('.'), '../../')))
from keras.models import load_model
from src.limit import limitUsage
limitUsage("5")
# In[17]:
modelFile = '../model/keras/model/facenet_keras.h5'
# faceNetModel = load_model(modelFile)
# In[18]:
#faceNetModel.summary()
# In[19]:
facenet_model = load_model(modelFile)
# In[20]:
#!pip install git+https://www.github.com/keras-team/keras-contrib.git
#!pwd
# In[42]: