"""

Di Wu stevenwudi@gmail.com

2015-06-12

"""

from numpy import log

from glob import glob

import os

import sys

import cPickle

from classes import GestureSample

# customized imports

# modular imports

# the hyperparameter set the data dir, use etc classes, it's important to modify it according to your need

from classes.hyperparameters import use, lr, batch, reg, mom, tr, drop,\

net, DataLoader_with_skeleton_normalisation

from functions.test_functions import *

from functions.train_functions import _shared, _avg, write, ndtensor, print_params, lin,\

training_report, epoch_report, _batch,\

save_results, move_results, save_params, test_lio_skel

from classes.hyperparameters import batch

from dbn.utils import normalize

from convnet3d_grbm_early_fusion import convnet3d_grbm_early_fusion

import scipy.io as sio

## Load Prior and transitional Matrix

dic=sio.loadmat('Prior_Transition_matrix_5states.mat')

Transition_matrix = dic['Transition_matrix']

Prior = dic['Prior']

# number of hidden states for each gesture class

STATE_NO = 5

#data path and store path definition

pc = "wudi"

if pc=="wudi":

data = r"E:\CHALEARN2014\Train" # dir of original data -- note that wudi has decompressed it!!!

data = '/idiap/user/dwu/chalearn/Test'

save_dst = "/idiap/user/dwu/chalearn/Test_CNN_precompute"

res_dir_ = "/idiap/user/dwu/chalearn/result/"

elif pc=="lio":

data = "/media/lio/Elements/chalearn/trainingset"

save_dst = " "

load_flag = False

os.chdir(data)

if pc=="wudi":

samples=glob("*.zip") # because wudi unzipped all the files already!

elif pc=="lio":

samples=glob("*.zip")

print len(samples), "samples found"

used_joints = ['ElbowLeft', 'WristLeft', 'ShoulderLeft', 'HandLeft',

'ElbowRight', 'WristRight', 'ShoulderRight', 'HandRight',

'Head', 'Spine', 'HipCenter']

for file_count, file in enumerate(samples):

condition = (file_count > -1)

if condition: #wudi only used first 650 for validation !!! Lio be careful!

save_path= os.path.join(save_dst, file)

if os.path.isfile(save_path):

print "loading exiting file"

data_dic = cPickle.load(open(save_path,'rb'))

video = data_dic["video"]

Feature_gesture = data_dic["Feature_gesture"]

assert video.shape[0] == Feature_gesture.shape[0]

else:

print("\t Processing file " + file)

# Create the object to access the sample

sample = GestureSample(os.path.join(data,file))

print "finish loading samples"

video, Feature_gesture = sample.get_test_data_wudi_lio(used_joints)

assert video.shape[0] == Feature_gesture.shape[0]# -*- coding: utf-8 -*-

print "finish preprocessing"

out_file = open(save_path, 'wb')

cPickle.dump({"video":video, "Feature_gesture":Feature_gesture}, out_file, protocol=cPickle.HIGHEST_PROTOCOL)

out_file.close()