from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Dropout, Activation, Flatten
from tensorflow.keras.layers import Conv2D
from tensorflow.keras.layers import MaxPooling2D, BatchNormalization
import time
import dataLoading
import gc
from configReader import ConfigReader
CONF = ConfigReader("hyperParameters.ini")
ACTIONS = dataLoading.ACTIONS
TIME_SLOT = CONF.time_slot
FREQUENCY_SLOT = CONF.frequency_slot
CHANNELS_NUM = len(CONF.selected_channels)
RESHAPE = (-1, TIME_SLOT, FREQUENCY_SLOT, CHANNELS_NUM)
HIDDEN_LAYERS = int(CONF.getAttr("default", "hidden_layers"))
# 用于后续规格化，(NTFC)
# 由于后续keras中卷积层默认通道数在最后一个维度上，即channels_last，故此处需要将8放在最后
# cpu版本的tf不支持channels_first，只支持NHWC模式，即channels_last
OUT_SIZE = len(ACTIONS) #输出规格，与分类数有关
# ========================== data create =======================
print("Loading data...")
train_data, test_data, validate_data = dataLoading.load("new_data")
print("Done.")
train_X, train_y = dataLoading.tag_divide(train_data)
test_X, test_y = dataLoading.tag_divide(test_data)
val_X, val_y = dataLoading.tag_divide(validate_data)
# ========================== model design ==========================
from pylsl import StreamInlet, resolve_stream
import tensorflow as tf
import numpy as np
import time
from collections import deque
import os
from boxGraphicView import BoxGraphicView
from configReader import ConfigReader
import dataLoading
CONF = ConfigReader("hyperParameters.ini")
RESHAPE = (-1, 8, 60)
FFT_MAX_HZ = CONF.frequency_slot
HM_SECONDS = 10
TOTAL_ITERS = HM_SECONDS * 25
ACTIONS_H = CONF.getAttr("horizontal", "actions").split(',')
ACTIONS_V = CONF.getAttr("vertical", "actions").split(',')
CHANNELS_NUM = CONF.channels_num
TIME_SLOT = CONF.time_slot
model_h = tf.keras.models.load_model(
os.path.join(CONF.getAttr("horizontal", "models_dir"),
CONF.getAttr("horizontal", "test_model")))
model_v = tf.keras.models.load_model(
os.path.join(CONF.getAttr("vertical", "models_dir"),
CONF.getAttr("vertical", "test_model")))
# model_h.predict(np.zeros((32,60,60,8)))
last_print = time.time()
fps_counter = deque(maxlen=150)
