gametab_position = [593, 593, 132, 132]
select_position = [564, 564, 248, 248]
disconnect_position = [1184, 1184, 703, 703]
output_keysList = []
n_input, tensor_size, lstm_classes, n_hidden, lstm_based_Bots, cnn_classes = cgrAPI.gameBotParamInit(
1, 20, 5, 512, 0, 1)
associate_flag, RUNNING_TIME, AI_BOTS_DIR, RESULT_DIR, BIND_CPU, HUMAN_RUN, Reso_Width, Reso_Hight, MultipleMode = cgrAPI.globalParamInit(
)
lstmX, lstmPred, lstmInit, lstmSaver, lstmLogPath = cgrAPI.LSTMInit(
"redeclipse", AI_BOTS_DIR, n_input, tensor_size, lstm_classes,
n_hidden)
pic_region, cnnDetection_graph, cnnDetector = cgrAPI.CNNInit(
"redeclipse", AI_BOTS_DIR, Reso_Width, Reso_Hight, cnn_classes)
output_file = cgrAPI.logsInit(RESULT_DIR)
cgrAPI.commandInit("redeclipse", associate_flag, RUNNING_TIME, BIND_CPU,
HUMAN_RUN, MultipleMode, 5)
with mss.mss(display=':0.0') as sct:
with tf.Session() as lstmSession:
lstmSession.run(lstmInit)
if os.path.isfile(lstmLogPath + "checkpoint"):
lstmSaver.restore(lstmSession, lstmLogPath + "lstm-model")
with tf.Session(graph=cnnDetection_graph) as cnnSession:
start_time = time.time()
cur_time = time.time()
last_cur_time = cur_time
while (cur_time - start_time <= RUNNING_TIME) and (HUMAN_RUN
== 0):
lstm_start = 0
lstm_end = 0
counter_n = counter_n + 1
time.sleep(2)
keyboard_action.mouse_click(XPos)
time.sleep(1)
return
if __name__ == '__main__':
file_name = '../training_data/raw-data/training_data' + str(
int(time.time())) + '.npy'
training_data = []
output_keysList = [0, 0]
dragPos = [681, 681, 679, 679]
flag_count = 0
associate_flag, RUNNING_TIME, AI_BOTS_DIR, RESULT_DIR, BIND_CPU, HUMAN_RUN, Reso_Width, Reso_Hight, MultipleMode = cgrAPI.globalParamInit(
)
cgrAPI.commandInit("imhotepvr", associate_flag, RUNNING_TIME, BIND_CPU,
HUMAN_RUN, MultipleMode)
imhotepvrBotActions()
start_time = time.time()
cur_time = time.time()
while (HUMAN_RUN == 0) and (cur_time - start_time <= RUNNING_TIME):
# click start position
pyautogui.moveTo(dragPos[0], dragPos[2], duration=0.1)
if flag_count == 0:
flag_count += 1
pyautogui.dragRel(300, 0, duration=1)
record = [[0, flag_count], [1, 0, 0, 0]]
training_data.append(record)
elif flag_count == 1:
flag_count += 1
pyautogui.dragRel(-300, 0, duration=1)
if __name__ == '__main__':
count = 0
supertuxkart_restart = [985, 985, 1030, 1030]
lstmInputVec = [0, 0]
n_input, tensor_size, lstm_classes, n_hidden, lstm_based_Bots, cnn_classes = cgrAPI.gameBotParamInit(
1, 2, 3, 512, 1, 2)
associate_flag, RUNNING_TIME, AI_BOTS_DIR, RESULT_DIR, BIND_CPU, HUMAN_RUN, Reso_Width, Reso_Hight, MultipleMode = cgrAPI.globalParamInit(
)
lstmX, lstmPred, lstmInit, lstmSaver, lstmLogPath = cgrAPI.LSTMInit(
"supertuxkart", AI_BOTS_DIR, n_input, tensor_size, lstm_classes,
n_hidden)
pic_region, cnnDetection_graph, cnnDetector = cgrAPI.CNNInit(
"supertuxkart", AI_BOTS_DIR, Reso_Width, Reso_Hight, cnn_classes)
output_file = cgrAPI.logsInit(RESULT_DIR)
cgrAPI.commandInit("supertuxkart", associate_flag, RUNNING_TIME, BIND_CPU,
HUMAN_RUN, MultipleMode, 3)
with mss.mss(display=':0.0') as sct:
with tf.Session() as lstmSession:
lstmSession.run(lstmInit)
if os.path.isfile(lstmLogPath + "checkpoint"):
lstmSaver.restore(lstmSession, lstmLogPath + "lstm-model")
with tf.Session(graph=cnnDetection_graph) as cnnSession:
start_time = time.time()
cur_time = time.time()
last_cur_time = cur_time
while ((cur_time - start_time <= RUNNING_TIME)
and (HUMAN_RUN == 0)):
count += 1
print(count)
position_vec = [0, 1080]
x_dim = range(786, 1096, 1)
last_life_value = 0
retreat_flag = 0
battle_flag = 0
n_input, tensor_size, lstm_classes, n_hidden, lstm_based_Bots, cnn_classes = cgrAPI.gameBotParamInit(
1, 4, 3, 512, 1, 2)
associate_flag, RUNNING_TIME, AI_BOTS_DIR, RESULT_DIR, BIND_CPU, HUMAN_RUN, Reso_Width, Reso_Hight, MultipleMode = cgrAPI.globalParamInit(
)
lstmX, lstmPred, lstmInit, lstmSaver, lstmLogPath = cgrAPI.LSTMInit(
"dota2", AI_BOTS_DIR, n_input, tensor_size, lstm_classes, n_hidden)
pic_region, cnnDetection_graph, cnnDetector = cgrAPI.CNNInit(
"dota2", AI_BOTS_DIR, Reso_Width, Reso_Hight, cnn_classes)
output_file = cgrAPI.logsInit(RESULT_DIR)
cgrAPI.commandInit("dota2", associate_flag, RUNNING_TIME, BIND_CPU,
HUMAN_RUN, MultipleMode, 10)
dotaBotActions()
with mss.mss(display=':0.0') as sct:
with tf.Session() as lstmSession:
lstmSession.run(lstmInit)
if os.path.isfile(lstmLogPath + "checkpoint"):
lstmSaver.restore(lstmSession, lstmLogPath + "lstm-model")
with tf.Session(graph=cnnDetection_graph) as cnnSession:
start_time = time.time()
cur_time = time.time()
last_cur_time = cur_time
while ((cur_time - start_time <= RUNNING_TIME)
and (HUMAN_RUN == 0)):
lstm_start = 0
lstm_end = 0
if __name__ == '__main__':
inmind_center = [940, 566] #960,564
i_counter = 0
last_drag = 0
output_keysList = []
lstmInputVec = [0, 0]
n_input, tensor_size, lstm_classes, n_hidden, lstm_based_Bots, cnn_classes = cgrAPI.gameBotParamInit(
1, 2, 3, 512, 1, 3)
associate_flag, RUNNING_TIME, AI_BOTS_DIR, RESULT_DIR, BIND_CPU, HUMAN_RUN, Reso_Width, Reso_Hight, MultipleMode = cgrAPI.globalParamInit(
)
lstmX, lstmPred, lstmInit, lstmSaver, lstmLogPath = cgrAPI.LSTMInit(
"inmindvr", AI_BOTS_DIR, n_input, tensor_size, lstm_classes, n_hidden)
pic_region, cnnDetection_graph, cnnDetector = cgrAPI.CNNInit(
"inmindvr", AI_BOTS_DIR, Reso_Width, Reso_Hight, cnn_classes)
output_file = cgrAPI.logsInit(RESULT_DIR)
cgrAPI.commandInit("inmindvr", associate_flag, RUNNING_TIME, BIND_CPU,
HUMAN_RUN, MultipleMode, 3)
with mss.mss(display=':0.0') as sct:
with tf.Session() as lstmSession:
lstmSession.run(lstmInit)
if os.path.isfile(lstmLogPath + "checkpoint"):
lstmSaver.restore(lstmSession, lstmLogPath + "lstm-model")
with tf.Session(graph=cnnDetection_graph) as cnnSession:
start_time = time.time()
cur_time = time.time()
last_cur_time = cur_time
while (cur_time - start_time <= RUNNING_TIME) and (HUMAN_RUN
== 0):
lstm_start = 0
lstm_end = 0
pyautogui.moveTo(inmind_center[0], inmind_center[1])