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])