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2 Commits

Author SHA1 Message Date
Ivey Song
34c9115258 brainmapping revise 2026-06-06 10:02:05 +08:00
Ivey Song
69b2802895 删除过去的pth 模型 2026-06-06 10:00:39 +08:00
2 changed files with 11 additions and 150 deletions

View File

@@ -1,4 +1,6 @@
import ast import ast
import glob
import os
import threading import threading
from datetime import datetime from datetime import datetime
import multiprocessing as mp import multiprocessing as mp
@@ -167,9 +169,11 @@ class Decoder_main(threading.Thread, device_type):
self.b_design = signal.firwin(65, [bandPass_low / (self.fs/2), bandPass_high / (self.fs/2)], pass_zero=False) # 设计8-30Hz带通滤波器 self.b_design = signal.firwin(65, [bandPass_low / (self.fs/2), bandPass_high / (self.fs/2)], pass_zero=False) # 设计8-30Hz带通滤波器
fileName = 'Model_' + datetime.now().strftime('%Y-%m-%d-%H-%M-%S') fileName = 'Model_' + datetime.now().strftime('%Y-%m-%d-%H-%M-%S')
filePath = './online_Models/' filePath = './online_Models/'
for old_pth in glob.glob(os.path.join(filePath, '*.pth')):
os.remove(old_pth)
self.modelPath = ''.join([filePath, fileName, '.pth']) self.modelPath = ''.join([filePath, fileName, '.pth'])
self.mp_data_queue = mp.Queue() #多进程传参队列 self.mp_data_queue = mp.Queue()
self.mp_result_queue = mp.Queue() #多进程结果队列 self.mp_result_queue = mp.Queue()
def preprocess(self, signal_data): def preprocess(self, signal_data):
# # 计算每行的平均值 # # 计算每行的平均值

View File

@@ -13,159 +13,16 @@ Num_blocks = 1
Num_trials = 10 Num_trials = 10
Audio_device = 0 Audio_device = 0
Rest_time = 2 Rest_time = 2
Device_type = 1
Device_Host = 127.0.0.1
Device_Port = 5086
Upper_Host = 127.0.0.1 Upper_Host = 127.0.0.1
Upper_Port = 8088 Upper_Port = 8088
Serial_port = COM44 Serial_port = COM44
algo_log_level = DEBUG algo_log_level = DEBUG
console_output = 1 console_output = 1
; 64 导设备配置
[device_type_1] ; 64 导设备配置 1; 32 2; 24 3; 16 4; 8 5; 4 6;
[device_type] = 1
device_sample_rate = 250 device_sample_rate = 250
device_channel_nums = 66 device_channel_nums = 66
device_channel_names = ['FP1', 'FP2', 'FC1', 'FC2', 'CP1', 'CP2', 'F3', 'F4', 'P3', 'P4', 'O1', 'O2', 'FT9', 'FT10', 'F7', 'F8', 'TP9', 'TP10', 'AF4', 'PO8', 'PZ', 'FCZ'] device_channel_names = ['FP1', 'FP2', 'PO6', 'POZ', 'F3', 'F4', 'FPZ', 'AF4', 'FC3', 'PO8', 'CP2', 'CP1', 'FCZ', 'PO5', 'FC2', 'FC1', 'C3', 'C4', 'FC4', 'CP4', 'P3', 'P4', 'F5', 'C5', 'F6', 'PO4', 'CP6', 'CP5', 'PO3', 'CP3', 'FC6', 'FC5', 'CB1', 'CB2', 'P5', 'AF7', 'A1', 'T7', 'FT7', 'TP7', 'FT8', 'AF8', 'F8', 'F7', 'P6', 'C6', 'O2', 'O1', 'T8', 'P7', 'CZ', 'PZ', 'P8', 'FZ', 'OZ', 'PO7', 'TP8', 'AF3', 'C2', 'C1', 'P2', 'P1', 'F2', 'F1', 'label', 'label_tag']
device_channel_index = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18] device_channel_index = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65]
[Layout]
main_splitter_left = 993
main_splitter_right = 922
right_splitter_left = 233
right_splitter_right = 771
left_splitter_left = 503
left_splitter_right = 501q
[channel]
channel_x_fp1 = 419
channel_y_fp1 = 124
channel_x_fc1 = 439
channel_y_fc1 = 296
channel_x_fp2 = 576
channel_y_fp2 = 124
channel_x_fc2 = 556
channel_y_fc2 = 299
channel_x_f3 = 397
channel_y_f3 = 231
channel_x_cp1 = 439
channel_y_cp1 = 426
channel_x_f4 = 601
channel_y_f4 = 232
channel_x_cp2 = 559
channel_y_cp2 = 425
channel_x_fc3 = 379
channel_y_fc3 = 295
channel_x_af4 = 571
channel_y_af4 = 171
channel_x_po8 = 645
channel_y_po8 = 564
channel_x_fpz = 499
channel_y_fpz = 112
channel_x_fcz = 499
channel_y_fcz = 300
channel_x_poz = 500
channel_y_poz = 554
channel_x_po5 = 387
channel_y_po5 = 551
channel_x_po6 = 611
channel_y_po6 = 551
channel_x_c3 = 373
channel_y_c3 = 363
channel_x_fc5 = 319
channel_y_fc5 = 292
channel_x_c4 = 620
channel_y_c4 = 363
channel_x_fc6 = 676
channel_y_fc6 = 288
channel_x_p3 = 398
channel_y_p3 = 491
channel_x_cp5 = 322
channel_y_cp5 = 430
channel_x_p4 = 600
channel_y_p4 = 489
channel_x_cp6 = 678
channel_y_cp6 = 430
channel_x_c5 = 313
channel_y_c5 = 361
channel_x_f6 = 650
channel_y_f6 = 223
channel_x_f5 = 349
channel_y_f5 = 224
channel_x_po4 = 573
channel_y_po4 = 551
channel_x_po3 = 429
channel_y_po3 = 550
channel_x_cp4 = 619
channel_y_cp4 = 424
channel_x_cp3 = 381
channel_y_cp3 = 426
channel_x_fc4 = 619
channel_y_fc4 = 295
channel_x_o1 = 423
channel_y_o1 = 598
channel_x_ft9 = 252
channel_y_ft9 = 168
channel_x_o2 = 576
channel_y_o2 = 597
channel_x_ft10 = 798
channel_y_ft10 = 277
channel_x_f7 = 295
channel_y_f7 = 214
channel_x_tp9 = 202
channel_y_tp9 = 445
channel_x_f8 = 701
channel_y_f8 = 215
channel_x_t7 = 252
channel_y_t7 = 362
channel_x_tp7 = 261
channel_y_tp7 = 436
channel_x_ft8 = 734
channel_y_ft8 = 283
channel_x_ft7 = 264
channel_y_ft7 = 286
channel_x_af8 = 645
channel_y_af8 = 159
channel_x_af7 = 351
channel_y_af7 = 160
channel_x_p6 = 652
channel_y_p6 = 499
channel_x_p5 = 348
channel_y_p5 = 499
channel_x_c6 = 683
channel_y_c6 = 362
channel_x_f1 = 447
channel_y_f1 = 236
channel_x_t8 = 745
channel_y_t8 = 361
channel_x_f2 = 549
channel_y_f2 = 235
channel_x_p7 = 300
channel_y_p7 = 505
channel_x_c1 = 435
channel_y_c1 = 363
channel_x_p8 = 698
channel_y_p8 = 508
channel_x_c2 = 559
channel_y_c2 = 359
channel_x_fz = 499
channel_y_fz = 238
channel_x_po7 = 354
channel_y_po7 = 562
channel_x_tp8 = 735
channel_y_tp8 = 438
channel_x_oz = 498
channel_y_oz = 609
channel_x_af3 = 428
channel_y_af3 = 170
channel_x_pz = 501
channel_y_pz = 486
channel_x_p2 = 551
channel_y_p2 = 483
channel_x_cz = 499
channel_y_cz = 361
channel_x_p1 = 448
channel_y_p1 = 488