Deeplearning/main.py

42 lines
1.2 KiB
Python

from Qtorch.Models.Qmlp import Qmlp
from Qtorch.Models.Qcnn import QCNN
from Qfunctions.loaData import load_data
from Qfunctions.saveToxlsx import save_to_xlsx as save_to_xlsx
import string
def main():
projet_name = '20240821Sound' # 输入元数据文件夹名称
label_names = ['flim', 'nano', 'pressure', 'sensor', 'water'] # 请在[]内输入每一个分类的名称
print(label_names)
data = load_data(projet_name, label_names, isDir=False, fileClass='xlsx')
model = Qmlp(
data=data,
labels=label_names,
hidden_layers = [128],
dropout_rate=0
)
# model = QCNN(
# X_train=X_train, X_test=X_test, y_train=y_train, y_test= y_test,
# dropout_rate=0
# )
pca_2d, pca_3d = model.get_PCA()
model.fit(300)
cm = model.get_cm()
epoch_data = model.get_epoch_data()
save_to_xlsx(project_name=projet_name, file_name="pca_2d", data=pca_2d)
save_to_xlsx(project_name=projet_name, file_name="pca_3d", data=pca_3d)
save_to_xlsx(project_name=projet_name, file_name="cm", data=cm )
save_to_xlsx(project_name=projet_name, file_name="acc_and_loss", data=epoch_data)
print("Done")
if __name__ == '__main__':
main()