train_path: str = "C:/Users/user/Documents/pruned_training/training/"
val_path: str = "C:/Users/user/Documents/pruned_training/val/"
model_dir: str = "C:/Users/user/Documents/Thundernet/models/"
model_weights: str = (
    "C:/Users/user/Documents/Thundernet/model/BS4_lossBCE_weights_lr_0.00013713842558297858_reg-1.1743577101671763e-05-ep-13-val_loss0.11463435739278793-train_loss0.053004469722509384-val_iou0.8959722518920898-train_iou0.9606077075004578.hdf5"
)
batch_size: int = 4
augment: bool = False  # True
rand_crop: bool = 0.05
loss: str = "BCE"
weights: list = None # [0.56, 3.27]
classes: int = 2
pretrained_bool: bool = False
pretrained_weigths: str = None
lr: float = 1e-4
epochs: int = 15
resolution: str = "640x480"
kernel_regularizer: float = 2e-4