MAM-ViTH-8gpu.toml

# Refer to utils/config.py for definition and options.

version = "mam_vith_8gpu"
dist = true
wandb = false

[model]
trimap_channel = 3
mask_channel = 1
batch_size = 10
freeze_seg = true
self_refine_width1 = 30
self_refine_width2 = 15
    [model.arch]
    seg = "sam_vit_h"
    m2m = "sam_decoder_deep"

[train]
total_step = 20000
warmup_step = 4000
val_step = 0
clip_grad = true
G_lr = 1e-3
rec_weight = 1.0
lap_weight = 1.0
# Uncomment to resume training
#resume_checkpoint = "path/to/checkpoint"
#reset_lr = false


[data]
d646_fg = "path/to/Distinctions-646/Train_ori/FG"
d646_pha = "path/to/Distinctions-646/Train_ori/GT"
aim_fg = "path/to/AIM/Combined_Dataset/fg"
aim_pha = "path/to/AIM/Combined_Dataset/alpha"
human2k_fg = "path/to/Human2K/Train/FG"
human2k_pha = "path/to/Human2K/Train/Alpha"
am2k_fg = "path/to/AM2k/train/fg"
am2k_pha = "path/to/AM2k/train/mask"
rim_img = "path/to/RefMatte/train/img_full"
rim_pha = "path/to/RefMatte/train/mask"
coco_bg = "path/to/COCO/train2017"
bg20k_bg = "path/to/Matting/BG20k/full"
workers = 4
crop_size = 1024
cutmask_prob = 0.25
pha_ratio = 0.5
augmentation = true
random_interp = true
real_world_aug = false

[log]
tensorboard_path = "./logs/tensorboard"
tensorboard_step = 100
tensorboard_image_step = 2000
logging_path = "./logs/stdout"
logging_step =  10
logging_level = "INFO"
checkpoint_path = "./checkpoints/"
checkpoint_step = 2000