laser_weeding/config/semantic_seg.yaml

96 lines
1.9 KiB
YAML

train:
experiment_name: 'semantic_sam'
# Model
model:
sam_name: 'sem_sam'
params:
# Fix the a part of parameters in SAM
fix_img_en: True
fix_prompt_en: True
fix_mask_de: False
ckpt_path: '/home/sweet/trt-finetune-anything/sam_ckpts/sam_vit_b_16.pth'
# class_num: 2
class_num: 3 # [background, lettuce, weed] [0, 1, 2]
model_type: 'vit_b' # type should be in [vit_h, vit_b, vit_l, default]
# Dataset
dataset:
name: 'torch_voc_sem'
params:
root: '/data/jinziqi/DATASETS/'
year: '2012'
image_set: 'train'
transforms:
resize:
params:
size: [1024, 1024]
to_tensor:
params: ~
target_transforms:
resize:
params:
size: [1024, 1024]
# Losses
losses:
ce:
weight: 0.5
params: # ~ means None type, the initial params of loss could be identified here
ignore_index: 255
label_one_hot: False
# Optimizer
opt_params:
lr_default: 1e-3
wd_default: 1e-4
momentum: 0.9
lr_list: [ 1e-2, ]
group_keys: [ [ 'mask_adapter.decoder_head', ], ]
wd_list: [ 0.0, ]
opt_name: 'sgd' # 'sgd'
scheduler_name: 'cosine'
# Runner
max_iter: 100000
log_iter: 20
eval_iter: 100
runner_name: 'sem_runner'
# Dataloader
bs: 2 # 8
num_workers: 2
drop_last: True
# Logger
use_tensorboard: True
tensorboard_folder: './experiment/tensorboard'
log_folder: './experiment/log'
model_folder: './experiment/model'
val:
# Dataset
dataset:
name: 'torch_voc_sem'
params:
root: '/data/jinziqi/DATASETS/'
year: '2012'
image_set: 'train'
transforms:
resize:
params:
size: [1024, 1024]
to_tensor:
params: ~
target_transforms:
resize:
params:
size: [1024, 1024]
bs: 2
num_workers: 2
drop_last: True
test:
need_test: False