drywall-clipseg / clipseg.yaml
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# CLIPSeg fine-tune — single unified model, both classes via prompt.
# Loss: focal BCE (γ=2) + Dice. Best CLIPSeg variant from ablation.
seed: 42
tasks:
- name: crack
dataset_dir: "data/processed/crack"
prompts:
- "segment crack"
- "segment wall crack"
- "a crack on the wall"
- "thin crack line"
eval_prompt: "segment crack"
- name: taping
dataset_dir: "data/processed/taping"
prompts:
- "segment taping area"
- "segment joint tape"
- "segment drywall seam"
- "drywall joint"
eval_prompt: "segment taping area"
model:
name: clipseg
pretrained: "CIDAS/clipseg-rd64-refined"
freeze_clip: true
unfreeze_decoder: true
unfreeze_film: true
unfreeze_visual_adapter: false
data:
input_size: 352
full_res_eval: true
num_workers: 4
pin_memory: true
train:
epochs: 30
batch_size: 16
optimizer: adamw
lr: 1.0e-4
weight_decay: 1.0e-4
scheduler: cosine
warmup_steps: 300
amp: true
log_every: 20
ckpt_dir: "outputs/checkpoints/clipseg"
log_dir: "outputs/logs/clipseg"
early_stop_patience: 6
monitor: "val/dice_mean"
neg_prob: 0.3
balanced_sampler: true
loss:
type: "focal_dice"
gamma: 2.0
bce_weight: 0.5
dice_weight: 0.5
pos_weight: 5.0
augmentation:
resize: 352
crop_size: 352
hflip_p: 0.5
vflip_p: 0.2
rotate_limit: 15
brightness_contrast_p: 0.3
blur_p: 0.1
noise_p: 0.1
inference:
threshold: 0.5
tta: true
multi_prompt_avg: true
eval:
metrics: [iou, dice, precision, recall]