drywall-clipseg

CLIPSeg fine-tune (HF CIDAS/clipseg-rd64-refined backbone, decoder + FiLM unfrozen) for prompted binary segmentation on drywall imagery. Single checkpoint covers two classes selected by text prompt:

• "segment crack" → wall-crack mask
• "segment taping area" → drywall taping-seam mask

Test metrics (focal_dice loss, threshold 0.6)

Task	Dice	mIoU	Precision	Recall
Crack	0.672	0.531	—	—
Taping	0.727	0.587	—	—

Load + predict

from huggingface_hub import hf_hub_download
import torch
from src.models.clipseg_wrapper import CLIPSegFT

ckpt_path = hf_hub_download(repo_id="ravindrakapse/drywall-clipseg", filename="best.pt")
model = CLIPSegFT(pretrained="CIDAS/clipseg-rd64-refined").cuda()
state = torch.load(ckpt_path, map_location="cuda")
model.load_state_dict(state["model"])
model.eval()

See load_models.py for the full inference pipeline (letterbox + TTA + un-letterbox).