talhailyas/pggp-annotator repository overview

⁠PGGP Crop/Weed Annotator — container usage

Private image: talhailyas/pggp-annotator:latest (GPU required).

⁠Run

docker run --rm --gpus all -p 7860:7860 \
  -v /path/to/your/field/images:/mnt/ssd/Talha/annotator/data/target_dataset \
  -v pggp_db:/home/talha/rpgp/gui_db \
  talhailyas/pggp-annotator:latest

Then open http://localhost:7860⁠.

• --gpus all is required (SAM3 needs CUDA). First start takes ~30–60 s to load the model.
• Mount your images at .../data/target_dataset; they appear in the left browser (tagged target). The image ships a small demo set (heldout_domain) so it works out-of-the-box.
• The named volume pggp_db persists your saved annotations (SQLite) across container runs.
• Default encoder is Config A (LoRA+SupCon); the field bank (field_bank_A.npz) is baked in so Auto-classify works immediately. The InstructSAM baseline button needs a separate sidecar (not in this image) and will report "unavailable" — the PGGP / CoP / SAM3-concept models all work.

⁠What's inside

• The cop conda env (torch 2.7.1+cu126), the PGGP app + GUI (Material Design 3), CoP + SAM3_LoRA code.
• Weights: sam3.pt (SAM3, see bundled LICENSE), LoRA A + ijepa checkpoints, field-bank caches.
• NOT included: the 45 GB week_wise / 17 GB target_dataset research data — mount what you need.

⁠Rebuild / re-push

cd /mnt/ssd/Talha/annotator/docker_build
bash assemble_context.sh                                  # refresh the context from the host
docker build -t talhailyas/pggp-annotator:latest .
docker push talhailyas/pggp-annotator:latest              # repo is PRIVATE