README.md

metadata

title: RefDiffNet
emoji: 🔬
colorFrom: blue
colorTo: green
sdk: gradio
sdk_version: 5.23.0
python_version: '3.10'
app_file: app.py
pinned: false
license: agpl-3.0

RefDiffNet — PCB Reference–Defect Enrichment (A11_CA)

Space: vinayedula/RefDiffNet

Standalone Gradio demo for the A11_CA prebackbone (no Ultralytics at runtime).

• Inputs: defect PCB image + golden reference image
• Output: enriched image (enriched = defect + α · gate · delta)

Weights: weights/prebackbone_a11_ca.pt (~few MB)

Deploy to Hugging Face Spaces

1. Prepare the Space folder locally

From the VYOLO repo root:

cd /mnt/data/vinay/work/VYOLO
bash hf_prebackbone_demo/prepare_space.sh

This will:

• Extract prebackbone_a11_ca.pt from best.pt (uses the VYOLO ultralytics fork once on your machine)
• Copy example image pairs into examples/
• Remove legacy vendor/ if present

2. Push to vinayedula/RefDiffNet

cd hf_prebackbone_demo
bash deploy_to_refdiffnet.sh

Note: The Space ships only a11_ca.py, prebackbone_infer.py, and prebackbone_a11_ca.pt — not the full ultralytics tree.

3. Space settings (recommended)

Setting	Value
Hardware	CPU Basic (works) or GPU for faster inference
Secrets	Optional: HF_TOKEN if weights are in a private model repo

Alternative: host weights on the Hub

HF_MODEL_REPO=YOUR_USER/YOUR_MODEL

The app downloads prebackbone_a11_ca.pt from that repo.

Run locally

cd hf_prebackbone_demo
# Clean broken Gradio 4.x + starlette 1.x mix if you hit jinja2 / localhost errors:
pip uninstall -y gradio gradio-client starlette fastapi uvicorn 2>/dev/null || true
pip install -r requirements.txt
pip install --force-reinstall "numpy>=1.23.0,<2"
export PREBACKBONE_ONLY_WEIGHTS=weights/prebackbone_a11_ca.pt
python app.py

Open http://127.0.0.1:7860 (default bind). Remote server: GRADIO_SERVER_NAME=0.0.0.0 python app.py or SSH port-forward.

One-time weight extraction (from full best.pt)

Only needed if you do not already have prebackbone_a11_ca.pt:

ULTRALYTICS_ROOT=../ultralytics python extract_prebackbone_weights.py \
  --ckpt ../ultralytics/Proposed/yolo12_training/HRIPCB_Results/yolo12n_hripcb_200epochs_batch16/weights/best.pt

Layout

File	Role
a11_ca.py	Standalone A11_CA module definition
prebackbone_infer.py	Load weights, run enrichment (same H×W inputs)
gradio_patch.py	Gradio 5.16 / client 1.7 compatibility patch
app.py	Gradio UI
weights/prebackbone_a11_ca.pt	Prebackbone weights only

Environment variables

Variable	Description
PREBACKBONE_ONLY_WEIGHTS	Path to prebackbone_a11_ca.pt
HF_MODEL_REPO	Hub repo with prebackbone_a11_ca.pt
PREBACKBONE_DEVICE	cpu or cuda (default: auto)
PORT	Gradio port (default 7860)