docs/2_week_plan.md

# 2-Week Build Plan — Indic Heritage Studio v2 (8×80GB NVIDIA Dev → AMD Demo)

**Hackathon window:** July 15 – August 6, 2026 (3 weeks available; we plan for 2 weeks of build + 1 week buffer)
**Dev hardware:** 8 × NVIDIA A100/H100 80GB = 640 GB total VRAM
**AMD GPU budget:** 10 credits = 10 GPU-hours on Radeon Cloud (only the final demo + benchmark burns these)
**Strategy:** Develop 100% on NVIDIA. Burn AMD credits ONLY for: (1) ROCm verification (0.05 cr), (2) live demo video recording (1 cr), (3) official benchmark (0.5 cr). Estimated AMD usage: **~2 credits**, leaving 8 as buffer.

---

## Why This Plan Wins

The v1 plan assumed a single 8 GB RTX 5060 — it had to compromise on every axis (SD 1.5 instead of SDXL, 512² instead of 1024², 8-frame video instead of 25-frame, no LoRA training, no ControlNet, no inpainting, no multi-GPU).

With 8 × 80GB on tap, v2 removes every compromise:

| Axis | v1 (8 GB) | v2 (8 × 80 GB) | Why it matters for the rubric |
|---|---|---|---|
| T2I model | SD 1.5 (DreamShaper) | **SDXL 1.0 + DreamShaper-XL turbo** | 4× higher resolution, dramatically better detail and coherence |
| Style conditioning | Prompt tags only | **Per-style LoRA fine-tune + IP-Adapter XL** | Authentic heritage look, not just "looks vaguely Indian" |
| Image → video | AnimateDiff 16f 512² | **Stable Video Diffusion XT 1.1, 25f 1024×576** | Industry-grade motion quality, 4× more frames |
| Composition control | None | **ControlNet (Canny / Depth / OpenPose)** | Lets users precisely constrain layout — a new feature class |
| Image repair | None | **SDXL inpainting** | Restore damaged real heritage paintings |
| Batch throughput | 1 GPU sequential | **Multi-GPU data parallel, 4× workers** | ~4× speedup, scales to 8× if needed |
| Resolution | 512² | **1024² (1536² for showcase)** | Publication-ready outputs |
| Steps | 25 | **25 turbo / 50 high-quality + SDXL refiner** | Both fast iteration AND showcase quality |

The rubric explicitly rewards: complete input→processing→output workflow (40 pts), innovative scenarios (20 pts), practical application & social value (20 pts), and clear/stable/diverse outputs on Radeon GPU (20 pts). v2 hits all four harder than v1 could.

---

## Hardware Reality Check

The dev box you're on reports 8 GPUs × 81920 MB VRAM each. That's 640 GB total — likely 8 × A100 80GB or 8 × H100 80GB. This changes the build strategy completely:

- **All pipelines can stay resident simultaneously.** No load/unload thrash. T2I on GPU 0, IP-Adapter XL on GPU 1, SVD on GPU 2, ControlNet on GPU 3 — and GPUs 4-7 are batch workers.
- **LoRA training fits comfortably.** SDXL LoRA at rank 32 needs ~30 GB during training. Any single GPU on this box handles it without breaking a sweat.
- **SVD at 25 frames @ 1024×576 is no problem.** No need to fall back to AnimateDiff-XL — SVD runs natively at full resolution.
- **Batch processing parallelism is real.** A folder of 40 input images × 5 styles = 200 outputs. At 4 GPU workers × 30 sec/image, that's 25 minutes — vs. 100 minutes on a single GPU.

The same Python code runs on AMD Radeon Cloud (single GPU, ~16 GB VRAM) for the final demo — `config/settings.py` auto-detects the device count and gracefully falls back to single-GPU mode.

---

## Week 1 (Jul 16–22) — Build + Train, Zero AMD Credits

**Goal:** Set up env, prepare heritage art datasets, train per-style LoRAs, smoke-test every pipeline end-to-end. By end of Week 1, every line of code is written and tested on real GPU hardware.

### Day-by-day

| Day | Task | Output | GPU-hours |
|---|---|---|---|
| Wed Jul 16 | Run `scripts/day1_setup.sh` — installs PyTorch CUDA, project deps, downloads all v2 models (~35 GB) | Local env ready | 0 |
| Wed Jul 16 | Get AMD Model API key from https://developer.amd.com.cn/radeon/modelapis. Test with curl. Add to `.env`. | Agent API working | 0 |
| Thu Jul 17 | Run `python scripts/verify_rocm.py` — confirm 8 GPUs visible, ~640 GB VRAM. Run `pytest tests/test_agents.py` — confirm agent layer works. | Env verified | 0 |
| Thu Jul 17 | Source 30-50 reference images per heritage style. Place under `assets/datasets/raw/<style>/`. See `assets/styles/README.md` for sources. | Raw dataset (5 × ~40 imgs) | 0 |
| Fri Jul 18 | Run `python training/prepare_dataset.py` — resizes, captions, writes metadata.jsonl. | 5 prepared datasets | 0 |
| Fri Jul 18 | **Train first LoRA** — `python -m training.train_lora --style madhubani --steps 800 --rank 32`. ~30 min on 1 GPU. | `assets/loras/madhubani.safetensors` | 0.5 |
| Sat Jul 19 | Train remaining 4 LoRAs (warli, pattachitra, mughal, tanjore). Run sequentially or in parallel across 5 GPUs. | 5 LoRAs trained | 2.0 |
| Sun Jul 20 | Smoke-test `core/text_to_image.py` with LoRA enabled. Generate 1 image per style. Iterate on prompt engineering if style fidelity is weak. | 5 smoke-test images | 0.5 |
| Sun Jul 20 | Smoke-test `core/style_transfer.py` (IP-Adapter XL). Iterate on `ip_adapter_scale` per style. | 5 styled images | 0.5 |
| Mon Jul 21 | Smoke-test `core/image_to_video.py` (SVD). Generate 1 video per style at 1024×576. | 5 test videos | 1.0 |
| Mon Jul 21 | Smoke-test `core/controlnet.py` and `core/inpainting.py`. One demo each. | 2 demo outputs | 0.5 |
| Tue Jul 22 | Run full `pytest tests/` + UI smoke test (`python app.py`, click through all 6 tabs). Fix bugs. | Tests passing | 0 |

**Week 1 GPU time:** ~5 hours (all free on NVIDIA)
**Week 1 AMD credits used:** 0
**Week 1 commit:** "v2: all 6 pipelines + 5 LoRAs trained + smoke tests passing"

---

## Week 2 (Jul 23–29) — Polish + Pre-bake Demo Assets + Submission Package

**Goal:** Pre-bake every demo output, write the PDF + PPT, run multi-GPU benchmark, freeze code. End of Week 2 = ready for AMD demo recording.

### Day-by-day

| Day | Task | Output | GPU-hours |
|---|---|---|---|
| Wed Jul 23 | Run `python scripts/generate_demo_outputs.py` — produces 45 T2I + 10 styled + 5 videos + 1 inpaint + 1 controlnet = ~62 demo assets. ~30 min on 8×80GB. | `examples/` populated | 0.5 |
| Thu Jul 24 | Curate best outputs. Write captions. Organize into `examples/1_text_to_image/`, `2_style_transfer/`, `3_image_to_video/`. | Curated gallery | 0 |
| Thu Jul 24 | Run `python scripts/benchmark.py --configs 1 2 4 8 --samples 4` — full multi-GPU scaling benchmark. Save JSON + MD + chart. | `outputs/benchmarks/` | 0.5 |
| Fri Jul 25 | Write the README v2 (replace v1). Test that a fresh clone + `pip install -r requirements.txt` + `python app.py` works end-to-end. | README polished | 0 |
| Sat Jul 26 | Write `docs/architecture.md` (already done in this repo). Build architecture diagram via Playwright+CSS. | `docs/architecture_diagram.png` | 0 |
| Sun Jul 27 | Generate the **Project Profile PDF** via the `pdf` skill. Sections: Background, Target Users, Scenarios, Architecture, Model & Algorithm, AMD/ROCm Adaptation, Benchmark, Future Work. Reference pre-baked demo outputs. | `Indic_Heritage_Studio_Profile.pdf` | 0 |
| Mon Jul 28 | Generate the **PPT / poster** via the `pptx` skill. 8-10 slides: Title, Problem, Concept, 5 Heritage Styles, Architecture, Demo Screenshots, AMD Optimization, Benchmark, Future. | `Indic_Heritage_Studio_PPT.pptx` | 0 |
| Tue Jul 29 | Buffer day. Final code review. Commit + push everything to your fork. Code freeze. | Code frozen | 0 |

**Week 2 GPU time:** ~1 hour (all free)
**Week 2 AMD credits used:** 0
**Week 2 commit:** "v2: demo gallery + benchmark + PDF + PPT — ready for AMD demo"

---

## Week 3 (Jul 30–Aug 5) — AMD Verification + Demo Recording + Submit

**Goal:** Burn the minimum AMD credits needed for the rule-compliant demo video and benchmark. Submit.

### Day-by-day

| Day | Task | AMD credits |
|---|---|---|
| Wed Jul 30 | Local: final review of PDF + PPT. Iterate. Practice the demo video script by walking through it on your local UI. | 0 |
| Thu Jul 31 | Local: prep the AMD session — review `scripts/amd_demo_recording.sh`. Test the script logic locally first. | 0 |
| Fri Aug 1 | Local: final check. Commit + push. Make sure the repo is clean. | 0 |
| Sat Aug 2 | Local: prep OBS (or screen recorder). Set up 1920×1080 canvas. Verify audio. | 0 |
| Sun Aug 3 | **AMD instance launch #1 (verification + benchmark, ~30 min):** Launch instance → run `scripts/verify_rocm.py` → run `scripts/benchmark.py --configs 1 --samples 2 --out-dir outputs/benchmarks/amd/` → **DESTROY**. | 0.5 |
| Mon Aug 4 | **AMD instance launch #2 (demo recording, ~60 min):** Launch instance → scp your pre-baked demo assets up (so you don't need to regenerate) → run `scripts/amd_demo_recording.sh` while recording screen with OBS → **DESTROY**. | 1.0 |
| Tue Aug 5 | Local: edit the demo video (trim dead air, add title card). Final code commit. Open PR against `AMD-DEV-CONTEST/Radeon-hackathon-2026-07`. PR title: `Track 1, TeamIndicForge, Indic Heritage Studio`. | 0 |

**Week 3 AMD credits used:** ~1.5
**Cumulative AMD:** 1.5 / 10
**Buffer remaining:** 8.5 credits (for emergencies, re-recording, etc.)

---

## The AMD Demo Recording Session (Aug 4) — Detailed

This is the only session where every minute counts. Pre-stage everything.

### Pre-session prep (do this on Mon Aug 3, locally)

1. Verify `scripts/amd_demo_recording.sh` runs cleanly on the local NVIDIA box (with `nvidia-smi` instead of `rocm-smi`).
2. Pre-stage the `examples/inputs/portrait.jpg` and `examples/inputs/portrait_mask.png` files in your repo.
3. Set up OBS (or your screen recorder) with a 1920×1080 canvas, capturing the terminal + browser side-by-side.
4. Test audio: do a 30-second test recording.

### The session (Aug 4, target 60 minutes)

| Minute | Action | AMD credit |
|---|---|---|
| 0:00 | Launch instance from your template (SSH enabled) | 0 |
| 0:05 | SSH in, `git clone` your fork, `cd` into project | 0 |
| 0:10 | `cp .env.example .env` + paste AMD API key + set `HF_HOME=/workspace/.cache/huggingface` | 0 |
| 0:12 | `pip install -r requirements.txt` (~3 min) | 0 |
| 0:15 | **Optional:** `scp` your local model cache to `/workspace/.cache/huggingface/` to skip download | 0 |
| 0:18 | Run `scripts/verify_rocm.py` — confirm ROCm ready | 0.05 |
| 0:20 | Start OBS recording. Run `scripts/amd_demo_recording.sh`. | (running) |
| 0:50 | Stop recording. Verify video file is good. | 0.7 |
| 0:55 | `scp` outputs and benchmark JSON back to your laptop. **DESTROY INSTANCE**. | (stop clock) |
| 1:00 | Done | **Total: ~0.75** |

### Fallback if demo recording goes wrong

If the AMD instance misbehaves or the video is bad:
- You have 8.5 buffer credits
- Re-launch, re-record — same script
- Worst case, do a "screen recording" of you running the commands locally on the 8×80GB NVIDIA box, but **explicitly state in the video** that the same code runs on AMD (show your `benchmark_amd.json` from Aug 3 as proof)

---

## Risk Register & Contingency

| Risk | Mitigation |
|---|---|
| LoRA training produces weak style fidelity | Increase rank from 32 → 64. Increase steps from 800 → 1500. Add more reference images (50+ per style). |
| SVD video looks too static | Increase `motion_bucket_id` (style-specific in `config/styles.py`). Increase `noise_aug_strength` from 0.02 → 0.05. |
| ControlNet output is too rigid | Lower `controlnet_conditioning_scale` from 0.8 → 0.5. |
| SVD OOMs on AMD (16 GB VRAM) | Set `decode_chunk_size=4` (already done). Reduce frames from 25 → 14. |
| AMD instance unavailable on Aug 4 | Use buffer credits on Aug 5 instead. Submit by Aug 5 night IST. |
| Demo video has bugs | Re-record on Aug 5 with buffer credits. |
| `/workspace` doesn't persist on AMD | Verified on Day 1 (Jul 17 AMD session, 0.5 credits). If broken, scp local cache up each session. |
| You get sick / busy | Submit MVP by Aug 3: code + README + local demo video showing 8×80GB NVIDIA execution + a note that AMD verification is pending. Better than nothing. |

---

## Daily Ritual

Every working day:

1. **Morning (5 min):** Check hackathon Discord (`https://discord.gg/zt9caur5B3`) for announcements.
2. **End of session (5 min):** `git add . && git commit -m "WIP: <what you did>" && git push`. Even incomplete work.
3. **Before destroying AMD instance:** `scp` outputs down to your laptop. Once destroyed, gone.

---

## Deliverables Checklist (Track 1 requirements)

- [ ] **PDF Profile Document** — generated via `pdf` skill in Week 2 (already done)
- [ ] **Source Code** — fork of `AMD-DEV-CONTEST/Radeon-hackathon-2026-07` with `indic-heritage-studio-v2/` folder
- [ ] **README** — env config + startup guide + dependency list (already in repo)
- [ ] **Demo Video (3–5 min)** — recorded on AMD Radeon Cloud Aug 4
- [ ] **PPT / poster** — generated via `pptx` skill in Week 2
- [ ] **Benchmark report** — `outputs/benchmarks/benchmark_<host>_rocm-*.json` + `.md` from Aug 3 AMD session

---

## Definition of Done

Submission is "done" when ALL of the following are true:

- [ ] PR opened against `AMD-DEV-CONTEST/Radeon-hackathon-2026-07`
- [ ] PR title: `Track 1, TeamIndicForge, Indic Heritage Studio`
- [ ] PR contains: source code, README, PDF, PPT, demo video link (or video file in repo)
- [ ] Demo video is 3–5 min, **shows live execution on AMD Radeon GPU** (rocm-smi visible)
- [ ] README has reproducibility instructions (evaluator can clone + run)
- [ ] All 6 modes verified working on AMD (not just locally):
      1. T2I (SDXL + LoRA)
      2. Style transfer (IP-Adapter XL)
      3. Image → Video (SVD)
      4. ControlNet
      5. Inpainting
      6. Batch (multi-GPU)
- [ ] `outputs/benchmarks/benchmark_amd.json` exists and is referenced in the PDF
- [ ] Multi-GPU scaling chart (1 vs 2 vs 4 vs 8 GPUs) included in the PDF — even if from NVIDIA, it's a strong talking point

**Submit by:** Aug 5, 11:59 PM IST (one day before the Aug 6 deadline — buffer for last-minute fixes).