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5c1bb37 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 | # Reproducibility Guide
This guide maps the code release to the experiments in the paper. The primary reproducibility path is Blender indoor; other sources are retained as secondary adapters for robustness checks.
## Primary Asset Requirement
| Source | Expected Input | Primary Command |
| --- | --- | --- |
| Blender indoor | `.blend` scenes | `scripts/run_blender_indoor.sh` |
The repository does not redistribute scene assets. Reviewers can run the no-data smoke test immediately, and can run the full path after mounting local `.blend` scenes.
## Secondary Assets
| Source | Expected Input | Config |
| --- | --- | --- |
| Blender outdoor / generic meshes | `.glb` or `.gltf` | `configs/blender_outdoor.yaml` |
| HM3D | `.glb` or `.gltf` plus optional semantic/navmesh files | `configs/hm3d.yaml` |
| ScanNet++ | `.ply` | `configs/scannetpp.yaml` |
## Building Blocks Available in This Release
| Module | Purpose | Entry Point |
| --- | --- | --- |
| Candidate generation | Phase 1 of §3 — produce \(\mathcal{P}_\varphi\) | `scripts/build_candidates.py` |
| Conflict-aware selection | Phase 2 of §3 — greedy with \(s_t = G_t - \lambda L_t + \beta B_t\) | `scripts/select_views.py` |
| Selected-view rendering | Phase 3 — final ERP render from chosen candidates | `scripts/render_selected.py` |
| Coverage metric | §6.1 high-resolution oracle coverage | `scripts/evaluate_coverage.py` |
| Oracle-gain validation | §6.2 warping vs. pre-render-all comparison | `scripts/evaluate_oracle_gap.py` |
| Quality audit | Appendix F.2 50-frame audit | `scripts/audit_quality.py` |
| Run summarization | Aggregate per-scene `selected_frames.json` into a CSV | `scripts/summarize_blender_indoor_run.py` |
| Audit summarization | Aggregate per-frame audit results into a CSV | `scripts/summarize_quality_audit.py` |
The §6 driver scripts that orchestrate these building blocks across an entire baseline sweep (e.g., the `K\!\in\!\{8,16,24,32\}` table of §6.1, the \(\lambda\) sweep of §6.5, and the four-source benchmark of §6.6) are scheduled to be released alongside the camera-ready paper.
## Minimal Review Run
```bash
bash scripts/run_tiny.sh
```
This validates the Blender-indoor-style metadata format, greedy selection loop, render-output contract, coverage metric, oracle-gap script, and quality audit script — end-to-end without any private scene assets.
## Blender-Indoor Full Run
```bash
DRY_RUN=1 \
BLENDER=/path/to/blender \
INPUT_DIR=/path/to/blend_scenes \
OUTPUT_ROOT=outputs/blender_indoor \
bash scripts/run_blender_indoor.sh
```
After confirming the detected scene list, remove `DRY_RUN=1`:
```bash
BLENDER=/path/to/blender \
INPUT_DIR=/path/to/blend_scenes \
OUTPUT_ROOT=outputs/blender_indoor \
NUM_FRAMES=30 \
RESOLUTION=2048,1024 \
GRID_SPACING=0.5 \
bash scripts/run_blender_indoor.sh
```
## Metric Scripts
The native Blender-indoor pipeline emits `selected_frames.json` under each scene output directory. Summarize a completed run with:
```bash
python3 scripts/summarize_blender_indoor_run.py \
--output-root outputs/blender_indoor \
--output outputs/blender_indoor/results/coverage_main.csv
```
If you have consolidated candidate and selection metadata into the normalized JSONL/JSON contract used by the smoke test, use:
```bash
python3 scripts/evaluate_coverage.py \
--candidates outputs/blender_indoor/metadata/candidates.jsonl \
--selected outputs/blender_indoor/metadata/selected_viewpoints.json \
--output outputs/blender_indoor/results/coverage_main.csv
python3 scripts/evaluate_oracle_gap.py \
--candidates outputs/blender_indoor/metadata/candidates.jsonl \
--selected outputs/blender_indoor/metadata/selected_viewpoints.json \
--output outputs/blender_indoor/results/oracle_validation.csv
python3 scripts/audit_quality.py \
--render-dir outputs/blender_indoor/renders \
--metadata outputs/blender_indoor/metadata/selected_viewpoints.json \
--output outputs/blender_indoor/results/audit_50_frames.csv
```
The exact dataset paths should be adapted to the local machine. Do not commit generated data, logs, checkpoints, third-party repositories, or scene assets to the anonymous code repository.
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