Flatten evaluation dataset layout

README.md

@@ -145,9 +145,9 @@ The prepared data does not replace access agreements for original source assets.
 [Posed object geometry](previews/3dfront/train-geometry.glb)
 
 <!-- partprobe3d-frozen-evaluation:start -->
-## Frozen indoor evaluation
+## Frozen evaluation
 
-The optional [indoor evaluation bundle](optional/evaluation/indoor/README.md) contains 2,603 images with visible masks and GT object meshes.
+The optional [evaluation bundle](optional/evaluation/README.md) contains 2,603 images with visible masks and GT object meshes.
 It includes all 100 PICASSO images, all 1,503 MessyKitchens images, and 1,000 random 3D-FRONT test views.
 The transfer is 23.40 GB.
 MessyKitchens shares 100 GT scene meshes across its views.
@@ -156,6 +156,6 @@ Default training downloads exclude this bundle.
 Apply the loader patch described in the bundle documentation before evaluating its samples.
 
 ```bash
-python -m preprocess.huggingface download --repo cubec/PartProbe3D-preprocessed --dataset indoor --optional evaluation
+python -m preprocess.huggingface download --repo cubec/PartProbe3D-preprocessed --optional evaluation
 ```
 <!-- partprobe3d-frozen-evaluation:end -->

code/evaluation.patch

@@ -231,6 +231,98 @@ index 3968d22..5f985e0 100644
  def collect_runs(run, selection):
      """Collect recorded model outputs and disjoint shards by their method metadata."""
      expected = {frame["key"]: frame for frame in selection["frames"]}
+diff --git a/preprocess/huggingface.py b/preprocess/huggingface.py
+index 2fdce63..df8bdf1 100644
+--- a/preprocess/huggingface.py
++++ b/preprocess/huggingface.py
+@@ -394,9 +394,9 @@ def extract(index, folder, destination):
+     if index.get('schema') != SCHEMA or not index.get('complete'):
+         raise ValueError('A complete archive index is required')
+     folder, destination = Path(folder), Path(destination).resolve()
+-    prefix = _relative(index['destination'])
++    prefix = _relative(index.get('archive_prefix', index['destination']))
+     restored_prefix = (_slat_destination(index['name'], index['resolution'])
+-                       if index.get('artifact_kind') == 'slat-shape-targets' else prefix)
++                       if index.get('artifact_kind') == 'slat-shape-targets' else _relative(index['destination']))
+     # Publish the original complete manifest only after restoring its artifacts.
+     for item in sorted(index['archives'], key=lambda item: item['file'] == 'metadata.tar'):
+         path = folder / _relative(item['file'])
+@@ -563,7 +563,7 @@ def download(repo, name, destination, revision, *, cleanup=None, bundle_root=Non
+     # Keep active training folders free of transfer archives. Retain the legacy
+     # cache path only when an explicit historical component needs resume.
+     cache = (destination / 'datasets' / '_deprecated' / name / 'huggingface'
+-             if bundle_root.startswith(('training/', 'optional/'))
++             if bundle_root.split('/')[0] in ('training', 'optional')
+              else destination / 'datasets' / name / 'archives' / 'huggingface')
+     index_path = hf_hub_download(repo, f'{bundle_root}/{name}/index.json', repo_type='dataset',
+                                  revision=revision, local_dir=cache)
+@@ -894,6 +894,8 @@ def main():
+         if args.optional and args.bundle_root:
+             parser.error('--optional and --bundle-root cannot be combined')
+         bundle_root = f'optional/{args.optional.replace("-", "_")}' if args.optional else args.bundle_root
++        if args.optional == 'evaluation' and args.dataset == 'all':
++            args.dataset, bundle_root = 'evaluation', 'optional'
+         if args.optional and args.dataset == 'all':
+             parser.error('Select one dataset with --dataset for an optional download')
+         cleanup = not args.keep_archives if bundle_root is None or args.optional else args.cleanup
+diff --git a/preprocess/reproduction.py b/preprocess/reproduction.py
+index fd0ccd7..deabce5 100644
+--- a/preprocess/reproduction.py
++++ b/preprocess/reproduction.py
+@@ -180,6 +180,8 @@ def package(root, output, component, name, *, destination, kind, metadata, group
+         raise ValueError(f'Package source changed. Select another output: {component}/{name}')
+     previous = {row['file']: row for row in old.get('archives', [])}
+     index = {'schema': SCHEMA, 'name': name, 'complete': False, **identity, 'archives': []}
++    if 'archive_prefix' in old:
++        index['archive_prefix'] = old['archive_prefix']
+     atomic_json(path, index)
+ 
+     def save(label, files, views):
+@@ -197,7 +199,8 @@ def package(root, output, component, name, *, destination, kind, metadata, group
+         if reusable:
+             record = old_record
+         else:
+-            record = _archive(folder / filename, files, root, Path(destination), old_record, checksums=checksums)
++            record = _archive(folder / filename, files, root,
++                              Path(index.get('archive_prefix', destination)), old_record, checksums=checksums)
+         record['views'] = views
+         index['archives'].append(record)
+         atomic_json(path, index)
+@@ -440,14 +443,15 @@ def _copy_files(api, repo, output, mapping, *, revision=LEGACY_REVISION, remove_
+     return commits
+ 
+ 
+-def export_code(output, base_revision):
+-    """Export only this migration's source changes, preserving unrelated workspace edits."""
++def export_code(output, base_revision, *, tracked=None, added=None, name='reproduction'):
++    """Export selected source changes and preserve unrelated workspace edits."""
+     output = Path(output)
+     folder = output / 'code'
+     folder.mkdir(parents=True, exist_ok=True)
+-    tracked = ['HF_DATASETS.md', 'preprocess/slat/HUGGING_FACE.md', 'preprocess/slat/README.md', 'dataloader/dataset.py',
+-               'dataloader/extent.py', 'preprocess/huggingface.py', 'preprocess/validate_dataset.py']
+-    added = ['preprocess/reproduction.py', 'preprocess/tests/test_reproduction.py']
++    tracked = (['HF_DATASETS.md', 'preprocess/slat/HUGGING_FACE.md', 'preprocess/slat/README.md', 'dataloader/dataset.py',
++                'dataloader/extent.py', 'preprocess/huggingface.py', 'preprocess/validate_dataset.py']
++               if tracked is None else tracked)
++    added = ['preprocess/reproduction.py', 'preprocess/tests/test_reproduction.py'] if added is None else added
+     content = subprocess.check_output(['git', 'diff', '--binary', base_revision, '--', *tracked, *added])
+     for path in added:
+         present = subprocess.run(['git', 'cat-file', '-e', f'{base_revision}:{path}'],
+@@ -461,11 +465,11 @@ def export_code(output, base_revision):
+         if result.returncode not in (0, 1):
+             raise RuntimeError(f'Cannot export restore source: {path}')
+         content += result.stdout
+-    patch = folder / 'reproduction.patch'
++    patch = folder / f'{name}.patch'
+     patch.write_bytes(content)
+     manifest = {'base_git_revision': base_revision, 'patch_sha256': sha256(patch),
+                 'files': {path: sha256(path) for path in [*tracked, *added]}}
+-    atomic_json(folder / 'manifest.json', manifest)
++    atomic_json(folder / ('manifest.json' if name == 'reproduction' else f'{name}_manifest.json'), manifest)
+     return manifest
+ 
+ 
 diff --git a/dataloader/frozen.py b/dataloader/frozen.py
 new file mode 100644
 index 0000000..2a43518
@@ -313,7 +405,7 @@ index 0000000..2a43518
 +                'source_dataset': self.manifest['source_dataset'], 'gt_representation': 'exported GLB float32'}
 diff --git a/preprocess/evaluation.py b/preprocess/evaluation.py
 new file mode 100644
-index 0000000..8f6dd03
+index 0000000..abe6e3b
 --- /dev/null
 +++ b/preprocess/evaluation.py
 @@ -0,0 +1,171 @@
@@ -434,7 +526,7 @@ index 0000000..8f6dd03
 +    output.mkdir(parents=True, exist_ok=True)
 +    publisher = Publisher(repo, workers=workers)
 +    result = {'repo': repo, 'complete': False, 'total_views': cohort['total_views'],
-+              'component': 'optional/evaluation/indoor', 'datasets': cohort['datasets']}
++              'component': 'optional/evaluation', 'datasets': cohort['datasets']}
 +    atomic_json(output / 'status.json', result)
 +    metadata = [source / 'index.json', *sorted(source.glob('*.md'))]
 +    groups, checksums = [], {}
@@ -453,8 +545,8 @@ index 0000000..8f6dd03
 +        metadata.extend([root / 'manifest.json', root / 'source_selection.json', *sorted(root.glob('*.md'))])
 +        groups.extend((name, sorted(paths), counts[scene]) for scene, paths in sorted(scenes.items()))
 +        checksums.update({artifact_path(root, key): value for key, value in manifest['files'].items()})
-+    index = package(source, output, 'optional/evaluation', 'indoor',
-+        destination=Path('datasets/evaluation/indoor'), kind='frozen-evaluation',
++    index = package(source, output, 'optional', 'evaluation',
++        destination=Path('datasets/evaluation'), kind='frozen-evaluation',
 +        metadata=metadata, groups=groups, checksums=checksums,
 +        details={'source_manifest_sha256': sha256(source / 'index.json'), 'views': cohort['total_views'],
 +                 'datasets': cohort['datasets'], 'evaluation_only': True},
@@ -470,10 +562,10 @@ index 0000000..8f6dd03
 +    commands = parser.add_subparsers(dest='command', required=True)
 +    staging = commands.add_parser('store')
 +    staging.add_argument('--source', type=Path, required=True)
-+    staging.add_argument('--destination', type=Path, default=Path('datasets/evaluation/indoor'))
++    staging.add_argument('--destination', type=Path, default=Path('datasets/evaluation'))
 +    staging.add_argument('--workers', type=int, default=4)
 +    publishing = commands.add_parser('publish')
-+    publishing.add_argument('--source', type=Path, default=Path('datasets/evaluation/indoor'))
++    publishing.add_argument('--source', type=Path, default=Path('datasets/evaluation'))
 +    publishing.add_argument('--output', type=Path, default=Path('outputs/huggingface/evaluation'))
 +    publishing.add_argument('--repo', default=DEFAULT_REPO)
 +    publishing.add_argument('--workers', type=int, default=4)
@@ -490,28 +582,28 @@ index 0000000..8f6dd03
 +    main()
 diff --git a/evaluation/configs/picasso_frozen.json b/evaluation/configs/picasso_frozen.json
 new file mode 100644
-index 0000000..5c472dc
+index 0000000..7d85ea9
 --- /dev/null
 +++ b/evaluation/configs/picasso_frozen.json
 @@ -0,0 +1,3 @@
 +{
-+  "root": "datasets/evaluation/indoor/picasso"
++  "root": "datasets/evaluation/picasso"
 +}
 diff --git a/evaluation/configs/messykitchen_frozen.json b/evaluation/configs/messykitchen_frozen.json
 new file mode 100644
-index 0000000..0191781
+index 0000000..2bf4e4b
 --- /dev/null
 +++ b/evaluation/configs/messykitchen_frozen.json
 @@ -0,0 +1,3 @@
 +{
-+  "root": "datasets/evaluation/indoor/messykitchen"
++  "root": "datasets/evaluation/messykitchen"
 +}
 diff --git a/evaluation/configs/front3d_frozen.json b/evaluation/configs/front3d_frozen.json
 new file mode 100644
-index 0000000..6087592
+index 0000000..c84bba7
 --- /dev/null
 +++ b/evaluation/configs/front3d_frozen.json
 @@ -0,0 +1,3 @@
 +{
-+  "root": "datasets/evaluation/indoor/3dfront"
++  "root": "datasets/evaluation/3dfront"
 +}

code/evaluation_manifest.json

@@ -1,15 +1,17 @@
 {
   "base_git_revision": "290027fe9f281a21db978a48da21bb9be90e5517",
-  "patch_sha256": "02a780a4df7abbfb37090beb86664d026b4dcc0d945fc7927a8621d4bf2d7fd0",
+  "patch_sha256": "4f5c19b5f257d3b99a8a423fca841de85f551d71de04af5b7d80c4a7a1673698",
   "files": {
     "dataloader/registry.py": "97690914f4c50c9f7d31213bb9dab174bc740cdd62bf7b217ccfe456b6b387e7",
     "evaluation/artifacts.py": "232f1b6ffd0374813ea93857ecb378c317a962b2bfbbb4cce0fd7d28e88fe12c",
     "evaluation/evaluate.py": "3d9115be9eb34e1e6193a31f3fb4e5bf770f60b70701dbf7d67017376b87ed17",
     "evaluation/workflows.py": "0623408a288a31d5502531f377c5492b985b5dc69429858d21180eaf0b06d2ba",
+    "preprocess/huggingface.py": "c747bf74aaa8ac262cfd5459199cba08e4fe574b1d5bae830dccb3abaa36398f",
+    "preprocess/reproduction.py": "7f5a50c5dfac603ab529ee4a4aab9a60a5aad8f748dfa03bfa270db0e233c069",
     "dataloader/frozen.py": "5efdb2209519d556f363599226d0d511de14009529899813b48a5574432bc508",
-    "preprocess/evaluation.py": "e6c72bb985e38e219885db4dbc2c68d31c5f6dcac2a8c0f9fcd37aa86565ba19",
-    "evaluation/configs/picasso_frozen.json": "39a3bbd78f4a5014624c8a190669154a52013af374bbdd2253d549ff981dab2b",
-    "evaluation/configs/messykitchen_frozen.json": "5a8559c3fb7214dd44bc4918d30f580ef7ff18afbdde169f25bdc2710a00b262",
-    "evaluation/configs/front3d_frozen.json": "2a30f9abc55b3185e0bae28940766bc672a0710807a536fe9696d3ccd0882c2e"
+    "preprocess/evaluation.py": "3e3b826fc5f9a50dd0e5c85a4094ec60ae17b397b357d9800516a65ea1615b3e",
+    "evaluation/configs/picasso_frozen.json": "5e691ad4b2266fb16f43c24c548a98bf3b68f139d471b956a36d0996a5b6492b",
+    "evaluation/configs/messykitchen_frozen.json": "b85423fbc37b16d64b57da59cb6bbde41194c1bf39cd065e72f7203f9f223a46",
+    "evaluation/configs/front3d_frozen.json": "661d67d3ba5f2a6a40f7dfbdbc5075e6f200ab14f94c8c90be0f8d285a54a07f"
   }
 }

optional/evaluation/{indoor/README.md → README.md}

@@ -1,4 +1,4 @@
-# PartProbe3D frozen indoor evaluation
+# PartProbe3D frozen evaluation
 
 This bundle contains 2,603 single-image evaluation samples and their GT object meshes.
 It requires about 23.4 GB, including RGB images, visible masks, previews, and shared geometry.
@@ -25,11 +25,11 @@ hf download cubec/PartProbe3D-preprocessed code/evaluation.patch --repo-type dat
 git apply --check outputs/huggingface/bootstrap/code/evaluation.patch
 git apply outputs/huggingface/bootstrap/code/evaluation.patch
 python -m pip install -e '.[preprocess]'
-python -m preprocess.huggingface download --repo cubec/PartProbe3D-preprocessed --dataset indoor --optional evaluation
+python -m preprocess.huggingface download --repo cubec/PartProbe3D-preprocessed --optional evaluation
 ```
 
 The downloader pins one Hub revision and verifies every archive checksum before restoration.
-The optional bundle restores to `datasets/evaluation/indoor/`.
+The optional bundle restores to `datasets/evaluation/`.
 Default training downloads exclude this bundle.
 The source manifest at `code/evaluation_manifest.json` records the loader files and patch checksum.
 
@@ -38,7 +38,7 @@ The source manifest at `code/evaluation_manifest.json` records the loader files
 ```python
 from dataloader.frozen import FrozenEvaluationLoader
 
-dataset = FrozenEvaluationLoader('datasets/evaluation/indoor/messykitchen')
+dataset = FrozenEvaluationLoader('datasets/evaluation/messykitchen')
 sample = dataset[0]
 rgb, masks, meshes = sample.rgb, sample.masks, sample.gt_meshes
 ```

optional/evaluation/{indoor/index.json → index.json}

@@ -1,8 +1,8 @@
 {
   "schema": "partprobe3d.hub-archives.v1",
-  "name": "indoor",
+  "name": "evaluation",
   "complete": true,
-  "destination": "datasets/evaluation/indoor",
+  "destination": "datasets/evaluation",
   "artifact_kind": "frozen-evaluation",
   "source_manifest_sha256": "f4c0dce6c5b4839f70e8a36ce66df00a743dc6b4c531b59071f7603137f5fe8d",
   "views": 2603,
@@ -31,8 +31,8 @@
     {
       "file": "metadata.tar",
       "bytes": 13086720,
-      "sha256": "bf1638f44b51249d3f46cc33c839cecb27bc031dea490af621a1db1947776ca2",
-      "identity": "4037de22399c3e9b3fd8b4d35569bcc48a332331af5aae52411651985118fea6",
+      "sha256": "1fe0fb12ecbac88f325b161e3bd5479247a440dfe35fdcdbe89a8bb148932849",
+      "identity": "7293a27f5a6c5076c4be6deff6915409a3040040c2a1af10b8ae7ea6914799f8",
       "files": 9,
       "views": 0
     },
@@ -237,5 +237,6 @@
       "views": 449
     }
   ],
-  "bytes": 23404277760
+  "bytes": 23404277760,
+  "archive_prefix": "datasets/evaluation/indoor"
 }

optional/evaluation/{indoor/metadata.tar → metadata.tar}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:bf1638f44b51249d3f46cc33c839cecb27bc031dea490af621a1db1947776ca2
+oid sha256:1fe0fb12ecbac88f325b161e3bd5479247a440dfe35fdcdbe89a8bb148932849
 size 13086720

training/index.json

@@ -85,8 +85,8 @@
       "component": "optional/evaluation/ycbv",
       "bytes": 1669857280
     },
-    "evaluation/indoor": {
-      "component": "optional/evaluation/indoor",
+    "evaluation": {
+      "component": "optional/evaluation",
       "bytes": 23404277760,
       "views": 2603,
       "datasets": {