Keep project documentation outside frozen evaluation archives

evaluation/README.md

@@ -25,7 +25,7 @@ The complete benchmark requires `evaluation/index.json` and all 26 archives list
 | File or files | Count | Contents |
 | --- | ---: | --- |
 | `evaluation/index.json` | 1 | Archive inventory and SHA-256 checksums |
-| `evaluation/metadata.tar` | 1 | Portable manifests, original selections, and dataset documentation |
+| `evaluation/metadata.tar` | 1 | Portable manifests, original selections, and source provenance |
 | `evaluation/picasso-00000.tar` | 1 | All 100 PICASSO images, masks, previews, and GT meshes |
 | `evaluation/messykitchen-00001.tar` through `messykitchen-00022.tar` | 22 | All 1,503 MessyKitchens images, masks, previews, and 100 shared GT meshes |
 | `evaluation/3dfront-00023.tar` and `3dfront-00024.tar` | 2 | The selected 1,000 3D-FRONT test images, masks, previews, and GT meshes |
@@ -34,6 +34,11 @@ The downloader restores every archive and checks its checksum.
 Each view requires its RGB image, instance mask, and referenced GT mesh.
 Older project checkouts also require `code/evaluation.patch` before restoration.
 
+The project README stays outside the data archives.
+The Hub stores it separately at `evaluation/README.md`.
+Restoration preserves the local project README, including local edits.
+Metadata archives retain dataset provenance files such as `messykitchen/SOURCE_README.md`.
+
 ## Optional files
 
 These separate Hub components are optional for this benchmark:
@@ -67,16 +72,53 @@ The required evaluation 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.
 
+## Refresh Hub metadata
+
+Use this procedure to remove the project README from an earlier archive.
+The refresh command downloads only the evaluation index and metadata archive.
+It preserves every other member and every data archive record.
+It publishes the project README separately.
+It requires no transfer of image, mask, or mesh archives.
+
+Prepare the update without uploading:
+
+```bash
+python -m preprocess.evaluation refresh-metadata \
+  --output outputs/huggingface/evaluation_metadata
+```
+
+Publish the three prepared metadata files:
+
+```bash
+python -m preprocess.evaluation refresh-metadata \
+  --output outputs/huggingface/evaluation_metadata --upload
+```
+
+The publication uses a pinned parent commit.
+A concurrent Hub change stops the update.
+Archive checksums and existing data checks remain mandatory.
+
+Refresh the task catalog after publication:
+
+```bash
+python -m preprocess.tasks publish --repo cubec/PartProbe3D-preprocessed \
+  --output outputs/huggingface/tasks
+```
+
+The catalog records the current Git revision.
+Use a revision available on the Git remote.
+
 ## Geometry-only inference
 
 The benchmark compares geometry meshes.
 Comparison baselines disable independent appearance decoding, UV generation, and texture baking.
-Geometry checks must confirm unchanged surfaces, object placement, indices, units, and coordinate frames.
+Geometry checks must show unchanged surfaces, object placement, indices, units, and coordinate frames.
 Native geometry settings remain fixed.
 
-Save raw prediction GLBs and their input and model provenance.
-Keep RGB, masks, GT references, shared depth, and scoring results with those predictions.
-These artifacts support additional geometry metrics without repeating inference.
+Save raw prediction GLBs, stable sample identities, the pinned dataset revision, and scoring settings.
+Keep source snapshots, dependency versions, and metric results for portable reevaluation.
+Restore RGB, masks, and GT meshes from the pinned Hub release when required.
+Geometry metric reevaluation needs no model weights or native working files.
 
 ## Read samples
 

evaluation/index.json

@@ -30,10 +30,10 @@
   "archives": [
     {
       "file": "metadata.tar",
-      "bytes": 13086720,
-      "sha256": "89f5bd7e4f42224122cb517d2bcf93f301b1d58e1241316962004b2fb0143164",
-      "identity": "f6f58b739c0892c8771c79da79af51589e8aba907fe0bdc946a517c988fb2c26",
-      "files": 9,
+      "bytes": 13076480,
+      "sha256": "a0b695a62cbc646a5e350482574892dba7fe2a6af75a55c75b194cfdec3d0274",
+      "identity": "853dfc93d9b120e4be2efbc3eb5828d672b4c421597c2fc14b91cd1f978f0c3b",
+      "files": 8,
       "views": 0
     },
     {
@@ -237,7 +237,8 @@
       "views": 449
     }
   ],
-  "bytes": 23404277760,
+  "bytes": 23404267520,
   "archive_prefix": "datasets/evaluation/indoor",
-  "required_for_evaluation": true
+  "required_for_evaluation": true,
+  "project_readme_included": false
 }

evaluation/metadata.tar

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:89f5bd7e4f42224122cb517d2bcf93f301b1d58e1241316962004b2fb0143164
-size 13086720
+oid sha256:a0b695a62cbc646a5e350482574892dba7fe2a6af75a55c75b194cfdec3d0274
+size 13076480