Copy public roots without spaces (44/44)

.gitattributes

@@ -28706,3 +28706,5 @@ Assets/PhysicBenchmark/Content/__ExternalActors__/PhysicsScenario/Levels/buildin
 Assets/PhysicBenchmark/Content/__ExternalActors__/PhysicsScenario/Levels/building/E/UG/HF2YMAZF89GZ7RY1VIET2I.uasset filter=lfs diff=lfs merge=lfs -text
 Assets/PhysicBenchmark/Content/__ExternalActors__/PhysicsScenario/Levels/building/E/YX/MBPW1J1NZHR5LXZZK2W1EL.uasset filter=lfs diff=lfs merge=lfs -text
 Assets/PhysicBenchmark/Content/__ExternalActors__/deformable/5/3J/RJQ0J1N13LMCBW5ROJ8M8F.uasset filter=lfs diff=lfs merge=lfs -text
+Utils/leaderboard_lists/video-generation.txt filter=lfs diff=lfs merge=lfs -text
+Utils/metadata/repo_assignment.txt filter=lfs diff=lfs merge=lfs -text

Assets/PhysicBenchmark/PhysInOne.uproject

@@ -0,0 +1,59 @@
+{
+	"FileVersion": 3,
+	"EngineAssociation": "5.5",
+	"Category": "",
+	"Description": "",
+	"Plugins": [
+		{
+			"Name": "ModelingToolsEditorMode",
+			"Enabled": true,
+			"TargetAllowList": [
+				"Editor"
+			]
+		},
+		{
+			"Name": "ChaosModularVehicle",
+			"Enabled": true
+		},
+		{
+			"Name": "ChaosModularVehicleExamples",
+			"Enabled": true
+		},
+		{
+			"Name": "ChaosVehiclesPlugin",
+			"Enabled": true
+		},
+		{
+			"Name": "JsonBlueprintUtilities",
+			"Enabled": true
+		},
+		{
+			"Name": "MovieRenderPipeline",
+			"Enabled": true
+		},
+		{
+			"Name": "MoviePipelineMaskRenderPass",
+			"Enabled": true
+		},
+		{
+			"Name": "GeometryScripting",
+			"Enabled": true
+		},
+		{
+			"Name": "PythonFoundationPackages",
+			"Enabled": true
+		},
+		{
+			"Name": "PCG",
+			"Enabled": true
+		},
+		{
+			"Name": "PCGBiomeCore",
+			"Enabled": true
+		},
+		{
+			"Name": "PCGBiomeSample",
+			"Enabled": true
+		}
+	]
+}

Utils/3D_ASSETS_DOWNLOAD.md

@@ -0,0 +1,215 @@
+# PhysInOne Validation 3D Assets
+
+This guide explains how to download, extract, and open the public PhysInOne
+validation 3D asset release. The release contains the Unreal Engine project
+files and validation resources for 1,000 scenes.
+
+Repository location:
+
+[`3D Assets/PhysicBenchmark`](https://huggingface.co/datasets/vLAR/PhysInOne/tree/main/3D%20Assets/PhysicBenchmark)
+
+## Requirements
+
+- Unreal Engine **5.5.4**
+- Python 3.9 or newer for the automated downloader
+- `huggingface_hub`; `tqdm` is recommended for progress display
+- At least **50–60 GiB of free disk space** when keeping both ZIP files and
+  extracted assets
+
+Windows is recommended for the simplest Unreal Engine setup. Linux is also
+supported, but Unreal Engine installation, platform plugins, permissions, and
+case-sensitive paths may require additional configuration.
+
+## Automated setup
+
+Install the Python dependencies:
+
+```bash
+pip install -U huggingface_hub tqdm
+```
+
+Download the script, release lists, and this guide:
+
+```bash
+hf download vLAR/PhysInOne \
+  "PhysInOne Utils/scripts/download_3d_assets.py" \
+  "PhysInOne Utils/3d_assets_lists/validation.txt" \
+  "PhysInOne Utils/3d_assets_lists/validation_archives.txt" \
+  "PhysInOne Utils/3d_assets_lists/summary.json" \
+  "PhysInOne Utils/3D_ASSETS_DOWNLOAD.md" \
+  --repo-type dataset \
+  --local-dir .
+```
+
+Run the downloader:
+
+```bash
+python "PhysInOne Utils/scripts/download_3d_assets.py" \
+  --output-dir ./PhysInOne-3D-Assets
+```
+
+The default command performs all of the following:
+
+1. Downloads the exact validation release file list.
+2. Preserves the Hugging Face repository hierarchy.
+3. Validates ZIP paths and rejects unsafe archive members.
+4. Extracts all eight ZIP files into their correct parent directories.
+5. Merges scene and trajectory batches without overwriting different files.
+6. Writes resumable extraction markers and detailed success/failure logs.
+
+After completion, the Unreal Engine project root is:
+
+```text
+PhysInOne-3D-Assets/3D Assets/PhysicBenchmark/
+```
+
+Open the project with Unreal Engine 5.5.4 by launching:
+
+```text
+PhysInOne-3D-Assets/3D Assets/PhysicBenchmark/PhysInOne.uproject
+```
+
+## Download without extraction
+
+To download the released files but keep every archive compressed:
+
+```bash
+python "PhysInOne Utils/scripts/download_3d_assets.py" \
+  --output-dir ./PhysInOne-3D-Assets \
+  --no-extract
+```
+
+You can run the default command later with the same output directory to extract
+the archives.
+
+## Save disk space
+
+To delete each ZIP only after it has been completely extracted and verified:
+
+```bash
+python "PhysInOne Utils/scripts/download_3d_assets.py" \
+  --output-dir ./PhysInOne-3D-Assets \
+  --delete-zip-after-extract
+```
+
+Completion markers prevent successfully extracted and deleted archives from
+being downloaded again when the same command is resumed. Do not delete the
+`.physinone_extract_status/` directories if this behavior is required.
+
+## Release contents
+
+The current validation release contains:
+
+- 4,299 downloadable files
+- 8 ZIP archives
+- Approximately 22.25 GiB of downloaded data
+- Scene and trajectory resources for 1,000 validation scenes
+- Shared Unreal Engine project content and dependencies required by the release
+
+The exact maintained lists are available here:
+
+- [`validation.txt`](https://huggingface.co/datasets/vLAR/PhysInOne/blob/main/PhysInOne%20Utils/3d_assets_lists/validation.txt): every released file
+- [`validation_archives.txt`](https://huggingface.co/datasets/vLAR/PhysInOne/blob/main/PhysInOne%20Utils/3d_assets_lists/validation_archives.txt): the eight archives that must be extracted
+- [`summary.json`](https://huggingface.co/datasets/vLAR/PhysInOne/blob/main/PhysInOne%20Utils/3d_assets_lists/summary.json): release counts and byte sizes
+
+This is a validation release. The full training asset archives are not included
+in this download list.
+
+## Archives and extraction destinations
+
+Every ZIP must be extracted **in place**, meaning into the ZIP's current parent
+directory. Do not extract all archives into one common folder.
+
+| Archive, relative to `PhysicBenchmark/` | Extract in |
+| --- | --- |
+| `Content/PhysInOne/BackGrounds_raw/Val.zip` | `Content/PhysInOne/BackGrounds_raw/` |
+| `Content/PhysInOne/BreakableObjects/Val.zip` | `Content/PhysInOne/BreakableObjects/` |
+| `Content/PhysInOne/InteractableObjects/Val.zip` | `Content/PhysInOne/InteractableObjects/` |
+| `Content/PhysInOne/MaterialsAppearance/Val.zip` | `Content/PhysInOne/MaterialsAppearance/` |
+| `Content/PhysInOne/MaterialsPhysics/Val.zip` | `Content/PhysInOne/MaterialsPhysics/` |
+| `Content/PhysInOne/SolidObjects/Val.zip` | `Content/PhysInOne/SolidObjects/` |
+| `Content/PhysInOne/Scenes/val_scenes_batch_0000.zip` | `Content/PhysInOne/Scenes/` |
+| `Content/PhysInOne/Trajectories/val_trajectory_batch_0000.zip` | `Content/PhysInOne/Trajectories/` |
+
+The six `Val.zip` archives contain a top-level `Val/` folder. The scene and
+trajectory batch archives also contain paths beginning with `Val/`. Extracting
+each archive into its listed parent produces the correct Unreal Engine content
+layout.
+
+## Expected project structure
+
+After extraction, preserve the directory names and hierarchy exactly. In
+particular, do not rename `BackGrounds_raw`, `__ExternalActors__`, or
+`__ExternalObjects__`.
+
+```text
+PhysicBenchmark/
+├── PhysInOne.uproject
+├── Config/
+├── DerivedDataCache/
+└── Content/
+    ├── Collections/
+    ├── Ice/
+    ├── StarterContent/
+    ├── __ExternalActors__/
+    ├── __ExternalObjects__/
+    └── PhysInOne/
+        ├── Backgrounds/
+        ├── BackGrounds_raw/
+        │   └── Val/
+        ├── BreakableObjects/
+        │   └── Val/
+        ├── InteractableObjects/
+        │   └── Val/
+        ├── MaterialsAppearance/
+        │   └── Val/
+        ├── MaterialsPhysics/
+        │   └── Val/
+        ├── Microsoft/
+        ├── SolidObjects/
+        │   └── Val/
+        ├── Scenes/
+        │   └── Val/
+        └── Trajectories/
+            └── Val/
+```
+
+Unreal Engine resolves content by project-relative package paths. Changing this
+layout can cause missing asset references or prevent levels from loading.
+
+## Resume and logs
+
+The downloader is safe to run again with the same output directory. Completed
+downloads are reused by `huggingface_hub`, existing identical extracted files
+are retained, and archives with complete markers are skipped.
+
+Logs are written to:
+
+```text
+<output-dir>/_3d_asset_download_logs/YYYYMMDD_HHMMSS/
+├── downloads.tsv
+├── extraction.tsv
+├── failures.tsv
+├── events.jsonl
+└── summary.json
+```
+
+If a run is interrupted, execute the same command again and review
+`failures.tsv` and `summary.json` after completion.
+
+For a slower or rate-limited network, reduce concurrency:
+
+```bash
+python "PhysInOne Utils/scripts/download_3d_assets.py" \
+  --output-dir ./PhysInOne-3D-Assets \
+  --workers 2
+```
+
+Public downloads do not require authentication. Do not place access credentials
+in source code, shared shell scripts, commands, or download logs.
+
+## Contact
+
+For setup questions, contact Siyuan Zhou at
+`siyuan.zhou@connect.polyu.hk`. WeChat: `aify20001009`.
+

Utils/3d_assets_lists/summary.json

@@ -0,0 +1,10 @@
+{
+  "bytes": 23895880477,
+  "files": 4299,
+  "release": "validation",
+  "remote_root": "3D Assets/PhysicBenchmark",
+  "repo_id": "vLAR/PhysInOne",
+  "scenes": 1000,
+  "zip_bytes": 21249298639,
+  "zip_files": 8
+}

Utils/3d_assets_lists/validation_archives.txt

@@ -0,0 +1,8 @@
+3D Assets/PhysicBenchmark/Content/PhysInOne/BackGrounds_raw/Val.zip
+3D Assets/PhysicBenchmark/Content/PhysInOne/BreakableObjects/Val.zip
+3D Assets/PhysicBenchmark/Content/PhysInOne/InteractableObjects/Val.zip
+3D Assets/PhysicBenchmark/Content/PhysInOne/MaterialsAppearance/Val.zip
+3D Assets/PhysicBenchmark/Content/PhysInOne/MaterialsPhysics/Val.zip
+3D Assets/PhysicBenchmark/Content/PhysInOne/Scenes/val_scenes_batch_0000.zip
+3D Assets/PhysicBenchmark/Content/PhysInOne/SolidObjects/Val.zip
+3D Assets/PhysicBenchmark/Content/PhysInOne/Trajectories/val_trajectory_batch_0000.zip

Utils/LEADERBOARD_DOWNLOAD.md

@@ -0,0 +1,216 @@
+# PhysInOne Leaderboard Evaluation Data
+
+This guide explains how to download the public evaluation data for all four
+PhysInOne Leaderboard tasks:
+
+- Video Generation
+- Future Prediction
+- Physical Properties Estimation
+- Motion Transfer
+
+The data is hosted in the public
+[`vLAR/PhysInOne`](https://huggingface.co/datasets/vLAR/PhysInOne) dataset
+repository under [`Leaderboard/`](https://huggingface.co/datasets/vLAR/PhysInOne/tree/main/Leaderboard).
+No Hugging Face access token is required for public downloads.
+
+## Install
+
+Python 3.9 or newer is recommended.
+
+```bash
+pip install -U huggingface_hub tqdm
+```
+
+Download the utility script:
+
+```bash
+hf download vLAR/PhysInOne \
+  "PhysInOne Utils/scripts/download_leaderboard.py" \
+  --repo-type dataset \
+  --local-dir .
+```
+
+The Python script automatically fetches the required task manifest from the
+public Hugging Face repository for the selected `--task` and `--revision`. You
+do not need to download any TXT manifest files manually.
+
+## Quick start
+
+Run these commands from the directory containing the downloaded
+`PhysInOne Utils/` folder.
+
+Download all four tasks:
+
+```bash
+python "PhysInOne Utils/scripts/download_leaderboard.py" \
+  --task all \
+  --output-dir ./PhysInOne-Leaderboard
+```
+
+Download one task:
+
+```bash
+python "PhysInOne Utils/scripts/download_leaderboard.py" \
+  --task future-prediction \
+  --output-dir ./PhysInOne-Leaderboard
+```
+
+Download multiple tasks in one run:
+
+```bash
+python "PhysInOne Utils/scripts/download_leaderboard.py" \
+  --task video-generation motion-transfer \
+  --output-dir ./PhysInOne-Leaderboard
+```
+
+## Task names and file lists
+
+For each selected task, the downloader automatically fetches a maintained TXT
+manifest containing one exact repository file path per line. It uses that
+manifest instead of scanning or downloading unrelated parts of the large
+PhysInOne repository. The links below are provided for inspection and
+reproducibility; manual manifest downloads are not required.
+
+| `--task` value | Repository directory | Maintained file list |
+| --- | --- | --- |
+| `video-generation` | `Leaderboard/Video Generation/` | [`video-generation.txt`](https://huggingface.co/datasets/vLAR/PhysInOne/blob/main/PhysInOne%20Utils/leaderboard_lists/video-generation.txt) |
+| `future-prediction` | `Leaderboard/Future Prediction/` | [`future-prediction.txt`](https://huggingface.co/datasets/vLAR/PhysInOne/blob/main/PhysInOne%20Utils/leaderboard_lists/future-prediction.txt) |
+| `physical-properties-estimation` | `Leaderboard/Physical Properties Estimation/` | [`physical-properties-estimation.txt`](https://huggingface.co/datasets/vLAR/PhysInOne/blob/main/PhysInOne%20Utils/leaderboard_lists/physical-properties-estimation.txt) |
+| `motion-transfer` | `Leaderboard/Motion Transfer/` | [`motion-transfer.txt`](https://huggingface.co/datasets/vLAR/PhysInOne/blob/main/PhysInOne%20Utils/leaderboard_lists/motion-transfer.txt) |
+
+Use `--list-only` to print the selected remote paths without downloading data:
+
+```bash
+python "PhysInOne Utils/scripts/download_leaderboard.py" \
+  --task motion-transfer \
+  --list-only
+```
+
+Use `--dry-run` to show the number of selected files:
+
+```bash
+python "PhysInOne Utils/scripts/download_leaderboard.py" \
+  --task all \
+  --dry-run
+```
+
+## Download individual scenes
+
+`--scene` performs a case-insensitive substring match against repository paths.
+It accepts a complete scene name or the unique six-character scene ID and can
+be repeated.
+
+```bash
+python "PhysInOne Utils/scripts/download_leaderboard.py" \
+  --task future-prediction \
+  --scene yUlWPB \
+  --output-dir ./PhysInOne-Leaderboard
+```
+
+```bash
+python "PhysInOne Utils/scripts/download_leaderboard.py" \
+  --task motion-transfer \
+  --scene B15ta6 \
+  --scene 7omQio \
+  --output-dir ./PhysInOne-Leaderboard
+```
+
+## ZIP extraction
+
+By default, archives remain compressed. This saves disk space and preserves the
+exact released artifacts. Add `--extract` to validate each ZIP with a CRC check
+and safely extract it next to the archive:
+
+```bash
+python "PhysInOne Utils/scripts/download_leaderboard.py" \
+  --task physical-properties-estimation \
+  --output-dir ./PhysInOne-Leaderboard \
+  --extract
+```
+
+To remove an archive after successful extraction, explicitly add
+`--delete-zip-after-extract`:
+
+```bash
+python "PhysInOne Utils/scripts/download_leaderboard.py" \
+  --task future-prediction \
+  --output-dir ./PhysInOne-Leaderboard \
+  --extract \
+  --delete-zip-after-extract
+```
+
+Allow enough free space before extracting. Keeping both a ZIP and its extracted
+contents can temporarily require approximately twice the archive's disk space.
+
+## Released contents
+
+### Video Generation
+
+Each scene directory contains the first RGB frame from the selected static
+camera, the first RGB frame from the moving camera, the two corresponding
+Blender camera JSON files, and `caption.txt`.
+
+### Future Prediction
+
+Each scene ZIP contains only fixed training views. It includes RGB frames
+`0000.jpg` through `0074.jpg` and the three split descriptions
+`transforms_train.json`, `transforms_val.json`, and `transforms_test.json`.
+Novel views and `CineCamera_Moving` are excluded from these public inputs.
+
+### Physical Properties Estimation
+
+Each scene ZIP contains background images for novel views; background, RGB, and
+segmentation data for training views; camera JSON files for cameras 0 through
+14; `particle_materials.json`; and `recorder_stats.json`. Novel views are
+selected from each scene's transform metadata rather than assumed to have fixed
+camera indices. Shared supplementary resources are stored under
+`test_supp_info/`.
+
+### Motion Transfer
+
+Each scene ZIP contains source-video RGB frames, the first reference frame for
+the target/origin scene, and `caption.txt`, organized by the two selected camera
+views.
+
+## Output layout
+
+The downloader preserves the repository hierarchy:
+
+```text
+PhysInOne-Leaderboard/
+├── Leaderboard/
+│   ├── Video Generation/
+│   ├── Future Prediction/
+│   ├── Physical Properties Estimation/
+│   └── Motion Transfer/
+└── _download_logs/
+    └── YYYYMMDD_HHMMSS/
+        ├── success.tsv
+        ├── failures.tsv
+        ├── events.jsonl
+        └── summary.json
+```
+
+Hugging Face may also create a hidden local cache/metadata directory inside the
+output root. It is used to resume and avoid redundant transfers.
+
+## Resume and troubleshooting
+
+Downloads are handled by `huggingface_hub`. Re-running the same command reuses
+the local Hugging Face metadata and cache, so completed files are not downloaded
+again unnecessarily. Review `failures.tsv` after each run and repeat the same
+command to retry failed files.
+
+The default is four concurrent downloads. For a slow or rate-limited network,
+reduce concurrency:
+
+```bash
+python "PhysInOne Utils/scripts/download_leaderboard.py" \
+  --task all \
+  --output-dir ./PhysInOne-Leaderboard \
+  --workers 2
+```
+
+Public downloads do not require authentication. Do not place access tokens in
+source code, shared shell scripts, commands, or download logs.
+

Utils/leaderboard_lists/future-prediction.txt

@@ -0,0 +1,103 @@
+Leaderboard/Future Prediction/DoublePhysics/AccelConcaveSpin_AccelSurfaceSpin__bg280__yUlWPB_trajectory.zip
+Leaderboard/Future Prediction/DoublePhysics/AccelPanelSpin_BalloonFloat__bg202__mZuITT_trajectory.zip
+Leaderboard/Future Prediction/DoublePhysics/BalloonLift_ChainSuspend__bg267__m1Cqz7_trajectory.zip
+Leaderboard/Future Prediction/DoublePhysics/BalloonTether_BlockWallCollapse__bg227__74YCgm_trajectory.zip
+Leaderboard/Future Prediction/DoublePhysics/CatapultLaunch_StickSupportFail__bg204__ulAbpI_trajectory.zip
+Leaderboard/Future Prediction/DoublePhysics/DynMirrorRedirect_MirrorReflect__bg264__NxPd1o_trajectory.zip
+Leaderboard/Future Prediction/DoublePhysics/ElasticCouple_CartMove__bg253__GSA6mr_trajectory.zip
+Leaderboard/Future Prediction/DoublePhysics/ElasticFall_PlasticineFall__bg852__2QHJQg_trajectory.zip
+Leaderboard/Future Prediction/DoublePhysics/FixedArrayRedirect_FixedConcaveRedirect__bg210__L2y3J0_trajectory.zip
+Leaderboard/Future Prediction/DoublePhysics/FixedConvexRedirect_RotBoardInertia__bg234__fT2JKm_trajectory.zip
+Leaderboard/Future Prediction/DoublePhysics/FixedPlanarRedirect_LaserBlock__bg299__TfT2x2_trajectory.zip
+Leaderboard/Future Prediction/DoublePhysics/FloatOnLiquid_DropInLiquid__bg509__lRK4PA_trajectory.zip
+Leaderboard/Future Prediction/DoublePhysics/FrictionStop_CrankPush__bg261__iFf7zo_trajectory.zip
+Leaderboard/Future Prediction/DoublePhysics/ImpactFracture_DoublePendulum__bg215__RErDnS_trajectory.zip
+Leaderboard/Future Prediction/DoublePhysics/LinCarryInertia_SimplePendulum__bg294__Ty0PCX_trajectory.zip
+Leaderboard/Future Prediction/DoublePhysics/LiquidMultiTransfers_LiquidRise__bg544__WYOBHP_trajectory.zip
+Leaderboard/Future Prediction/DoublePhysics/LiquidThroughGrid_StickyToObjects__bg670__EAVM3Z_trajectory.zip
+Leaderboard/Future Prediction/DoublePhysics/MagnetAttract_MagnetRepel__bg265__rel0pp_trajectory.zip
+Leaderboard/Future Prediction/DoublePhysics/MirrorFragmentReflect_RotTurnableInertia__bg286__yAEdAd_trajectory.zip
+Leaderboard/Future Prediction/DoublePhysics/MovingHitsFixed_WindGravityBalance__bg299__l185PI_trajectory.zip
+Leaderboard/Future Prediction/DoublePhysics/MovingHitsFixed_WindPushStationary__bg298__ifDc18_trajectory.zip
+Leaderboard/Future Prediction/DoublePhysics/MovingHitsStationary_MovingHitsMoving__bg242__CrPMCl_trajectory.zip
+Leaderboard/Future Prediction/DoublePhysics/MovingObjDriveLiquid_LiquidTransfer__bg596__hjv8Xm_trajectory.zip
+Leaderboard/Future Prediction/DoublePhysics/NewtonianFluidFall_GranularFall__bg851__3GTIkU_trajectory.zip
+Leaderboard/Future Prediction/DoublePhysics/ObliqueProjectile_RollDownSlope__bg250__s663ZS_trajectory.zip
+Leaderboard/Future Prediction/DoublePhysics/RollUpSlope_AccelPanelSpin__bg256__ied5pR_trajectory.zip
+Leaderboard/Future Prediction/DoublePhysics/SeesawCenterPivot_SeesawOffsetPivot__bg221__hudzDK_trajectory.zip
+Leaderboard/Future Prediction/DoublePhysics/SpringCompress_SpringStretch__bg304__iY1AZp_trajectory.zip
+Leaderboard/Future Prediction/DoublePhysics/UniformConcaveSpin_SpringboardRebound__bg254__hhDGVy_trajectory.zip
+Leaderboard/Future Prediction/DoublePhysics/VerticalFall_UniformPanelSpin__bg261__OCFwnO_trajectory.zip
+Leaderboard/Future Prediction/DoublePhysics/WindDeflectMotion_UniformSurfaceSpin__bg242__EvkQJ4_trajectory.zip
+Leaderboard/Future Prediction/DoublePhysics/WindPushSameDir_WindPushOppDir__bg223__K3BpfI_trajectory.zip
+Leaderboard/Future Prediction/SinglePhysics/AccelConcaveSpin__bg212__NFdwUo_trajectory.zip
+Leaderboard/Future Prediction/SinglePhysics/AccelPanelSpin__bg262__djc1vR_trajectory.zip
+Leaderboard/Future Prediction/SinglePhysics/AccelSurfaceSpin__bg222__QZ2PE4_trajectory.zip
+Leaderboard/Future Prediction/SinglePhysics/BalloonFloat__bg302__p4KZYD_trajectory.zip
+Leaderboard/Future Prediction/SinglePhysics/BalloonLift__bg292__Qt12QQ_trajectory.zip
+Leaderboard/Future Prediction/SinglePhysics/BalloonTether__bg238__DxDc80_trajectory.zip
+Leaderboard/Future Prediction/SinglePhysics/BlockWallCollapse__bg298__FNYLX6_trajectory.zip
+Leaderboard/Future Prediction/SinglePhysics/CartMove__bg206__kYmfIb_trajectory.zip
+Leaderboard/Future Prediction/SinglePhysics/CatapultLaunch__bg285__oEOde8_trajectory.zip
+Leaderboard/Future Prediction/SinglePhysics/ChainSuspend__bg231__ryNCAj_trajectory.zip
+Leaderboard/Future Prediction/SinglePhysics/CrankPush__bg244__bthMYh_trajectory.zip
+Leaderboard/Future Prediction/SinglePhysics/DoublePendulum__bg222__Nzo0Eh_trajectory.zip
+Leaderboard/Future Prediction/SinglePhysics/DynMirrorRedirect__bg292__41t9VE_trajectory.zip
+Leaderboard/Future Prediction/SinglePhysics/ElasticCouple__bg227__JKaxKZ_trajectory.zip
+Leaderboard/Future Prediction/SinglePhysics/ElasticFall__bg852__rueoHR_trajectory.zip
+Leaderboard/Future Prediction/SinglePhysics/FixedArrayRedirect__bg299__ZepDd8_trajectory.zip
+Leaderboard/Future Prediction/SinglePhysics/FixedConcaveRedirect__bg293__coyuOe_trajectory.zip
+Leaderboard/Future Prediction/SinglePhysics/FixedConvexRedirect__bg285__n1yPPu_trajectory.zip
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Utils/leaderboard_lists/physical-properties-estimation.txt

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+Leaderboard/Physical Properties Estimation/DoublePhysics/ElasticFall_PlasticineFall__bg852__EyOXxy_trajectory.zip
+Leaderboard/Physical Properties Estimation/DoublePhysics/ElasticFall_PlasticineFall__bg852__ihzgfo_trajectory.zip
+Leaderboard/Physical Properties Estimation/DoublePhysics/NewtonianFluidFall_GranularFall__bg851__3GTIkU_trajectory.zip
+Leaderboard/Physical Properties Estimation/DoublePhysics/NewtonianFluidFall_GranularFall__bg851__BlGkE3_trajectory.zip
+Leaderboard/Physical Properties Estimation/DoublePhysics/NewtonianFluidFall_GranularFall__bg851__fDvosI_trajectory.zip
+Leaderboard/Physical Properties Estimation/SinglePhysics/ElasticFall__bg851__HyKM4e_trajectory.zip
+Leaderboard/Physical Properties Estimation/SinglePhysics/ElasticFall__bg851__ONA90r_trajectory.zip
+Leaderboard/Physical Properties Estimation/SinglePhysics/ElasticFall__bg851__Urfkor_trajectory.zip
+Leaderboard/Physical Properties Estimation/SinglePhysics/ElasticFall__bg851__aZnA3h_trajectory.zip
+Leaderboard/Physical Properties Estimation/SinglePhysics/ElasticFall__bg851__tCRMt3_trajectory.zip
+Leaderboard/Physical Properties Estimation/SinglePhysics/ElasticFall__bg851__wBxhzP_trajectory.zip
+Leaderboard/Physical Properties Estimation/SinglePhysics/ElasticFall__bg852__n4vNbZ_trajectory.zip
+Leaderboard/Physical Properties Estimation/SinglePhysics/ElasticFall__bg852__rueoHR_trajectory.zip
+Leaderboard/Physical Properties Estimation/SinglePhysics/ElasticFall__bg852__tgPNPs_trajectory.zip
+Leaderboard/Physical Properties Estimation/SinglePhysics/ElasticFall__bg853__IKwBRg_trajectory.zip
+Leaderboard/Physical Properties Estimation/SinglePhysics/ElasticFall__bg853__ZT7AUD_trajectory.zip
+Leaderboard/Physical Properties Estimation/SinglePhysics/ElasticFall__bg853__cPLVum_trajectory.zip
+Leaderboard/Physical Properties Estimation/SinglePhysics/GranularFall__bg851__9lIDU3_trajectory.zip
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+Leaderboard/Physical Properties Estimation/SinglePhysics/PlasticineFall__bg851__CJa9sg_trajectory.zip
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+Leaderboard/Physical Properties Estimation/SinglePhysics/PlasticineFall__bg853__wWdOlo_trajectory.zip
+Leaderboard/Physical Properties Estimation/TriplePhysics/ElasticFall_PlasticineFall_GranularFall__bg853__S2qLvS_trajectory.zip
+Leaderboard/Physical Properties Estimation/TriplePhysics/ElasticFall_PlasticineFall_GranularFall__bg853__t7AbFK_trajectory.zip
+Leaderboard/Physical Properties Estimation/TriplePhysics/ElasticFall_PlasticineFall_GranularFall__bg853__uzqMDe_trajectory.zip
+Leaderboard/Physical Properties Estimation/TriplePhysics/NewtonianFluidFall_NonNewtonianFluidFall_ElasticFall__bg852__EyPG9y_trajectory.zip
+Leaderboard/Physical Properties Estimation/TriplePhysics/NewtonianFluidFall_NonNewtonianFluidFall_ElasticFall__bg852__YklJCP_trajectory.zip
+Leaderboard/Physical Properties Estimation/TriplePhysics/NewtonianFluidFall_NonNewtonianFluidFall_ElasticFall__bg852__rGZfig_trajectory.zip
+Leaderboard/Physical Properties Estimation/test_supp_info/Test_sdf.zip
+Leaderboard/Physical Properties Estimation/test_supp_info/test_case_supp_map.json

Utils/leaderboard_lists/summary.json

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+{
+  "future-prediction": {
+    "bytes": 15831190088,
+    "file_list": "PhysInOne Utils/leaderboard_lists/future-prediction.txt",
+    "files": 103,
+    "remote_directory": "Leaderboard/Future Prediction",
+    "zip_files": 103
+  },
+  "motion-transfer": {
+    "bytes": 9601241294,
+    "file_list": "PhysInOne Utils/leaderboard_lists/motion-transfer.txt",
+    "files": 217,
+    "remote_directory": "Leaderboard/Motion Transfer",
+    "zip_files": 217
+  },
+  "physical-properties-estimation": {
+    "bytes": 14919879645,
+    "file_list": "PhysInOne Utils/leaderboard_lists/physical-properties-estimation.txt",
+    "files": 74,
+    "remote_directory": "Leaderboard/Physical Properties Estimation",
+    "zip_files": 73
+  },
+  "video-generation": {
+    "bytes": 9396335391,
+    "file_list": "PhysInOne Utils/leaderboard_lists/video-generation.txt",
+    "files": 75865,
+    "remote_directory": "Leaderboard/Video Generation",
+    "zip_files": 0
+  }
+}

Utils/leaderboard_lists/video-generation.txt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b350ed9cb6bf97f6dc06b7d6f057640312b15b68ba1395d3a39930c29cf6b31a
+size 10567964

Utils/metadata/repo_assignment.txt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:380a0ba378cd4c2e89b1fc6b6c26c5adf01e65f2c1c1a0c62862d360c47091ab
+size 21608478

Utils/metadata/repo_map.json

@@ -0,0 +1,18 @@
+{
+  "physinone_part1": "PhysInOneP01/PhysInOneP01",
+  "physinone_part2": "PhysInOneP02/PhysInOneP02",
+  "physinone_part3": "PhysInOneP03/PhysInOneP03",
+  "physinone_part4": "PhysInOneP04/PhysInOneP04",
+  "physinone_part5": "PhysInOneP05/PhysInOneP05",
+  "physinone_part6": "PhysInOneP06/PhysInOneP06",
+  "physinone_part7": "PhysInOneP07/PhysInOneP07",
+  "physinone_part8": "PhysInOneP08/PhysInOneP08",
+  "physinone_part9": "PhysInOneP09/PhysInOneP09",
+  "physinone_part10": "PhysInOneP10/PhysInOneP10",
+  "physinone_part11": "PhysInOneP11/PhysInOneP11",
+  "physinone_part12": "PhysInOneP12/PhysInOneP12",
+  "physinone_part13": "PhysInOneP13/PhysInOneP13",
+  "physinone_part14": "PhysInOneP14/PhysInOneP14",
+  "physinone_part15": "PhysInOneP15/PhysInOneP15",
+  "physinone_part16": "PhysInOneP16/PhysInOneP16"
+}

Utils/scripts/download.py

@@ -0,0 +1,188 @@
+#!/usr/bin/env python3
+"""
+Download selected PhysInOne case zip files from Hugging Face shard repositories.
+
+Input:
+    selected_cases.json produced by filter_cases.py
+    repo_map.json mapping part IDs to Hugging Face repo IDs
+
+Recommended repo_map.json format:
+{
+  "physinone_part1": "PhysInOneP01/PhysInOneP01",
+  "physinone_part2": "PhysInOneP02/PhysInOneP02"
+}
+
+The script downloads each selected case zip using huggingface_hub.hf_hub_download.
+"""
+
+from __future__ import annotations
+
+import argparse
+import json
+import shutil
+from pathlib import Path
+from urllib.parse import urlparse
+
+from huggingface_hub import hf_hub_download
+from tqdm import tqdm
+
+
+DEFAULT_SELECTION_FILE = Path("selected_cases.json")
+DEFAULT_REPO_MAP_FILE = Path("metadata/repo_map.json")
+
+
+def normalize_repo_id(value: str) -> str:
+    """Accept either a repo id or a Hugging Face URL and return repo id."""
+    value = value.strip().rstrip("/")
+    if value.startswith("http://") or value.startswith("https://"):
+        parsed = urlparse(value)
+        # Expected: /datasets/PhysInOneP01/PhysInOneP01[/tree/main]
+        parts = [p for p in parsed.path.split("/") if p]
+        if len(parts) >= 3 and parts[0] == "datasets":
+            return f"{parts[1]}/{parts[2]}"
+        raise ValueError(f"Cannot parse Hugging Face dataset repo URL: {value}")
+    return value
+
+
+def load_json(path: Path) -> dict:
+    if not path.exists():
+        raise FileNotFoundError(f"File not found: {path}")
+    return json.loads(path.read_text(encoding="utf-8"))
+
+
+def load_repo_map(path: Path) -> dict[str, str]:
+    data = load_json(path)
+    if not isinstance(data, dict):
+        raise ValueError("repo_map.json must be a dictionary: part_id -> repo_id")
+    return {str(k): normalize_repo_id(str(v)) for k, v in data.items()}
+
+
+def safe_output_path(output_dir: Path, case: dict, keep_shard_structure: bool) -> Path:
+    filename = Path(case["hf_zip_path"]).name
+    if keep_shard_structure:
+        # Preserve Split/ActivityType layout.
+        return output_dir / case["part_id"] / case["split"] / case["activity_type"] / filename
+    return output_dir / filename
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser(description="Download PhysInOne selected case zips.")
+    parser.add_argument(
+        "--selection",
+        type=Path,
+        default=DEFAULT_SELECTION_FILE,
+        help=f"selected_cases.json from filter_cases.py. Default: {DEFAULT_SELECTION_FILE}",
+    )
+    parser.add_argument(
+        "--repo_map",
+        type=Path,
+        default=DEFAULT_REPO_MAP_FILE,
+        help=f"JSON mapping part_id to HF repo id. Default: {DEFAULT_REPO_MAP_FILE}",
+    )
+    parser.add_argument(
+        "--output_dir",
+        type=Path,
+        default=Path("./PhysInOne"),
+        help="Local output directory. Default: ./PhysInOne",
+    )
+    parser.add_argument(
+        "--repo_type",
+        type=str,
+        default="dataset",
+        help="Hugging Face repo type. Default: dataset",
+    )
+    parser.add_argument(
+        "--revision",
+        type=str,
+        default="main",
+        help="Hugging Face revision/branch. Default: main",
+    )
+    parser.add_argument(
+        "--token",
+        type=str,
+        default=None,
+        help="Optional Hugging Face token for gated/private repos.",
+    )
+    parser.add_argument(
+        "--keep_shard_structure",
+        action="store_true",
+        help="Save as output_dir/part_id/Split/ActivityType/*.zip instead of a flat folder.",
+    )
+    parser.add_argument(
+        "--dry_run",
+        action="store_true",
+        help="Print planned downloads without downloading.",
+    )
+    parser.add_argument(
+        "--overwrite",
+        action="store_true",
+        help="Overwrite local files if they already exist.",
+    )
+
+    args = parser.parse_args()
+
+    selection = load_json(args.selection)
+    repo_map = load_repo_map(args.repo_map)
+    cases = selection.get("cases", [])
+    if not isinstance(cases, list):
+        raise ValueError("selection JSON must contain a list field named 'cases'.")
+
+    args.output_dir.mkdir(parents=True, exist_ok=True)
+
+    missing_parts = sorted({case["part_id"] for case in cases if case["part_id"] not in repo_map})
+    if missing_parts:
+        raise KeyError(
+            "The following part IDs are missing from repo_map.json: "
+            + ", ".join(missing_parts)
+        )
+
+    print(f"Cases to download: {len(cases)}")
+    if args.dry_run:
+        for case in cases[:20]:
+            repo_id = repo_map[case["part_id"]]
+            out_path = safe_output_path(args.output_dir, case, args.keep_shard_structure)
+            print(f"{repo_id} :: {case['hf_zip_path']} -> {out_path}")
+        if len(cases) > 20:
+            print(f"... and {len(cases) - 20} more")
+        return
+
+    failures = []
+    for case in tqdm(cases, desc="Downloading cases"):
+        repo_id = repo_map[case["part_id"]]
+        filename = case["hf_zip_path"]
+        out_path = safe_output_path(args.output_dir, case, args.keep_shard_structure)
+        out_path.parent.mkdir(parents=True, exist_ok=True)
+
+        if out_path.exists() and not args.overwrite:
+            continue
+
+        try:
+            cached_file = hf_hub_download(
+                repo_id=repo_id,
+                filename=filename,
+                repo_type=args.repo_type,
+                revision=args.revision,
+                token=args.token,
+            )
+            shutil.copy2(cached_file, out_path)
+        except Exception as exc:  # Keep going and summarize failures.
+            failures.append(
+                {
+                    "case_id": case.get("case_id"),
+                    "part_id": case.get("part_id"),
+                    "repo_id": repo_id,
+                    "hf_zip_path": filename,
+                    "error": repr(exc),
+                }
+            )
+
+    if failures:
+        failure_path = args.output_dir / "download_failures.json"
+        failure_path.write_text(json.dumps(failures, indent=2, ensure_ascii=False), encoding="utf-8")
+        print(f"Finished with {len(failures)} failures. See: {failure_path}")
+    else:
+        print("All downloads completed successfully.")
+
+
+if __name__ == "__main__":
+    main()

Utils/scripts/download_3d_assets.py

@@ -0,0 +1,444 @@
+#!/usr/bin/env python3
+"""Download and assemble the PhysInOne validation 3D asset project."""
+
+from __future__ import annotations
+
+import argparse
+import filecmp
+import json
+import os
+import shutil
+import stat
+import sys
+import threading
+import zipfile
+from concurrent.futures import ThreadPoolExecutor, as_completed
+from dataclasses import dataclass
+from datetime import datetime, timezone
+from pathlib import Path, PurePosixPath
+from typing import Sequence
+
+try:
+    from huggingface_hub import hf_hub_download
+except ImportError as exc:  # pragma: no cover
+    raise SystemExit(
+        "Missing dependency: huggingface_hub. Install it with "
+        "`pip install -U huggingface_hub tqdm`."
+    ) from exc
+
+try:
+    from tqdm import tqdm
+except ImportError:  # pragma: no cover
+    tqdm = None
+
+
+REPO_ID = "vLAR/PhysInOne"
+REPO_TYPE = "dataset"
+REMOTE_ROOT = "3D Assets/PhysicBenchmark"
+LIST_REPO_ROOT = "PhysInOne Utils/3d_assets_lists"
+LOCAL_LIST_ROOT = Path(__file__).resolve().parent.parent / "3d_assets_lists"
+FILE_LIST_NAME = "validation.txt"
+ARCHIVE_LIST_NAME = "validation_archives.txt"
+SUMMARY_NAME = "summary.json"
+
+
+def utc_now() -> str:
+    return datetime.now(timezone.utc).isoformat(timespec="seconds")
+
+
+def safe_message(exc: BaseException) -> str:
+    return " ".join(str(exc).replace("\t", " ").splitlines()).strip() or type(exc).__name__
+
+
+def read_lines(path: Path) -> list[str]:
+    return [
+        line.strip()
+        for line in path.read_text(encoding="utf-8").splitlines()
+        if line.strip() and not line.lstrip().startswith("#")
+    ]
+
+
+def get_release_file(name: str, revision: str, cache_dir: Path) -> Path:
+    local = LOCAL_LIST_ROOT / name
+    if local.is_file():
+        return local
+    return Path(
+        hf_hub_download(
+            REPO_ID,
+            f"{LIST_REPO_ROOT}/{name}",
+            repo_type=REPO_TYPE,
+            revision=revision,
+            cache_dir=cache_dir,
+        )
+    )
+
+
+def load_release(revision: str, cache_dir: Path) -> tuple[list[str], list[str], dict]:
+    files = read_lines(get_release_file(FILE_LIST_NAME, revision, cache_dir))
+    archives = read_lines(get_release_file(ARCHIVE_LIST_NAME, revision, cache_dir))
+    summary = json.loads(
+        get_release_file(SUMMARY_NAME, revision, cache_dir).read_text(encoding="utf-8")
+    )
+    if not files or len(files) != len(set(files)) or files != sorted(files):
+        raise RuntimeError("the validation 3D asset file list is empty, duplicated, or unsorted")
+    if any(not path.startswith(REMOTE_ROOT + "/") for path in files):
+        raise RuntimeError("a release path is outside the expected PhysicBenchmark root")
+    if set(archives) != {path for path in files if path.lower().endswith(".zip")}:
+        raise RuntimeError("the archive list does not match the validation file list")
+    if any(PurePosixPath(path).name.casefold() == "train.zip" for path in files):
+        raise RuntimeError("the validation release unexpectedly contains Train.zip")
+    return files, archives, summary
+
+
+def archive_marker(archive: Path) -> Path:
+    return archive.parent / ".physinone_extract_status" / f"{archive.name}.json"
+
+
+def completed_removed_archive(archive: Path) -> bool:
+    marker = archive_marker(archive)
+    if archive.exists() or not marker.is_file():
+        return False
+    try:
+        state = json.loads(marker.read_text(encoding="utf-8"))
+    except (OSError, ValueError):
+        return False
+    return state.get("status") == "complete" and int(state.get("files", 0)) > 0
+
+
+def safe_zip_members(archive: zipfile.ZipFile) -> list[zipfile.ZipInfo]:
+    members = archive.infolist()
+    for info in members:
+        path = PurePosixPath(info.filename)
+        mode = (info.external_attr >> 16) & 0o170000
+        if (
+            path.is_absolute()
+            or not path.parts
+            or any(part in {"", ".", ".."} for part in path.parts)
+            or mode == stat.S_IFLNK
+        ):
+            raise RuntimeError(f"unsafe ZIP member: {info.filename}")
+    return members
+
+
+def members_complete(parent: Path, members: Sequence[zipfile.ZipInfo]) -> bool:
+    files = [info for info in members if not info.is_dir()]
+    return bool(files) and all(
+        (parent.joinpath(*PurePosixPath(info.filename).parts)).is_file()
+        and (parent.joinpath(*PurePosixPath(info.filename).parts)).stat().st_size
+        == info.file_size
+        for info in files
+    )
+
+
+def merge_extracted_tree(temporary: Path, destination: Path) -> tuple[int, int]:
+    added = 0
+    reused = 0
+    for source in sorted(temporary.rglob("*")):
+        relative = source.relative_to(temporary)
+        target = destination / relative
+        if source.is_dir():
+            target.mkdir(parents=True, exist_ok=True)
+            continue
+        target.parent.mkdir(parents=True, exist_ok=True)
+        if target.exists():
+            if not target.is_file():
+                raise RuntimeError(f"extraction conflict with non-file path: {target}")
+            if source.stat().st_size != target.stat().st_size or not filecmp.cmp(
+                source, target, shallow=False
+            ):
+                raise RuntimeError(f"extraction would overwrite different data: {target}")
+            source.unlink()
+            reused += 1
+        else:
+            source.replace(target)
+            added += 1
+    return added, reused
+
+
+def extract_archive(archive_path: Path) -> tuple[str, int, int]:
+    marker = archive_marker(archive_path)
+    with zipfile.ZipFile(archive_path) as archive:
+        members = safe_zip_members(archive)
+        files = [info for info in members if not info.is_dir()]
+        if members_complete(archive_path.parent, members):
+            marker.parent.mkdir(exist_ok=True)
+            marker.write_text(
+                json.dumps(
+                    {
+                        "archive": archive_path.name,
+                        "archive_size": archive_path.stat().st_size,
+                        "files": len(files),
+                        "status": "complete",
+                        "verified_at": utc_now(),
+                    },
+                    sort_keys=True,
+                )
+                + "\n",
+                encoding="utf-8",
+            )
+            return "already_extracted", 0, len(files)
+
+        temporary_root = archive_path.parent / ".physinone_extracting"
+        temporary = temporary_root / (
+            f"{archive_path.stem}-{os.getpid()}-{threading.get_ident()}"
+        )
+        if temporary.exists():
+            shutil.rmtree(temporary)
+        temporary.mkdir(parents=True)
+        try:
+            archive.extractall(temporary)
+            added, reused = merge_extracted_tree(temporary, archive_path.parent)
+        finally:
+            if temporary.exists():
+                shutil.rmtree(temporary)
+            if temporary_root.exists() and not any(temporary_root.iterdir()):
+                temporary_root.rmdir()
+
+    marker.parent.mkdir(exist_ok=True)
+    marker.write_text(
+        json.dumps(
+            {
+                "archive": archive_path.name,
+                "archive_size": archive_path.stat().st_size,
+                "files": len(files),
+                "status": "complete",
+                "verified_at": utc_now(),
+            },
+            sort_keys=True,
+        )
+        + "\n",
+        encoding="utf-8",
+    )
+    return "extracted", added, reused
+
+
+@dataclass(frozen=True)
+class DownloadResult:
+    remote_path: str
+    local_path: str
+    status: str
+    error: str = ""
+
+
+class Logs:
+    def __init__(self, root: Path) -> None:
+        self.root = root
+        self.root.mkdir(parents=True, exist_ok=True)
+        self.downloads = root / "downloads.tsv"
+        self.failures = root / "failures.tsv"
+        self.extraction = root / "extraction.tsv"
+        self.events = root / "events.jsonl"
+        self._lock = threading.Lock()
+        self.downloads.write_text(
+            "remote_path\tlocal_path\tstatus\ttimestamp\n", encoding="utf-8"
+        )
+        self.failures.write_text(
+            "stage\tpath\terror\ttimestamp\n", encoding="utf-8"
+        )
+        self.extraction.write_text(
+            "archive\tstatus\tadded_files\treused_files\ttimestamp\n",
+            encoding="utf-8",
+        )
+
+    def event(self, event: str, **fields: object) -> None:
+        payload = {"event": event, "timestamp": utc_now(), **fields}
+        with self._lock, self.events.open("a", encoding="utf-8") as handle:
+            handle.write(json.dumps(payload, sort_keys=True) + "\n")
+
+    def record_download(self, result: DownloadResult) -> None:
+        timestamp = utc_now()
+        with self._lock:
+            if result.error:
+                with self.failures.open("a", encoding="utf-8") as handle:
+                    handle.write(
+                        f"download\t{result.remote_path}\t{result.error}\t{timestamp}\n"
+                    )
+            else:
+                with self.downloads.open("a", encoding="utf-8") as handle:
+                    handle.write(
+                        f"{result.remote_path}\t{result.local_path}\t"
+                        f"{result.status}\t{timestamp}\n"
+                    )
+        self.event(
+            "download",
+            remote_path=result.remote_path,
+            local_path=result.local_path,
+            status=result.status,
+            error=result.error,
+        )
+
+    def record_extraction(
+        self, archive: str, status: str, added: int, reused: int, error: str = ""
+    ) -> None:
+        timestamp = utc_now()
+        with self._lock:
+            if error:
+                with self.failures.open("a", encoding="utf-8") as handle:
+                    handle.write(f"extract\t{archive}\t{error}\t{timestamp}\n")
+            else:
+                with self.extraction.open("a", encoding="utf-8") as handle:
+                    handle.write(
+                        f"{archive}\t{status}\t{added}\t{reused}\t{timestamp}\n"
+                    )
+        self.event(
+            "extraction",
+            archive=archive,
+            status=status,
+            added_files=added,
+            reused_files=reused,
+            error=error,
+        )
+
+
+def download_one(
+    remote_path: str,
+    output_dir: Path,
+    cache_dir: Path,
+    revision: str,
+    skip_removed_archive: bool,
+) -> DownloadResult:
+    local_expected = output_dir.joinpath(*PurePosixPath(remote_path).parts)
+    if skip_removed_archive and completed_removed_archive(local_expected):
+        return DownloadResult(remote_path, str(local_expected), "extracted_zip_removed")
+    try:
+        local = hf_hub_download(
+            REPO_ID,
+            remote_path,
+            repo_type=REPO_TYPE,
+            revision=revision,
+            local_dir=output_dir,
+            cache_dir=cache_dir,
+        )
+        return DownloadResult(remote_path, str(local), "ready")
+    except Exception as exc:
+        return DownloadResult(remote_path, "", "failed", safe_message(exc))
+
+
+def build_parser() -> argparse.ArgumentParser:
+    parser = argparse.ArgumentParser(
+        description="Download and assemble the PhysInOne validation 3D asset project."
+    )
+    parser.add_argument(
+        "--output-dir",
+        type=Path,
+        default=Path("PhysInOne-3D-Assets"),
+        help=(
+            "Local release root. The project will be stored at "
+            "<output-dir>/3D Assets/PhysicBenchmark."
+        ),
+    )
+    parser.add_argument(
+        "--workers", type=int, default=4, help="Concurrent downloads (default: 4)."
+    )
+    parser.add_argument("--revision", default="main", help="Dataset revision (default: main).")
+    parser.add_argument(
+        "--no-extract",
+        action="store_true",
+        help="Download the release without extracting its eight ZIP archives.",
+    )
+    parser.add_argument(
+        "--delete-zip-after-extract",
+        action="store_true",
+        help="Delete each ZIP only after it is completely extracted and verified.",
+    )
+    parser.add_argument(
+        "--dry-run", action="store_true", help="Show release statistics without downloading."
+    )
+    return parser
+
+
+def main(argv: Sequence[str] | None = None) -> int:
+    args = build_parser().parse_args(argv)
+    if args.workers < 1:
+        raise SystemExit("--workers must be at least 1")
+    if args.no_extract and args.delete_zip_after_extract:
+        raise SystemExit("--delete-zip-after-extract cannot be combined with --no-extract")
+
+    output_dir = args.output_dir.expanduser().resolve()
+    cache_dir = output_dir / ".hf_cache"
+    files, archives, release_summary = load_release(args.revision, cache_dir)
+    print(
+        f"Validation 3D assets: {len(files)} files, {len(archives)} ZIP archives, "
+        f"{int(release_summary['bytes']) / (1024 ** 3):.2f} GiB download"
+    )
+    print(f"Project root: {output_dir / '3D Assets' / 'PhysicBenchmark'}")
+    if args.dry_run:
+        return 0
+
+    output_dir.mkdir(parents=True, exist_ok=True)
+    run_id = datetime.now().strftime("%Y%m%d_%H%M%S")
+    logs = Logs(output_dir / "_3d_asset_download_logs" / run_id)
+    results: list[DownloadResult] = []
+    with ThreadPoolExecutor(max_workers=args.workers) as pool:
+        futures = {
+            pool.submit(
+                download_one,
+                path,
+                output_dir,
+                cache_dir,
+                args.revision,
+                args.delete_zip_after_extract,
+            ): path
+            for path in files
+        }
+        completed = as_completed(futures)
+        if tqdm is not None:
+            completed = tqdm(completed, total=len(futures), unit="file", desc="Download")
+        for future in completed:
+            result = future.result()
+            logs.record_download(result)
+            results.append(result)
+
+    download_failures = [result for result in results if result.error]
+    extraction_failures = 0
+    extracted = 0
+    if not args.no_extract:
+        iterable = archives
+        if tqdm is not None:
+            iterable = tqdm(archives, unit="archive", desc="Extract")
+        for remote_path in iterable:
+            archive_path = output_dir.joinpath(*PurePosixPath(remote_path).parts)
+            if completed_removed_archive(archive_path):
+                logs.record_extraction(remote_path, "already_extracted_zip_removed", 0, 0)
+                extracted += 1
+                continue
+            if not archive_path.is_file():
+                error = "archive is unavailable because its download failed"
+                logs.record_extraction(remote_path, "failed", 0, 0, error)
+                extraction_failures += 1
+                continue
+            try:
+                status, added, reused = extract_archive(archive_path)
+                logs.record_extraction(remote_path, status, added, reused)
+                extracted += 1
+                if args.delete_zip_after_extract:
+                    archive_path.unlink()
+            except Exception as exc:
+                logs.record_extraction(
+                    remote_path, "failed", 0, 0, safe_message(exc)
+                )
+                extraction_failures += 1
+
+    summary = {
+        "repo_id": REPO_ID,
+        "revision": args.revision,
+        "release": "validation",
+        "expected_files": len(files),
+        "successful_downloads": len(results) - len(download_failures),
+        "download_failures": len(download_failures),
+        "expected_archives": len(archives),
+        "completed_archives": extracted,
+        "extraction_failures": extraction_failures,
+        "project_root": str(output_dir / "3D Assets" / "PhysicBenchmark"),
+        "log_dir": str(logs.root),
+        "finished_at": utc_now(),
+    }
+    (logs.root / "summary.json").write_text(
+        json.dumps(summary, indent=2, sort_keys=True) + "\n", encoding="utf-8"
+    )
+    print(json.dumps(summary, indent=2, sort_keys=True))
+    return 1 if download_failures or extraction_failures else 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())

Utils/scripts/download_leaderboard.py

@@ -0,0 +1,435 @@
+#!/usr/bin/env python3
+"""Download public PhysInOne Leaderboard evaluation data.
+
+The script uses release-maintained, task-specific file lists so every download
+is explicit, reproducible, resumable, and limited to the requested tasks.
+"""
+
+from __future__ import annotations
+
+import argparse
+import json
+import os
+import shutil
+import stat
+import sys
+import threading
+import zipfile
+from concurrent.futures import ThreadPoolExecutor, as_completed
+from dataclasses import dataclass
+from datetime import datetime, timezone
+from pathlib import Path, PurePosixPath
+from typing import Iterable, Sequence
+
+try:
+    from huggingface_hub import hf_hub_download
+except ImportError as exc:  # pragma: no cover - exercised by users without the dependency
+    raise SystemExit(
+        "Missing dependency: huggingface_hub. Install it with "
+        "`pip install -U huggingface_hub tqdm`."
+    ) from exc
+
+try:
+    from tqdm import tqdm
+except ImportError:  # pragma: no cover - tqdm is optional
+    tqdm = None
+
+
+REPO_ID = "vLAR/PhysInOne"
+REPO_TYPE = "dataset"
+TASKS = {
+    "video-generation": {
+        "display": "Video Generation",
+        "list": "video-generation.txt",
+    },
+    "future-prediction": {
+        "display": "Future Prediction",
+        "list": "future-prediction.txt",
+    },
+    "physical-properties-estimation": {
+        "display": "Physical Properties Estimation",
+        "list": "physical-properties-estimation.txt",
+    },
+    "motion-transfer": {
+        "display": "Motion Transfer",
+        "list": "motion-transfer.txt",
+    },
+}
+ALIASES = {
+    "video": "video-generation",
+    "vg": "video-generation",
+    "future": "future-prediction",
+    "fp": "future-prediction",
+    "physical-properties": "physical-properties-estimation",
+    "physical-property-estimation": "physical-properties-estimation",
+    "ppe": "physical-properties-estimation",
+    "motion": "motion-transfer",
+    "mt": "motion-transfer",
+}
+LIST_REPO_ROOT = "PhysInOne Utils/leaderboard_lists"
+LOCAL_LIST_ROOT = Path(__file__).resolve().parent.parent / "leaderboard_lists"
+
+
+def utc_now() -> str:
+    return datetime.now(timezone.utc).isoformat(timespec="seconds")
+
+
+def safe_message(exc: BaseException) -> str:
+    return " ".join(str(exc).replace("\t", " ").splitlines()).strip() or type(exc).__name__
+
+
+def normalize_task(value: str) -> str:
+    slug = value.strip().lower().replace("_", "-").replace(" ", "-")
+    slug = ALIASES.get(slug, slug)
+    if slug not in TASKS and slug != "all":
+        choices = ", ".join([*TASKS, "all"])
+        raise argparse.ArgumentTypeError(f"unknown task {value!r}; choose one of: {choices}")
+    return slug
+
+
+def selected_tasks(values: Sequence[str]) -> list[str]:
+    if not values or "all" in values:
+        return list(TASKS)
+    return list(dict.fromkeys(values))
+
+
+def read_lines(path: Path) -> list[str]:
+    lines = []
+    for raw in path.read_text(encoding="utf-8").splitlines():
+        line = raw.strip()
+        if line and not line.startswith("#"):
+            lines.append(line)
+    return lines
+
+
+def get_task_list(task: str, revision: str, cache_dir: Path) -> list[str]:
+    filename = str(TASKS[task]["list"])
+    local = LOCAL_LIST_ROOT / filename
+    if not local.is_file():
+        remote = f"{LIST_REPO_ROOT}/{filename}"
+        local = Path(
+            hf_hub_download(
+                repo_id=REPO_ID,
+                repo_type=REPO_TYPE,
+                filename=remote,
+                revision=revision,
+                cache_dir=cache_dir,
+            )
+        )
+    paths = read_lines(local)
+    expected_root = f"Leaderboard/{TASKS[task]['display']}/"
+    invalid = [path for path in paths if not path.startswith(expected_root)]
+    if invalid:
+        raise RuntimeError(f"invalid path in {filename}: {invalid[0]}")
+    if len(paths) != len(set(paths)):
+        raise RuntimeError(f"duplicate paths found in {filename}")
+    return paths
+
+
+def filter_scenes(paths: Iterable[str], scene_filters: Sequence[str]) -> list[str]:
+    filters = [item.casefold() for item in scene_filters if item.strip()]
+    if not filters:
+        return list(paths)
+    return [path for path in paths if any(item in path.casefold() for item in filters)]
+
+
+def is_safe_zip_member(info: zipfile.ZipInfo) -> bool:
+    path = PurePosixPath(info.filename)
+    if path.is_absolute() or not path.parts:
+        return False
+    if any(part in {"", ".", ".."} for part in path.parts):
+        return False
+    mode = (info.external_attr >> 16) & 0o170000
+    return mode != stat.S_IFLNK
+
+
+def extract_scene_zip(zip_path: Path) -> str:
+    """Safely extract a scene archive next to the ZIP and return its root path."""
+    expected_root = zip_path.stem
+    destination = zip_path.parent / expected_root
+    marker_dir = zip_path.parent / ".physinone_extract_status"
+    marker = marker_dir / f"{zip_path.name}.json"
+    archive_stat = zip_path.stat()
+
+    if marker.is_file() and destination.is_dir():
+        try:
+            state = json.loads(marker.read_text(encoding="utf-8"))
+            if state.get("archive_size") == archive_stat.st_size:
+                return "already_extracted"
+        except (OSError, ValueError):
+            pass
+    if destination.exists():
+        raise RuntimeError(
+            f"extraction target already exists without a matching completion marker: {destination}"
+        )
+
+    temporary = zip_path.parent / (
+        f".{expected_root}.extracting-{os.getpid()}-{threading.get_ident()}"
+    )
+    if temporary.exists():
+        shutil.rmtree(temporary)
+    temporary.mkdir(parents=False)
+    try:
+        with zipfile.ZipFile(zip_path) as archive:
+            members = archive.infolist()
+            unsafe = [info.filename for info in members if not is_safe_zip_member(info)]
+            if unsafe:
+                raise RuntimeError(f"unsafe ZIP member: {unsafe[0]}")
+            roots = {PurePosixPath(info.filename).parts[0] for info in members}
+            if roots != {expected_root}:
+                raise RuntimeError(
+                    f"unexpected ZIP root(s) {sorted(roots)}; expected {expected_root!r}"
+                )
+            bad = archive.testzip()
+            if bad is not None:
+                raise RuntimeError(f"ZIP CRC check failed at {bad}")
+            archive.extractall(temporary)
+        extracted = temporary / expected_root
+        if not extracted.is_dir():
+            raise RuntimeError(f"archive did not create the expected scene directory: {expected_root}")
+        extracted.replace(destination)
+        marker_dir.mkdir(exist_ok=True)
+        marker.write_text(
+            json.dumps(
+                {
+                    "archive": zip_path.name,
+                    "archive_size": archive_stat.st_size,
+                    "extracted_at": utc_now(),
+                },
+                sort_keys=True,
+            )
+            + "\n",
+            encoding="utf-8",
+        )
+        return "extracted"
+    finally:
+        if temporary.exists():
+            shutil.rmtree(temporary)
+
+
+@dataclass(frozen=True)
+class Result:
+    task: str
+    remote_path: str
+    local_path: str
+    status: str
+    extracted: str
+    error: str = ""
+
+
+class Logs:
+    def __init__(self, root: Path) -> None:
+        self.root = root
+        self.root.mkdir(parents=True, exist_ok=True)
+        self.success = self.root / "success.tsv"
+        self.failures = self.root / "failures.tsv"
+        self.events = self.root / "events.jsonl"
+        self._lock = threading.Lock()
+        self.success.write_text(
+            "task\tremote_path\tlocal_path\tstatus\textracted\ttimestamp\n",
+            encoding="utf-8",
+        )
+        self.failures.write_text(
+            "task\tremote_path\terror\ttimestamp\n",
+            encoding="utf-8",
+        )
+
+    def record(self, result: Result) -> None:
+        timestamp = utc_now()
+        with self._lock:
+            if result.error:
+                with self.failures.open("a", encoding="utf-8") as handle:
+                    handle.write(
+                        f"{result.task}\t{result.remote_path}\t{result.error}\t{timestamp}\n"
+                    )
+            else:
+                with self.success.open("a", encoding="utf-8") as handle:
+                    handle.write(
+                        f"{result.task}\t{result.remote_path}\t{result.local_path}\t"
+                        f"{result.status}\t{result.extracted}\t{timestamp}\n"
+                    )
+            with self.events.open("a", encoding="utf-8") as handle:
+                handle.write(
+                    json.dumps(
+                        {
+                            "task": result.task,
+                            "remote_path": result.remote_path,
+                            "local_path": result.local_path,
+                            "status": result.status,
+                            "extracted": result.extracted,
+                            "error": result.error,
+                            "timestamp": timestamp,
+                        },
+                        sort_keys=True,
+                    )
+                    + "\n"
+                )
+
+
+def download_one(
+    task: str,
+    remote_path: str,
+    output_dir: Path,
+    cache_dir: Path,
+    revision: str,
+    extract: bool,
+    delete_zip: bool,
+) -> Result:
+    try:
+        local = Path(
+            hf_hub_download(
+                repo_id=REPO_ID,
+                repo_type=REPO_TYPE,
+                filename=remote_path,
+                revision=revision,
+                local_dir=output_dir,
+                cache_dir=cache_dir,
+            )
+        )
+        extracted = "not_requested"
+        if extract and local.suffix.lower() == ".zip":
+            extracted = extract_scene_zip(local)
+            if delete_zip:
+                local.unlink()
+        elif extract:
+            extracted = "not_a_zip"
+        return Result(task, remote_path, str(local), "ready", extracted)
+    except Exception as exc:  # keep other downloads running and report all failures
+        return Result(task, remote_path, "", "failed", "not_extracted", safe_message(exc))
+
+
+def build_parser() -> argparse.ArgumentParser:
+    parser = argparse.ArgumentParser(
+        description="Download public PhysInOne Leaderboard evaluation data."
+    )
+    parser.add_argument(
+        "--task",
+        nargs="+",
+        type=normalize_task,
+        default=["all"],
+        help=(
+            "Task(s) to download: video-generation, future-prediction, "
+            "physical-properties-estimation, motion-transfer, or all."
+        ),
+    )
+    parser.add_argument(
+        "--output-dir",
+        type=Path,
+        default=Path("PhysInOne-Leaderboard"),
+        help="Local dataset root (default: ./PhysInOne-Leaderboard).",
+    )
+    parser.add_argument(
+        "--scene",
+        action="append",
+        default=[],
+        help="Download only paths containing this scene name or six-character ID; repeatable.",
+    )
+    parser.add_argument(
+        "--workers",
+        type=int,
+        default=4,
+        help="Concurrent file downloads (default: 4).",
+    )
+    parser.add_argument("--revision", default="main", help="Dataset revision (default: main).")
+    parser.add_argument(
+        "--extract",
+        action="store_true",
+        help="Validate and safely extract downloaded scene ZIP files next to each archive.",
+    )
+    parser.add_argument(
+        "--delete-zip-after-extract",
+        action="store_true",
+        help="Delete each ZIP only after successful extraction; requires --extract.",
+    )
+    parser.add_argument(
+        "--list-only",
+        action="store_true",
+        help="Print the selected remote file paths without downloading them.",
+    )
+    parser.add_argument(
+        "--dry-run",
+        action="store_true",
+        help="Show task and file counts without downloading data.",
+    )
+    return parser
+
+
+def main(argv: Sequence[str] | None = None) -> int:
+    args = build_parser().parse_args(argv)
+    if args.workers < 1:
+        raise SystemExit("--workers must be at least 1")
+    if args.delete_zip_after_extract and not args.extract:
+        raise SystemExit("--delete-zip-after-extract requires --extract")
+
+    tasks = selected_tasks(args.task)
+    output_dir = args.output_dir.expanduser().resolve()
+    cache_dir = output_dir / ".hf_cache"
+    selections: list[tuple[str, str]] = []
+    counts: dict[str, int] = {}
+    for task in tasks:
+        paths = filter_scenes(get_task_list(task, args.revision, cache_dir), args.scene)
+        counts[task] = len(paths)
+        selections.extend((task, path) for path in paths)
+
+    if args.list_only:
+        for _, path in selections:
+            print(path)
+        return 0
+
+    for task in tasks:
+        print(f"{task}: {counts[task]} file(s)")
+    print(f"Total: {len(selections)} file(s)")
+    if args.scene and not selections:
+        print("No files matched --scene.", file=sys.stderr)
+        return 2
+    if args.dry_run:
+        return 0
+
+    output_dir.mkdir(parents=True, exist_ok=True)
+    run_id = datetime.now().strftime("%Y%m%d_%H%M%S")
+    logs = Logs(output_dir / "_download_logs" / run_id)
+    results: list[Result] = []
+    with ThreadPoolExecutor(max_workers=args.workers) as pool:
+        futures = {
+            pool.submit(
+                download_one,
+                task,
+                path,
+                output_dir,
+                cache_dir,
+                args.revision,
+                args.extract,
+                args.delete_zip_after_extract,
+            ): (task, path)
+            for task, path in selections
+        }
+        completed = as_completed(futures)
+        if tqdm is not None:
+            completed = tqdm(completed, total=len(futures), unit="file")
+        for future in completed:
+            result = future.result()
+            logs.record(result)
+            results.append(result)
+
+    failed = [result for result in results if result.error]
+    summary = {
+        "repo_id": REPO_ID,
+        "revision": args.revision,
+        "tasks": tasks,
+        "selected_files": len(selections),
+        "successful_files": len(results) - len(failed),
+        "failed_files": len(failed),
+        "output_dir": str(output_dir),
+        "log_dir": str(logs.root),
+        "finished_at": utc_now(),
+    }
+    (logs.root / "summary.json").write_text(
+        json.dumps(summary, indent=2, sort_keys=True) + "\n",
+        encoding="utf-8",
+    )
+    print(json.dumps(summary, indent=2, sort_keys=True))
+    return 1 if failed else 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())

Utils/scripts/filter_cases.py

@@ -0,0 +1,433 @@
+#!/usr/bin/env python3
+"""
+Filter PhysInOne cases from repo_assignment.txt.
+
+Expected assignment file format:
+    /Game/PhysInOne/Scenes/Train/DoublePhysics/CaseName.CaseName    physinone_part1
+
+The script parses:
+    split: Train / Val / Test
+    activity_type: SinglePhysics / DoublePhysics / TriplePhysics
+    phenomena: abbreviations before "__bg..."
+    background: bgXXX
+    hash: final six-character code
+    part_id: e.g. physinone_part1
+    hf_zip_path: expected zip path inside the shard repo, e.g.
+        Train/DoublePhysics/AccelConcaveSpin_AccelSurfaceSpin__bg070__K5ER39_trajectory.zip
+"""
+
+from __future__ import annotations
+
+import argparse
+import json
+import random
+import re
+from dataclasses import asdict, dataclass
+from pathlib import Path
+from typing import Iterable, Literal
+
+
+DEFAULT_ASSIGNMENT_FILE = Path("metadata/repo_assignment.txt")
+
+
+SUPPORTED_PHENOMENA = {
+    "MovingHitsFixed",
+    "MovingHitsStationary",
+    "MovingHitsMoving",
+    "WindGravityBalance",
+    "WindPushStationary",
+    "WindPushSameDir",
+    "WindPushOppDir",
+    "WindDeflectMotion",
+    "ObliqueProjectile",
+    "VerticalFall",
+    "RollDownSlope",
+    "RollUpSlope",
+    "MagnetAttract",
+    "MagnetRepel",
+    "UniformPanelSpin",
+    "AccelPanelSpin",
+    "UniformConcaveSpin",
+    "AccelConcaveSpin",
+    "UniformSurfaceSpin",
+    "AccelSurfaceSpin",
+    "FrictionStop",
+    "SpringCompress",
+    "SpringStretch",
+    "ImpactFracture",
+    "MirrorFragmentReflect",
+    "ElasticCouple",
+    "SpringboardRebound",
+    "SeesawCenterPivot",
+    "SeesawOffsetPivot",
+    "BalloonFloat",
+    "BalloonTether",
+    "BalloonLift",
+    "FixedPlanarRedirect",
+    "FixedArrayRedirect",
+    "FixedConcaveRedirect",
+    "FixedConvexRedirect",
+    "DynMirrorRedirect",
+    "LaserBlock",
+    "MirrorReflect",
+    "CartMove",
+    "RotTurnableInertia",
+    "RotBoardInertia",
+    "LinCarryInertia",
+    "CatapultLaunch",
+    "ChainSuspend",
+    "SimplePendulum",
+    "DoublePendulum",
+    "CrankPush",
+    "BlockWallCollapse",
+    "StickSupportFail",
+    "FloatOnLiquid",
+    "DropInLiquid",
+    "MovingObjDriveLiquid",
+    "LiquidCarryMovingObj",
+    "LiquidHitFixedObj",
+    "LiquidTransfer",
+    "LiquidMultiTransfers",
+    "LiquidThroughGrid",
+    "LiquidAcrossUneven",
+    "LiquidRise",
+    "LiquidAlongContours",
+    "JetLiquid",
+    "LiquidTension",
+    "LiquidRefraction",
+    "StickyToObjects",
+    "StickyFromObjects",
+    "ElasticFall",
+    "PlasticineFall",
+    "NewtonianFluidFall",
+    "NonNewtonianFluidFall",
+    "GranularFall",
+}
+
+
+SPLIT_ALIASES = {
+    "train": "Train",
+    "val": "Val",
+    "validation": "Val",
+    "test": "Test",
+}
+
+ACTIVITY_ALIASES = {
+    "single": "SinglePhysics",
+    "singlephysics": "SinglePhysics",
+    "double": "DoublePhysics",
+    "doublephysics": "DoublePhysics",
+    "triple": "TriplePhysics",
+    "triplephysics": "TriplePhysics",
+}
+
+
+@dataclass
+class CaseRecord:
+    case_id: str
+    split: str
+    activity_type: str
+    phenomena: list[str]
+    background: str
+    hash: str
+    ue_path: str
+    part_id: str
+    hf_zip_path: str
+
+
+def normalize_split(value: str | None) -> str | None:
+    if value is None:
+        return None
+    key = value.strip().lower()
+    if key not in SPLIT_ALIASES:
+        raise ValueError(
+            f"Unknown split '{value}'. Expected one of: train, val, test."
+        )
+    return SPLIT_ALIASES[key]
+
+
+def normalize_activity(value: str | None) -> str | None:
+    if value is None:
+        return None
+    key = value.strip().lower()
+    if key not in ACTIVITY_ALIASES:
+        raise ValueError(
+            f"Unknown activity_type '{value}'. Expected one of: single, double, triple."
+        )
+    return ACTIVITY_ALIASES[key]
+
+
+def validate_phenomena(values: list[str] | None) -> list[str] | None:
+    if not values:
+        return values
+
+    invalid = sorted(set(values) - SUPPORTED_PHENOMENA)
+    if invalid:
+        valid_preview = ", ".join(sorted(SUPPORTED_PHENOMENA))
+        raise ValueError(
+            "Unsupported phenomenon abbreviation(s): "
+            + ", ".join(invalid)
+            + "\nExpected one or more of the 71 supported abbreviations:\n"
+            + valid_preview
+        )
+    return values
+
+
+def parse_case_line(line: str, line_no: int) -> CaseRecord | None:
+    line = line.strip()
+    if not line or line.startswith("#"):
+        return None
+
+    parts = re.split(r"\s+", line, maxsplit=1)
+    if len(parts) != 2:
+        raise ValueError(f"Line {line_no}: expected two columns: <ue_path> <part_id>")
+
+    ue_path, part_id = parts[0], parts[1].strip()
+    path_parts = ue_path.split("/")
+
+    try:
+        scenes_idx = path_parts.index("Scenes")
+        split = path_parts[scenes_idx + 1]
+        activity_type = path_parts[scenes_idx + 2]
+        object_ref = path_parts[scenes_idx + 3]
+    except (ValueError, IndexError) as exc:
+        raise ValueError(f"Line {line_no}: cannot parse UE path: {ue_path}") from exc
+
+    if split not in {"Train", "Val", "Test"}:
+        raise ValueError(
+            f"Line {line_no}: unsupported split '{split}' in assignment file. "
+            "Expected Train, Val, or Test."
+        )
+
+    if activity_type not in {"SinglePhysics", "DoublePhysics", "TriplePhysics"}:
+        raise ValueError(
+            f"Line {line_no}: unsupported activity type '{activity_type}' in assignment file. "
+            "Expected SinglePhysics, DoublePhysics, or TriplePhysics."
+        )
+
+    case_id = object_ref.split(".")[-1]
+
+    if "__" not in case_id:
+        raise ValueError(f"Line {line_no}: cannot parse case_id: {case_id}")
+
+    tokens = case_id.split("__")
+    phenomenon_token = tokens[0]
+    phenomena = phenomenon_token.split("_") if phenomenon_token else []
+
+    invalid_in_file = sorted(set(phenomena) - SUPPORTED_PHENOMENA)
+    if invalid_in_file:
+        raise ValueError(
+            f"Line {line_no}: assignment file contains unsupported phenomenon "
+            f"abbreviation(s): {', '.join(invalid_in_file)} in case_id {case_id}"
+        )
+
+    expected_count = {
+        "SinglePhysics": 1,
+        "DoublePhysics": 2,
+        "TriplePhysics": 3,
+    }[activity_type]
+    if len(phenomena) != expected_count:
+        raise ValueError(
+            f"Line {line_no}: activity type {activity_type} expects "
+            f"{expected_count} phenomenon abbreviation(s), but got {len(phenomena)} "
+            f"in case_id {case_id}"
+        )
+
+    background = ""
+    hash_code = ""
+    for token in tokens[1:]:
+        if re.fullmatch(r"bg\d+", token):
+            background = token
+        else:
+            hash_code = token
+
+    if not background:
+        raise ValueError(f"Line {line_no}: background token not found in case_id: {case_id}")
+    if not hash_code:
+        raise ValueError(f"Line {line_no}: hash token not found in case_id: {case_id}")
+
+    hf_zip_path = f"{split}/{activity_type}/{case_id}_trajectory.zip"
+
+    return CaseRecord(
+        case_id=case_id,
+        split=split,
+        activity_type=activity_type,
+        phenomena=phenomena,
+        background=background,
+        hash=hash_code,
+        ue_path=ue_path,
+        part_id=part_id,
+        hf_zip_path=hf_zip_path,
+    )
+
+
+def load_assignment(path: Path) -> list[CaseRecord]:
+    if not path.exists():
+        raise FileNotFoundError(
+            f"Assignment file not found: {path}\n"
+            f"Put repo_assignment.txt at {DEFAULT_ASSIGNMENT_FILE} or pass --assignment_file."
+        )
+
+    records: list[CaseRecord] = []
+    with path.open("r", encoding="utf-8") as f:
+        for line_no, line in enumerate(f, start=1):
+            record = parse_case_line(line, line_no)
+            if record is not None:
+                records.append(record)
+    return records
+
+
+def record_matches_phenomena(
+    record: CaseRecord,
+    requested: Iterable[str] | None,
+    match_mode: Literal["contains", "exact"],
+) -> bool:
+    requested_list = list(requested or [])
+    if not requested_list:
+        return True
+
+    requested_set = set(requested_list)
+    record_set = set(record.phenomena)
+
+    if match_mode == "contains":
+        return requested_set.issubset(record_set)
+    if match_mode == "exact":
+        return requested_set == record_set
+
+    raise ValueError(f"Unsupported match_mode: {match_mode}")
+
+
+def filter_records(
+    records: list[CaseRecord],
+    split: str | None = None,
+    activity_type: str | None = None,
+    phenomena: list[str] | None = None,
+    match_mode: Literal["contains", "exact"] = "contains",
+) -> list[CaseRecord]:
+    split_norm = normalize_split(split)
+    activity_norm = normalize_activity(activity_type)
+    phenomena = validate_phenomena(phenomena)
+
+    out = []
+    for record in records:
+        if split_norm is not None and record.split != split_norm:
+            continue
+        if activity_norm is not None and record.activity_type != activity_norm:
+            continue
+        if not record_matches_phenomena(record, phenomena, match_mode):
+            continue
+        out.append(record)
+    return out
+
+
+def build_stats(records: list[CaseRecord]) -> dict:
+    stats: dict = {
+        "num_cases": len(records),
+        "by_split": {},
+        "by_activity_type": {},
+        "by_part": {},
+    }
+    for r in records:
+        stats["by_split"][r.split] = stats["by_split"].get(r.split, 0) + 1
+        stats["by_activity_type"][r.activity_type] = stats["by_activity_type"].get(r.activity_type, 0) + 1
+        stats["by_part"][r.part_id] = stats["by_part"].get(r.part_id, 0) + 1
+    return stats
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser(description="Filter PhysInOne cases.")
+    parser.add_argument(
+        "--assignment_file",
+        type=Path,
+        default=DEFAULT_ASSIGNMENT_FILE,
+        help=f"Path to repo_assignment.txt. Default: {DEFAULT_ASSIGNMENT_FILE}",
+    )
+    parser.add_argument("--split", type=str, default=None, help="train, val, or test.")
+    parser.add_argument(
+        "--activity_type",
+        type=str,
+        default=None,
+        help="single, double, or triple.",
+    )
+    parser.add_argument(
+        "--phenomena",
+        nargs="*",
+        default=None,
+        help="One or more phenomenon abbreviations, e.g. AccelConcaveSpin FrictionStop.",
+    )
+    parser.add_argument(
+        "--match_mode",
+        choices=["contains", "exact"],
+        default="contains",
+        help=(
+            "contains: selected cases contain all requested phenomena; "
+            "exact: selected cases have exactly the requested phenomena. "
+            "Order is ignored in both modes."
+        ),
+    )
+    parser.add_argument(
+        "--num",
+        type=int,
+        default=None,
+        help="Global number of cases to sample after filtering. Default: keep all matches.",
+    )
+    parser.add_argument(
+        "--seed",
+        type=int,
+        default=42,
+        help="Random seed used when --num is specified. Default: 42.",
+    )
+    parser.add_argument(
+        "--output",
+        type=Path,
+        default=Path("selected_cases.json"),
+        help="Output JSON path. Default: selected_cases.json",
+    )
+    parser.add_argument(
+        "--show_stats",
+        action="store_true",
+        help="Print dataset/filtering statistics.",
+    )
+
+    args = parser.parse_args()
+
+    records = load_assignment(args.assignment_file)
+    matches = filter_records(
+        records,
+        split=args.split,
+        activity_type=args.activity_type,
+        phenomena=args.phenomena,
+        match_mode=args.match_mode,
+    )
+
+    if args.num is not None:
+        if args.num < 0:
+            raise ValueError("--num must be non-negative.")
+        rng = random.Random(args.seed)
+        if args.num < len(matches):
+            matches = rng.sample(matches, args.num)
+
+    result = {
+        "filters": {
+            "split": args.split,
+            "activity_type": args.activity_type,
+            "phenomena": args.phenomena or [],
+            "match_mode": args.match_mode,
+            "num": args.num,
+            "seed": args.seed,
+        },
+        "stats": build_stats(matches),
+        "cases": [asdict(r) for r in matches],
+    }
+
+    args.output.parent.mkdir(parents=True, exist_ok=True)
+    args.output.write_text(json.dumps(result, indent=2, ensure_ascii=False), encoding="utf-8")
+
+    print(f"Matched cases: {len(matches)}")
+    print(f"Saved selection to: {args.output}")
+    if args.show_stats:
+        print(json.dumps(result["stats"], indent=2, ensure_ascii=False))
+
+
+if __name__ == "__main__":
+    main()