Upload README.md
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README.md
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@@ -94,6 +94,12 @@ homepage: https://vlar-group.github.io/PhysInOne.html
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font-weight: 700;
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}
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<h1 align="center" style="font-size: 42px;">PhysInOne: Visual Physics Learning and Reasoning in One Suite</h1>
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<div style="margin-left: 24px;">
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<h3 id="physical-phenomena" style="font-size: 1.35em; margin-top: 0.75em; margin-bottom: 0.22em; line-height: 1.2; margin-left: 24px;"><span style="display: inline-block; width: 1.
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<div style="margin-left: 24px;">
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PhysInOne provides synchronized visual and physical annotations for each dynamic 3D scene.
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<h3 id="depth" style="font-size: 1.35em; margin-top: 0.75em; margin-bottom: 0.22em; line-height: 1.2; margin-left: 24px;"><span style="display: inline-block; width: 1.
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<div style="margin-left: 24px;">
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</div>
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<h3 id="segmentation" style="font-size: 1.35em; margin-top: 0.75em; margin-bottom: 0.22em; line-height: 1.2; margin-left: 24px;"><span style="display: inline-block; width: 1.
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</div>
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<h3 id="captions" style="font-size: 1.35em; margin-top: 0.75em; margin-bottom: 0.22em; line-height: 1.2; margin-left: 24px;"><span style="display: inline-block; width: 1.
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<div style="margin-left: 24px;">
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</div>
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<h3 id="trajectories" style="font-size: 1.35em; margin-top: 0.75em; margin-bottom: 0.22em; line-height: 1.2; margin-left: 24px;"><span style="display: inline-block; width: 1.
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</div>
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<h3 id="cameras" style="font-size: 1.35em; margin-top: 0.75em; margin-bottom: 0.22em; line-height: 1.2; margin-left: 24px;"><span style="display: inline-block; width: 1.
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<div style="margin-left: 24px;">
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- Taichi-based MPM simulations (elastic solids, plasticine, granular substances, some Newtonian and Non-Newtonian fluids): 15 static cameras + 1 dynamic camera
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- Other scenes: 12 static cameras + 1 dynamic camera
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<h5 id="camera-json-structure" style="font-size: 1.02em; margin-top: 0.55em; margin-bottom: 0.12em; line-height: 1.16; font-weight: 700; margin-left: 0;"><span style="display: inline-block; width: 1.
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<div style="margin-left: 18px;">
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</div>
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<h5 id="dynamic-camera-behavior" style="font-size: 1.02em; margin-top: 0.55em; margin-bottom: 0.12em; line-height: 1.16; font-weight: 700; margin-left: 0;"><span style="display: inline-block; width: 1.
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</div>
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<h3 id="point-clouds" style="font-size: 1.35em; margin-top: 0.75em; margin-bottom: 0.22em; line-height: 1.2; margin-left: 24px;"><span style="display: inline-block; width: 1.
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Please download the `assets` folder, which contains:
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```text
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metadata/
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repo_assignment.txt
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filter_cases.py
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download.py
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```
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</div>
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<div style="margin-left: 24px;">
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```bash
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pip install huggingface_hub tqdm
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```
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</div>
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By default, phenomenon matching uses `contains` mode. For example, the following command selects all double-physics cases that contain `FrictionStop`:
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```bash
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python scripts/filter_cases.py \
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--split train \
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--match_mode contains \
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--output selected_cases.json
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```
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For exact matching, use `--match_mode exact`. Order does not matter. For example, this command selects cases whose phenomenon set is exactly `{AccelConcaveSpin, AccelSurfaceSpin}`:
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```bash
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python scripts/filter_cases.py \
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--split train \
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--match_mode exact \
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--output selected_cases.json
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```
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<div style="margin-left: 24px;" data-subsection="random-sampling">
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`--num` is the global number of cases sampled after filtering. The default random seed is `42`.
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```bash
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python scripts/filter_cases.py \
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--split train \
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--seed 42 \
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--output selected_cases.json
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```
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</div>
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Each selected case is downloaded as a zip file from the corresponding Hugging Face shard repository.
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```bash
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python scripts/download.py \
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--selection selected_cases.json \
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--output_dir ./PhysInOne
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```
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If the dataset repositories are gated or private, pass a Hugging Face token:
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```bash
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python scripts/download.py \
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--selection selected_cases.json \
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--output_dir ./PhysInOne \
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--token YOUR_HF_TOKEN
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```
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By default, downloaded zip files are saved into a flat output folder. To preserve shard/split/activity structure:
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```bash
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python scripts/download.py \
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--selection selected_cases.json \
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--output_dir ./PhysInOne \
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--keep_shard_structure
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```
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The preserved structure is:
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```text
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PhysInOne/
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physinone_part1/
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DoublePhysics/
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AccelConcaveSpin_AccelSurfaceSpin__bg070__K5ER39_trajectory.zip
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```
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</div>
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If you use PhysInOne in your research, please cite:
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```bibtex
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@article{zhou2026physinone,
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title={PhysInOne: Visual Physics Learning and Reasoning in One Suite},
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year={2026}
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}
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```
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</div>
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line-height: 1.16;
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font-weight: 700;
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}
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margin-top: 0.25em;
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}
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.physinone-card p + pre {
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margin-top: 0.15em;
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}
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</style>
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<h1 align="center" style="font-size: 42px;">PhysInOne: Visual Physics Learning and Reasoning in One Suite</h1>
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<div style="margin-left: 24px;">
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<h3 id="physical-phenomena" style="font-size: 1.35em; margin-top: 0.75em; margin-bottom: 0.22em; line-height: 1.2; margin-left: 24px;"><span style="display: inline-block; width: 1.18em;">•</span>Physical Phenomenon and Abbreviations</h3>
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<div style="margin-left: 24px;">
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PhysInOne provides synchronized visual and physical annotations for each dynamic 3D scene.
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<h3 id="depth" style="font-size: 1.35em; margin-top: 0.75em; margin-bottom: 0.22em; line-height: 1.2; margin-left: 24px;"><span style="display: inline-block; width: 1.18em;">•</span>Depth</h3>
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<div style="margin-left: 24px;">
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</div>
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<h3 id="segmentation" style="font-size: 1.35em; margin-top: 0.75em; margin-bottom: 0.22em; line-height: 1.2; margin-left: 24px;"><span style="display: inline-block; width: 1.18em;">•</span>Segmentation</h3>
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<div style="margin-left: 24px;">
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</div>
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<h3 id="captions" style="font-size: 1.35em; margin-top: 0.75em; margin-bottom: 0.22em; line-height: 1.2; margin-left: 24px;"><span style="display: inline-block; width: 1.18em;">•</span>Captions</h3>
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<div style="margin-left: 24px;">
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</div>
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<h3 id="trajectories" style="font-size: 1.35em; margin-top: 0.75em; margin-bottom: 0.22em; line-height: 1.2; margin-left: 24px;"><span style="display: inline-block; width: 1.18em;">•</span>Trajectories</h3>
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<div style="margin-left: 24px;">
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</div>
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<h3 id="cameras" style="font-size: 1.35em; margin-top: 0.75em; margin-bottom: 0.22em; line-height: 1.2; margin-left: 24px;"><span style="display: inline-block; width: 1.18em;">•</span>Cameras</h3>
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<div style="margin-left: 24px;">
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- Taichi-based MPM simulations (elastic solids, plasticine, granular substances, some Newtonian and Non-Newtonian fluids): 15 static cameras + 1 dynamic camera
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- Other scenes: 12 static cameras + 1 dynamic camera
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<h5 id="camera-json-structure" style="font-size: 1.02em; margin-top: 0.55em; margin-bottom: 0.12em; line-height: 1.16; font-weight: 700; margin-left: 0;"><span style="display: inline-block; width: 1.10em;">◦</span>Camera JSON structure</h5>
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<div style="margin-left: 18px;">
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</div>
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<h5 id="dynamic-camera-behavior" style="font-size: 1.02em; margin-top: 0.55em; margin-bottom: 0.12em; line-height: 1.16; font-weight: 700; margin-left: 0;"><span style="display: inline-block; width: 1.10em;">◦</span>Dynamic camera behavior</h5>
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<div style="margin-left: 18px;">
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</div>
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<h3 id="point-clouds" style="font-size: 1.35em; margin-top: 0.75em; margin-bottom: 0.22em; line-height: 1.2; margin-left: 24px;"><span style="display: inline-block; width: 1.18em;">•</span>Point Clouds</h3>
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<div style="margin-left: 24px;">
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Please download the `assets` folder, which contains:
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<div style="margin-top: -0.35em;">
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```text
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metadata/
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repo_assignment.txt
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filter_cases.py
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download.py
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```
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</div>
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<div style="margin-left: 24px;">
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<div style="margin-top: -0.35em;">
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```bash
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pip install huggingface_hub tqdm
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```
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</div>
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</div>
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By default, phenomenon matching uses `contains` mode. For example, the following command selects all double-physics cases that contain `FrictionStop`:
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<div style="margin-top: -0.35em;">
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```bash
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python scripts/filter_cases.py \
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--split train \
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--match_mode contains \
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--output selected_cases.json
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```
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</div>
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For exact matching, use `--match_mode exact`. Order does not matter. For example, this command selects cases whose phenomenon set is exactly `{AccelConcaveSpin, AccelSurfaceSpin}`:
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<div style="margin-top: -0.35em;">
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```bash
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python scripts/filter_cases.py \
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--split train \
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--match_mode exact \
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--output selected_cases.json
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```
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</div>
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<div style="margin-left: 24px;" data-subsection="random-sampling">
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`--num` is the global number of cases sampled after filtering. The default random seed is `42`.
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<div style="margin-top: -0.35em;">
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```bash
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python scripts/filter_cases.py \
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--split train \
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--seed 42 \
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--output selected_cases.json
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```
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</div>
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</div>
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Each selected case is downloaded as a zip file from the corresponding Hugging Face shard repository.
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<div style="margin-top: -0.35em;">
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```bash
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python scripts/download.py \
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--selection selected_cases.json \
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--output_dir ./PhysInOne
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```
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</div>
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If the dataset repositories are gated or private, pass a Hugging Face token:
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<div style="margin-top: -0.35em;">
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```bash
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python scripts/download.py \
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--selection selected_cases.json \
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--output_dir ./PhysInOne \
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--token YOUR_HF_TOKEN
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```
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</div>
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By default, downloaded zip files are saved into a flat output folder. To preserve shard/split/activity structure:
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<div style="margin-top: -0.35em;">
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```bash
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python scripts/download.py \
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--selection selected_cases.json \
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--output_dir ./PhysInOne \
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--keep_shard_structure
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```
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</div>
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The preserved structure is:
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<div style="margin-top: -0.35em;">
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```text
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PhysInOne/
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physinone_part1/
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DoublePhysics/
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AccelConcaveSpin_AccelSurfaceSpin__bg070__K5ER39_trajectory.zip
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```
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</div>
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</div>
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If you use PhysInOne in your research, please cite:
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<div style="margin-top: -0.35em;">
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```bibtex
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@article{zhou2026physinone,
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title={PhysInOne: Visual Physics Learning and Reasoning in One Suite},
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year={2026}
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}
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```
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</div>
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</div>
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