Update dataset card metadata, paper link and usage

README.md

@@ -1,18 +1,20 @@
 ---
-license: cc-by-nc-sa-4.0
 language:
 - en
+license: cc-by-nc-sa-4.0
+task_categories:
+- other
 ---
 
 # OWM Benchmark
 
 [![Project Page](https://img.shields.io/badge/Project-Page-blue)](https://compvis.github.io/myriad)
-[![Paper](https://img.shields.io/badge/arXiv-paper-b31b1b)](https://arxiv.org/abs/2604.09527)
+[![Paper](https://img.shields.io/badge/arXiv-paper-b31b1b)](https://huggingface.co/papers/2604.09527)
 [![MYRIAD Weights](https://img.shields.io/badge/HuggingFace-Weights-orange)](https://huggingface.co/CompVis/myriad)
 
 ## Abstract
 
-The OWM benchmark was proposed in the paper [Envisioning the Future, One Step at a Time](_blank) and used to evaluate the [MYRIAD](https://huggingface.co/CompVis/myriad/) model.
+The OWM benchmark was proposed in the paper [Envisioning the Future, One Step at a Time](https://huggingface.co/papers/2604.09527) and used to evaluate the [MYRIAD](https://huggingface.co/CompVis/myriad/) model.
 
 OWM is a benchmark of 95 curated videos with motion annotations, with the distribution of motion constrained to enable the evaluation of probabilistic motion prediction methods.
 Videos are obtained from Pexels ([Pexels License](https://www.pexels.com/license/)). We manually annotate relevant objects and the type of motion observed. We use an off-the-shelf tracker to obtain motion trajectories and manually verify correctness.
@@ -24,21 +26,23 @@ Videos are obtained from Pexels ([Pexels License](https://www.pexels.com/license
 
 ![OWM samples](https://compvis.github.io/myriad/static/images/paper-svg/owm-qualitative.svg)
 
-*OWM samples are include complex real-world scenes with different motion types and complexities.*
+*OWM samples include complex real-world scenes with different motion types and complexities.*
 
 ## Usage
 
 We provide code to run the OWM evaluation in our [GitHub repository](https://github.com/CompVis/flow-poke-transformer).
 
-To run the evaluation, first download the data by running `hf download CompVis/owm-95 --repo-type dataset` then run the evaluation script via
+To run the evaluation, first download the data by running `hf download CompVis/owm-95 --repo-type dataset`.
+
+Then run the evaluation script via:
 ```shell
-python -m scripts.eval.myriad_eval.openset_prediction --checkpoint-path path/to/checkpoint  -data-path path/to/data
+python -m scripts.myriad_eval.openset_prediction --data-root path/to/data --ckpt-path path/to/checkpoint --dataset-name owm
 ```
 
 ## License
 
 - Videos are sourced from Pexels and thus licensed under the [Pexels License](https://www.pexels.com/license/)
-- Metadata and motion annotations are provided under the [CC-BY-NC-SA-44.0](https://creativecommons.org/licenses/by-nc-sa/4.0/deed.en) license
+- Metadata and motion annotations are provided under the [CC-BY-NC-SA-4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/deed.en) license
 
 ## Citation