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dataset_info:
config_name: robometer_failure_detection
features:
- name: id
dtype: string
- name: task
dtype: string
- name: lang_vector
list: float32
- name: data_source
dtype: string
- name: frames
dtype: string
- name: is_robot
dtype: bool
- name: quality_label
dtype: string
- name: preference_group_id
dtype: 'null'
- name: preference_rank
dtype: 'null'
- name: partial_success
dtype: 'null'
splits:
- name: train
num_bytes: 175273
num_examples: 100
download_size: 28483
dataset_size: 175273
configs:
- config_name: robometer_failure_detection
data_files:
- split: train
path: robometer_failure_detection/train-*
---
# Robometer Failure Detection Dataset
The exact **100 videos** that the reported Robometer failure-detection results are
computed on: 81 trajectories across 7 tasks, external and wrist views (43 ext / 57
wrist), labels `successful` / `suboptimal` / `failure` (suboptimal counted as failure
at evaluation time).
Tasks: foldtowel, movebanana, movemouse, pourpebble, pulltissue, putspoon, stirpot.
## Metric note
Reported F1 uses **failure as the positive class**, and the "Average" row is pooled over
all videos (not a macro-average over tasks).
## Usage
```python
from datasets import load_dataset
ds = load_dataset("myconnects/robometer_failure_detection",
"robometer_failure_detection", split="train")
```
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