| --- |
| license: cc-by-4.0 |
| pretty_name: COSPLAN |
| configs: |
| - config_name: Maze-E |
| data_files: |
| - split: test |
| path: checkboard/metadata.jsonl |
| - config_name: Blocksworld-E |
| data_files: |
| - split: test |
| path: blocksworld/metadata.jsonl |
| - config_name: Shuffle-E |
| data_files: |
| - split: test |
| path: imagenet/metadata.jsonl |
| - config_name: Robovqa-E |
| data_files: |
| - split: test |
| path: robovqa/metadata.jsonl |
| --- |
| |
| # COSPLAN |
|
|
| A composite visual-planning benchmark with four multiple-choice subsets. Each |
| subset is a separate config in HuggingFace `imagefolder` format (images + |
| `metadata.jsonl`). Every row has an `image`, a `prompt`, and a `correct_option` |
| (A/B/C/D). |
|
|
| All four subsets are **step-completion** tasks: given a partial sequence (with one |
| erroneous step) and an image, select the option that correctly completes the task. |
|
|
| | Config | Items | Task | |
| |--------|-------|------| |
| | `Maze-E` | 5000 | Complete the path from start to goal around obstacles | |
| | `Blocksworld-E` | 5000 | Complete the block-move sequence to the target configuration | |
| | `Shuffle-E` | 5000 | Complete the patch-swap sequence to rearrange into the target image | |
| | `Robovqa-E` | 390 | Complete the robot action sequence | |
|
|
| ## Usage |
|
|
| ```python |
| from datasets import load_dataset |
| |
| ds = load_dataset("shrg7/COSPLAN", "Blocksworld-E", split="test") |
| |
| row = ds[0] |
| print(row["prompt"], row["correct_option"]) |
| |
| # The image is decoded as a PIL.Image under the "image" column |
| img = row["image"] |
| print(img.size, img.mode) |
| img.save("example.png") # or img.show() |
| ``` |
|
|
