| --- |
| license: mit |
| task_categories: |
| - visual-question-answering |
| - multiple-choice |
| language: |
| - en |
| pretty_name: VideoColorBench |
| size_categories: |
| - n<1K |
| configs: |
| - config_name: films |
| data_files: |
| - split: test |
| path: films/test-* |
| - config_name: youtube |
| data_files: |
| - split: test |
| path: youtube/test-* |
| --- |
| |
| # VideoColorBench |
|
|
| Can a model recognize a famous video from just its colors? |
|
|
| Each image is a barcode of one video. Every stripe is the average color of a few seconds, in order from start to end. The model picks which video it is out of 10 options, so guessing gets 10%. |
|
|
| | config | questions | what's in it | |
| |--------|-----------|--------------| |
| | `films` | 100 | feature films | |
| | `youtube` | 100 | the most viewed YouTube videos, mostly music videos | |
|
|
| ```python |
| from datasets import load_dataset |
| ds = load_dataset("loganbolton/VideoColorBench", "films", split="test") |
| ds[0]["image"], ds[0]["choices"], ds[0]["answer"] |
| ``` |
|
|
| ## Fields |
|
|
| | field | meaning | |
| |-------|---------| |
| | `image` | the barcode, 1000x200 PNG | |
| | `choices` | the 10 options | |
| | `answer`, `answer_index`, `answer_title` | the right option as a letter (A to J), an index (0 to 9) and text | |
| | `title`, `artist`, `year`, `genre` | about the video | |
| | `average_color` | mean color of the whole video as hex | |
| | `colorfulness` | how saturated the video is, near 0 for black and white | |
| | `seconds` | runtime | |
| | `source_url` | where the video came from | |
|
|
| The wrong options are picked to be plausible. Same genre, close in year, similar colorfulness. |
|
|
| ## Running a model |
|
|
| The code is at https://github.com/LoganBolton/VideoColorBench. Any OpenRouter model runs with one command. |
|
|
| ```bash |
| export OPENROUTER_API_KEY=sk-or-... |
| uv run run.py --model openai/gpt-6.1-sol |
| ``` |
|
|
| Only barcodes are shared here, no frames from the videos. |
|
|
