Implementation:Open compass VLMEvalKit MMLongBench
| Field | Value |
|---|---|
| source | VLMEvalKit |
| domain | Vision, Benchmarking, Long Document Understanding |
Overview
Benchmark dataset implementation for MMLongBench long document understanding evaluation in VLMEvalKit.
Description
MMLongBench inherits from ImageBaseDataset and implements the MMLongBench_DOC benchmark for evaluating multimodal models on long document understanding tasks. The TYPE field is set to 'VQA'. It includes a SUPPORTED_MODELS mapping defining per-model page handling configurations and handles multi-page document processing with configurable page limits.
Usage
Registered in vlmeval/dataset/__init__.py and invoked through build_dataset() by benchmark name.
Code Reference
- Source:
vlmeval/dataset/mmlongbench.py, Lines: L1-584 - Import:
from vlmeval.dataset.mmlongbench import MMLongBench
Signature:
class MMLongBench(ImageBaseDataset):
TYPE = 'VQA'
DATASET_URL = {...}
DATASET_MD5 = {...}
SUPPORTED_MODELS = {...}
...
I/O Contract
| Direction | Description |
|---|---|
| Inputs | TSV dataset file with multi-page document images and questions |
| Outputs | Evaluation results DataFrame with document understanding scores |
Usage Examples
from vlmeval.dataset import build_dataset
dataset = build_dataset('MMLongBench_DOC')