Implementation:Open compass VLMEvalKit InsightV
| Field | Value |
|---|---|
| source | VLMEvalKit |
| domain | Vision, Model_Architecture |
Overview
VLM adapter for the Insight-V model enabling benchmark evaluation in VLMEvalKit.
Description
InsightV inherits from BaseModel and wraps the Insight-V model for use within the VLMEvalKit evaluation framework. It initializes the model and tokenizer/processor from a HuggingFace model path (default: THUdyh/Insight-V-Reason-LLaMA3) and provides the generate_inner method for inference. Uses a two-stage architecture with separate reasoning and summary models.
Usage
Register in vlmeval/config.py via supported_VLM and invoke through the standard evaluation pipeline.
Code Reference
- Source:
vlmeval/vlm/insight_v.py, Lines: L1-245 - Import:
from vlmeval.vlm.insight_v import InsightV
Signature:
class InsightV(BaseModel):
INSTALL_REQ = True
INTERLEAVE = False
def __init__(self, model_path='THUdyh/Insight-V-Reason-LLaMA3', **kwargs): ...
def generate_inner(self, message, dataset=None): ...
I/O Contract
| Direction | Description |
|---|---|
| Inputs | message — list of dicts with type (text/image) and value; dataset — optional dataset name for custom prompting |
| Outputs | generate_inner() returns str (model response text) |
Usage Examples
from vlmeval.vlm.insight_v import InsightV
model = InsightV(model_path='path/to/model')
response = model.generate_inner(message)