> ## Documentation Index
> Fetch the complete documentation index at: https://docs.qwedai.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Image engine

> QWED's Image Engine verifies image claims using deterministic metadata extraction first, with multi-VLM consensus fallback for complex semantic claims.

The Image Engine verifies claims about images using **deterministic methods first**, with VLM fallback only for complex semantic claims.

## Features

* **Metadata extraction** — dimensions and format (PNG, JPEG, GIF, WebP)
* **Size verification** — exact dimension comparison from metadata
* **Claim classification** — routes claims to the appropriate verifier
* **Multi-VLM consensus** — cross-validates semantic claims

## Usage

```python theme={null}
from qwed_sdk import QWEDClient

client = QWEDClient(api_key="qwed_...")

# Read image
with open("chart.png", "rb") as f:
    image_bytes = f.read()

# Verify claim
result = client.verify_image(
    image=image_bytes,
    claim="The image is 800x600 pixels"
)

print(result.verdict)      # "SUPPORTED" or "REFUTED"
print(result.confidence)   # 1.0 (deterministic!)
print(result.methods_used) # ["metadata_extraction", "size_verification"]
```

## Claim types

| Claim Type      | Method           | Deterministic? |
| --------------- | ---------------- | -------------- |
| Size/Dimensions | Metadata parsing | ✅ 100%         |
| Format          | Header detection | ✅ 100%         |
| Color           | Pixel sampling   | ⚠️ Partial     |
| Text            | OCR required     | ❌ VLM          |
| Semantic        | Understanding    | ❌ VLM          |

## Multi-VLM consensus

For semantic claims, use multiple VLMs:

```python theme={null}
result = client.verify_image_consensus(
    image=image_bytes,
    claim="The person is smiling",
    min_agreement=2  # At least 2 VLMs must agree
)

print(result.agreement_count)  # 3/3
print(result.vlm_results)      # Individual VLM responses
```

## Supported providers for image verification

The Image Engine supports multimodal verification through any provider that accepts image inputs. When you set `ACTIVE_PROVIDER=gemini`, QWED uses Google Gemini's native multimodal capabilities for semantic image claims. Supported image formats are JPEG, PNG, and WebP.

```bash theme={null}
export ACTIVE_PROVIDER=gemini
export GOOGLE_API_KEY=your-google-api-key
```

See [LLM configuration](/getting-started/llm-configuration#google-gemini) for full setup instructions.