111 lines
2.4 KiB
Markdown
111 lines
2.4 KiB
Markdown
# TIFA-160
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## Overview
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TIFA-160 is a text-to-image benchmark with 160 carefully curated prompts designed to evaluate the faithfulness and quality of generated images using automated VQA-based evaluation.
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## Task Description
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- **Task Type**: Text-to-Image Generation Evaluation
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- **Input**: Text prompt for image generation
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- **Output**: Generated image evaluated using PickScore metric
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- **Size**: 160 prompts
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## Key Features
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- Compact, high-quality prompt set for efficient evaluation
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- Uses PickScore for human preference alignment
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- Tests diverse image generation capabilities
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- Supports both new generation and pre-existing image evaluation
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- Reproducible evaluation pipeline
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## Evaluation Notes
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- Default configuration uses **0-shot** evaluation
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- Primary metric: **PickScore** for human preference alignment
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- Evaluates images from the **test** split
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- Part of the T2V-Eval-Prompts dataset collection
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## Properties
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| Property | Value |
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|----------|-------|
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| **Benchmark Name** | `tifa160` |
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| **Dataset ID** | [AI-ModelScope/T2V-Eval-Prompts](https://modelscope.cn/datasets/AI-ModelScope/T2V-Eval-Prompts/summary) |
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| **Paper** | N/A |
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| **Tags** | `TextToImage` |
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| **Metrics** | `PickScore` |
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| **Default Shots** | 0-shot |
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| **Evaluation Split** | `test` |
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## Data Statistics
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| Metric | Value |
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|--------|-------|
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| Total Samples | 160 |
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| Prompt Length (Mean) | 56.13 chars |
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| Prompt Length (Min/Max) | 13 / 182 chars |
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## Sample Example
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**Subset**: `TIFA-160`
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```json
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{
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"input": [
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{
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"id": "9de3e3b1",
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"content": "A Christmas tree with lights and teddy bear"
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}
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],
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"id": 0,
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"group_id": 0,
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"metadata": {
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"prompt": "A Christmas tree with lights and teddy bear",
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"category": "",
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"tags": {},
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"id": "TIFA160_0",
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"image_path": ""
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}
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}
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```
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## Prompt Template
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*No prompt template defined.*
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## Usage
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### Using CLI
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```bash
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evalscope eval \
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--model YOUR_MODEL \
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--api-url OPENAI_API_COMPAT_URL \
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--api-key EMPTY_TOKEN \
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--datasets tifa160 \
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--limit 10 # Remove this line for formal evaluation
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```
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### Using Python
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```python
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from evalscope import run_task
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from evalscope.config import TaskConfig
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task_cfg = TaskConfig(
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model='YOUR_MODEL',
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api_url='OPENAI_API_COMPAT_URL',
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api_key='EMPTY_TOKEN',
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datasets=['tifa160'],
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limit=10, # Remove this line for formal evaluation
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)
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run_task(task_cfg=task_cfg)
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```
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