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---
title: CIDEr
tags:
- evaluate
- metric
description: "CIDEr (Consensus-based Image Description Evaluation) is a metric used to evaluate the quality of image captions by measuring their similarity to human-generated reference captions."
sdk: gradio
sdk_version: 5.45.0
app_file: app.py
pinned: false
---
# Metric Card for CIDEr
***Module Card Instructions:*** *This module implements the CIDEr metric for image captioning evaluation.*
## Metric Description
CIDEr (Consensus-based Image Description Evaluation) is a metric used to evaluate the quality of image captions by measuring their similarity to human-generated reference captions. It does this by comparing the n-grams of the candidate caption to the n-grams of the reference captions, and measuring how many n-grams are shared between the candidate and the references.
## How to Use
*To use this metric, you can call the `compute` method with the following parameters:*
### Inputs
- **predictions** *(batch of list of strings): The generated captions to evaluate.*
- **references** *(batch of list of strings): The reference captions for each generated caption.*
### Output Values
- **score** *(dict): The CIDEr score, which ranges from 0 to 1, with higher scores indicating better quality captions.*
### Examples
```python
import evaluate
metric = evaluate.load("sunhill/cider")
results = metric.compute(
predictions=[["train traveling down a track in front of a road"]],
references=[
[
"a train traveling down tracks next to lights",
"a blue and silver train next to train station and trees",
"a blue train is next to a sidewalk on the rails",
"a passenger train pulls into a train station",
"a train coming down the tracks arriving at a station",
]
]
)
print(results)
```
## Citation
```bibtex
@InProceedings{Vedantam_2015_CVPR,
author = {Vedantam, Ramakrishna and Lawrence Zitnick, C. and Parikh, Devi},
title = {CIDEr: Consensus-Based Image Description Evaluation},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2015}
}
```
## Further References
- [CIDEr](https://github.com/ramavedantam/cider)
- [Image Caption Metrics](https://github.com/EricWWWW/image-caption-metrics)
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