task_categories:text-to-image annotations_creators:machine-generated size_categories:n<1K language:en region:us
---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: caption
    dtype: string
  splits:
  - name: train
    num_bytes: 171055893.125
    num_examples: 1087
  download_size: 170841790
  dataset_size: 171055893.125
language:
- en
task_categories:
- text-to-image
annotations_creators:
- machine-generated
size_categories:
- n<1K
---
# Disclaimer
This was inspired from https://huggingface.co/datasets/lambdalabs/pokemon-blip-captions

# Dataset Card for A subset of Vivian Maier's photographs BLIP captions
The captions are generated with the [pre-trained BLIP model](https://github.com/salesforce/BLIP).

For each row the dataset contains `image` and `caption` keys. `image` is a varying size PIL jpeg, and `caption` is the accompanying text caption. Only a train split is provided.

## Examples


![vv1.jpg](https://raw.githubusercontent.com/CQUEEN-lpy/cqueenccc.github.io/main/imgs/vivian_a%20group%20of%20people.jpg)
> A group of people

![vv10.jpg](https://raw.githubusercontent.com/CQUEEN-lpy/cqueenccc.github.io/main/imgs/vivian_a%20person%20floating%20in%20the%20water.jpg)
> person floating in the water

![vv100.jpg](https://raw.githubusercontent.com/CQUEEN-lpy/cqueenccc.github.io/main/imgs/vivian_a%20person%20standing%20next%20to%20a%20refrigerator.jpg)
> a person standing next to a refrigerator

## Citation

If you use this dataset, please cite it as:

```
@misc{cqueenccc2023vivian,
      author = {cQueenccc},
      title = {Vivian Maier's photograph split BLIP captions},
      year={2023},
      howpublished= {\url{https://huggingface.co/datasets/cQueenccc/Vivian-Blip-Captions/}}
} 
```