# 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/}}
} 
```
task_categories:text-to-image annotations_creators:machine-generated size_categories:n<1K language:en region:us
{"annotations_creators": ["machine-generated"], "language": ["en"], "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "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}}
TAGS
#task_categories-text-to-image #annotations_creators-machine-generated #size_categories-n<1K #language-English #region-us 

# Disclaimer
This was inspired from URL

# Dataset Card for A subset of Vivian Maier's photographs BLIP captions
The captions are generated with the pre-trained BLIP model.

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


!URL
> A group of people

!URL
> person floating in the water

!URL
> a person standing next to a refrigerator

If you use this dataset, please cite it as:


# Disclaimer
This was inspired from URL # Dataset Card for A subset of Vivian Maier's photographs BLIP captions
The captions are generated with the pre-trained BLIP model.

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


!URL
> A group of people

!URL
> person floating in the water

!URL
> a person standing next to a refrigerator

If you use this dataset, please cite it as:
TAGS
#task_categories-text-to-image #annotations_creators-machine-generated #size_categories-n<1K #language-English #region-us 
 # Disclaimer
This was inspired from URL # Dataset Card for A subset of Vivian Maier's photographs BLIP captions
The captions are generated with the pre-trained BLIP model.

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


!URL
> A group of people

!URL
> person floating in the water

!URL
> a person standing next to a refrigerator

If you use this dataset, please cite it as:
passage: TAGS
#task_categories-text-to-image #annotations_creators-machine-generated #size_categories-n<1K #language-English #region-us 
# Disclaimer
This was inspired from URL# Dataset Card for A subset of Vivian Maier's photographs BLIP captions
The captions are generated with the pre-trained BLIP model.

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


!URL
> A group of people

!URL
> person floating in the water

!URL
> a person standing next to a refrigerator

If you use this dataset, please cite it as: