
# Instruction-prompted low-level image processing dataset

To construct this dataset, we took different number of samples from the following datasets for each task and constructed
a single dataset with prompts added like so:

| **Task** | **Prompt** | **Dataset** | **Number of samples** |
|---|---|---|---|
| Deblurring | “deblur the blurry image” | REDS (train_blur  and<br> train_sharp) | 1200 |
| Deraining | “derain the image” | Rain13k | 686 |
| Denoising | “denoise the noisy image” | SIDD | 8 |
| Low-light  <br>image enhancement | "enhance the low-light image” | LOL | 23 |

To know more about how this sampling was performed, refer to [this notebook](https://huggingface.co/datasets/instruction-tuning-sd/low-level-image-proc/blob/main/data_preparation/sample_dataset.ipynb).This notebook outputs a CSV file which was then used for generating the final version of the dataset ([notebook](https://huggingface.co/datasets/instruction-tuning-sd/low-level-image-proc/blob/main/data_preparation/final_data_preparation.ipynb)).

## Known limitations and biases

Since this dataset was derived from various datasets, as mentioned above, it inherits their limitations and biases as well. 

## Licensing

Since this dataset was derived from various datasets, as mentioned above, it inherits the licensing policies of those datasets. 
task_categories:image-to-image size_categories:1K<n<10K language:en region:us
{"language": ["en"], "size_categories": ["1K<n<10K"], "task_categories": ["image-to-image"], "dataset_info": {"features": [{"name": "instruction", "dtype": "string"}, {"name": "input_image", "dtype": "image"}, {"name": "ground_truth_image", "dtype": "image"}], "splits": [{"name": "train", "num_bytes": 3463030772.619, "num_examples": 1917}], "download_size": 3528678684, "dataset_size": 3463030772.619}}
TAGS
#task_categories-image-to-image #size_categories-1K<n<10K #language-English #region-us 

Instruction-prompted low-level image processing dataset
=======================================================


To construct this dataset, we took different number of samples from the following datasets for each task and constructed
a single dataset with prompts added like so:



To know more about how this sampling was performed, refer to this notebook.This notebook outputs a CSV file which was then used for generating the final version of the dataset (notebook).


Known limitations and biases
----------------------------


Since this dataset was derived from various datasets, as mentioned above, it inherits their limitations and biases as well.


Licensing
---------


Since this dataset was derived from various datasets, as mentioned above, it inherits the licensing policies of those datasets.



TAGS
#task_categories-image-to-image #size_categories-1K<n<10K #language-English #region-us 

passage: TAGS
#task_categories-image-to-image #size_categories-1K<n<10K #language-English #region-us 
