Datasets:
Tasks:
Image Classification
Modalities:
Image
Formats:
parquet
Sub-tasks:
multi-class-image-classification
Languages:
English
Size:
10K - 100K
License:
Upload README.md with huggingface_hub
Browse files
README.md
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---
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dataset_info:
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features:
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- name: image
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names:
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'0': dusty
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'1': not_dusty
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splits:
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- name: train
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num_bytes: 59643675.57
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num_examples: 9817
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- name: test
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num_bytes: 30537421.308
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num_examples: 5214
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- name: val
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num_bytes: 14924222.586
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num_examples: 2454
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download_size: 201145587
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dataset_size: 190138811.01999998
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configs:
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- config_name: default
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data_files:
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- split: train
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path: data/train-*
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- split: test
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path: data/test-*
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- split: val
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path: data/val-*
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- split: few_shot_train_2_shot
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path: data/few_shot_train_2_shot-*
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- split: few_shot_train_1_shot
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path: data/few_shot_train_1_shot-*
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- split: few_shot_train_10_shot
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path: data/few_shot_train_10_shot-*
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- split: few_shot_train_5_shot
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path: data/few_shot_train_5_shot-*
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- split: few_shot_train_15_shot
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path: data/few_shot_train_15_shot-*
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- split: few_shot_train_20_shot
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path: data/few_shot_train_20_shot-*
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- split: partition_train_0.01x_partition
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path: data/partition_train_0.01x_partition-*
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- split: partition_train_0.02x_partition
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path: data/partition_train_0.02x_partition-*
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- split: partition_train_0.50x_partition
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path: data/partition_train_0.50x_partition-*
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- split: partition_train_0.20x_partition
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path: data/partition_train_0.20x_partition-*
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- split: partition_train_0.05x_partition
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path: data/partition_train_0.05x_partition-*
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- split: partition_train_0.10x_partition
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path: data/partition_train_0.10x_partition-*
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- split: partition_train_0.25x_partition
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path: data/partition_train_0.25x_partition-*
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---
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---
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annotations_creators:
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- expert-generated
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language_creators:
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- found
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language:
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- en
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license:
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- cc-by-4.0
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multilinguality:
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- monolingual
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size_categories:
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- 10K<n<100K
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source_datasets:
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- original
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task_categories:
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- image-classification
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task_ids:
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- multi-class-image-classification
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pretty_name: mb-atmospheric_dust_cls_rdr_upd
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dataset_info:
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features:
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- name: image
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names:
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'0': dusty
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'1': not_dusty
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---
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# mb-atmospheric_dust_cls_rdr_upd
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A Mars image classification dataset for planetary science research.
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## Dataset Metadata
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* **License:** CC-BY-4.0 (Creative Commons Attribution 4.0 International)
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* **Version:** 1.0
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* **Date Published:** 2025-05-22
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* **Cite As:** TBD
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## Classes
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This dataset contains the following classes:
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- 0: dusty
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- 1: not_dusty
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## Statistics
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- **train**: 9817 images
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- **test**: 5214 images
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- **val**: 4969 images
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- **few_shot_train_2_shot**: 4 images
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- **few_shot_train_1_shot**: 2 images
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- **few_shot_train_10_shot**: 20 images
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- **few_shot_train_5_shot**: 10 images
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- **few_shot_train_15_shot**: 30 images
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- **few_shot_train_20_shot**: 40 images
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- **partition_train_0.01x_partition**: 98 images
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- **partition_train_0.02x_partition**: 196 images
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- **partition_train_0.50x_partition**: 4908 images
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- **partition_train_0.20x_partition**: 1963 images
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- **partition_train_0.05x_partition**: 490 images
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- **partition_train_0.10x_partition**: 981 images
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- **partition_train_0.25x_partition**: 2454 images
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## Few-shot Splits
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This dataset includes the following few-shot training splits:
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- **few_shot_train_2_shot**: 4 images
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- **few_shot_train_1_shot**: 2 images
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- **few_shot_train_10_shot**: 20 images
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- **few_shot_train_5_shot**: 10 images
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- **few_shot_train_15_shot**: 30 images
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- **few_shot_train_20_shot**: 40 images
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Few-shot configurations:
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- **2_shot.csv**
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- **1_shot.csv**
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- **10_shot.csv**
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- **5_shot.csv**
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- **15_shot.csv**
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- **20_shot.csv**
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## Partition Splits
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This dataset includes the following training data partitions:
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- **partition_train_0.01x_partition**: 98 images
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- **partition_train_0.02x_partition**: 196 images
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- **partition_train_0.50x_partition**: 4908 images
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- **partition_train_0.20x_partition**: 1963 images
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- **partition_train_0.05x_partition**: 490 images
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- **partition_train_0.10x_partition**: 981 images
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- **partition_train_0.25x_partition**: 2454 images
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## Usage
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```python
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from datasets import load_dataset
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dataset = load_dataset("Mirali33/mb-atmospheric_dust_cls_rdr_upd")
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```
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## Format
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Each example in the dataset has the following format:
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```
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{
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'image': Image(...), # PIL image
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'label': int, # Class label
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}
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```
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