Datasets:
Tasks:
Image Segmentation
Formats:
parquet
Sub-tasks:
semantic-segmentation
Languages:
English
Size:
10K - 100K
License:
Upload README.md with huggingface_hub
Browse files
README.md
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---
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- name: test
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num_bytes: 195648039.0
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num_examples: 800
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- name: partition_train_0.01x_partition
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num_bytes: 12489245.28176906
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num_examples: 49
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- name: partition_train_0.02x_partition
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num_bytes: 23978243.30398239
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num_examples: 99
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- name: partition_train_0.50x_partition
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num_bytes: 603306584.4177778
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num_examples: 2498
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- name: partition_train_0.20x_partition
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num_bytes: 238526608.70382228
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num_examples: 999
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- name: partition_train_0.05x_partition
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num_bytes: 59511811.370622374
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num_examples: 249
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- name: partition_train_0.10x_partition
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num_bytes: 120259686.481689
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num_examples: 499
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- name: partition_train_0.25x_partition
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num_bytes: 298766137.53188896
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num_examples: 1249
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download_size: 2784453000
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dataset_size: 2799662250.130552
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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: val
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path: data/val-*
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- split: test
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path: data/test-*
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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-segmentation
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task_ids:
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- semantic-segmentation
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pretty_name: mb-s5mars
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---
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# mb-s5mars
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A segmentation dataset for planetary science applications.
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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:** 2025-05-15
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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: Background
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- 1: Bedrock
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- 2: Hole
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- 3: Ridge
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- 4: Rock
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- 5: Rover
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- 6: Sand / Soil
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- 7: Sky
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- 8: Track
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## Directory Structure
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The dataset follows this structure:
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```
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dataset/
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├── train/
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│ ├── images/ # Image files
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│ └── masks/ # Segmentation masks
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├── val/
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│ ├── images/ # Image files
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│ └── masks/ # Segmentation masks
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├── test/
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│ ├── images/ # Image files
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│ └── masks/ # Segmentation masks
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```
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## Statistics
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- train: 4997 images
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- val: 200 images
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- test: 800 images
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- partition_train_0.01x_partition: 49 images
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- partition_train_0.02x_partition: 99 images
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- partition_train_0.50x_partition: 2498 images
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- partition_train_0.20x_partition: 999 images
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- partition_train_0.05x_partition: 249 images
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- partition_train_0.10x_partition: 499 images
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- partition_train_0.25x_partition: 1249 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-s5mars")
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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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'mask': Image(...), # PIL image of the segmentation mask
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'width': int, # Width of the image
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'height': int, # Height of the image
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'class_labels': [str,...] # List of class names present in the mask
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}
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```
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