Datasets:

weiqingma
/

OpenCAPY

task_categories:
  - image-segmentation
tags:
  - semantic-segmentation
  - capybara
  - computer-vision
  - synthetic-data
pretty_name: OpenCAPY
size_categories:
  - 10K<n<100K

OpenCAPY

OpenCAPY is a capybara semantic segmentation dataset.

Dataset Summary

OpenCAPY provides RGB images and single-channel PNG segmentation masks for capybara segmentation. Mask pixel values are class indices, not visualization values.

Task: semantic segmentation
Images: RGB image files under images/
Masks: single-channel PNG files under labels/
Label value 0: background
Label value 1: capybara
Training data includes real and synthetic data
Validation and test data are real data

Dataset Structure

OpenCAPY/
├── README.md
├── RELEASE_MANIFEST.txt
├── RELEASE_REPORT.md
├── dataset.json
├── images/
├── labels/
├── metadata/
└── splits/

Each image, label, and metadata file uses the same relative stem. For example:

images/train_real/night/img_xxx.jpg
labels/train_real/night/img_xxx.png
metadata/train_real/night/img_xxx.json

Split files contain extensionless image ids, for example:

train_real/night/img_xxx

The dataset.json file lists samples with relative paths for images, labels, and metadata.

Dataset Splits

train_synthetic_qc_cleaned   23626
train_real                    6494
val_real                       390
test_real                      382
----------------------------------
total                        30892

Labels

Masks are single-channel PNG files with class-index values:

0 background
1 capybara

Do not scale training labels to 0/255. Visualization masks and preview overlays should be generated outside the canonical dataset files.

Data Sources

The release contains both real and synthetic capybara image subsets. The dataset metadata and split names distinguish real subsets from the train_synthetic_qc_cleaned synthetic training subset.

Confirmed subset names in this release:

train_real
train_synthetic_qc_cleaned
val_real
test_real

Annotation / Processing

The dataset contains segmentation masks stored as canonical 0/1 class-index PNG files. Repository metadata indicates that automated processing used Qwen grounding and SAM3 segmentation for real subsets, and that synthetic training data passed a QC-cleaned pipeline before inclusion.

This release packaging did not rerun annotation, regenerate masks, change split membership, or perform a new data-quality audit. Sample identity and split identity were preserved from the frozen source dataset.

Intended Uses

Capybara semantic segmentation
Computer vision research
Segmentation benchmarking
Real/synthetic training experiments
Robustness and domain-gap studies involving animal segmentation

Limitations

The dataset is focused on capybaras and may not generalize to other animals or object categories.
Synthetic images may have a domain gap relative to real-world imagery.
Data sources and visual distributions may contain biases.
Users should validate generalization for their own deployment or research setting.

License / Redistribution

License and redistribution terms are being finalized before public release.

The final dataset license and original image redistribution status must be confirmed by the publisher before making the Hugging Face repository public.