GangCaoLab/FISH_spots
FISH_spots Dataset The manually verified in situ hybridization fluorescence images and point coordinate dataset. This dataset contains images and annotations for the task of single-molecule fluorescence in situ hybridization (FISH) spot detection, supporting 2D, 3D, and simulated noisy data. The structure is designed for deep learning model development, training, and evaluation. Directory Structure FISH_spots/ ├── 2d/ │ ├── csv/ │ ├── image/ │ ├── image_raw/ │ └──… See the full description on the dataset page: https://huggingface.co/datasets/GangCaoLab/FISH_spots.
FISH_spots Dataset
The manually verified in situ hybridization fluorescence images and point coordinate dataset. This dataset contains images and annotations for the task of single-molecule fluorescence in situ hybridization (FISH) spot detection, supporting 2D, 3D, and simulated noisy data. The structure is designed for deep learning model development, training, and evaluation.
Directory Structure
FISH_spots/
├── 2d/
│ ├── csv/
│ ├── image/
│ ├── image_raw/
│ └── meta.csv
├── 3d/
│ ├── csv/
│ ├── image/
│ ├── meta_test.csv
│ └── meta_valid.csv
└── noise/
├── csv/
├── image/
├── meta.csv
├── meta_test.csv
└── meta_valid.csv
Download
# Make sure you have git-lfs installed (https://git-lfs.com)
git lfs install
git clone https://huggingface.co/datasets/GangCaoLab/FISH_spotsData Content and Annotation Format
- image directory Contains 512×512 image patches used for training. The images are ready for use by deep learning models, in standard formats such as PNG or TIFF.
- csv directory Stores CSV files containing annotated spot positions for each corresponding image patch. Each row records the coordinates and other metadata of detected or simulated spots.
- *meta.csv**
meta.csv, provide global metadata.
2D Dataset
- Includes data used in the U-FISH publication, comprising both real experimental data and simulated data.
- Covers 7 different experimental sources, providing diversity (real and simulated conditions).
- Contains over 4,000 images and 160,000 annotated spot positions.
- Suitable for benchmarking model generalization and spot detection in varied scenarios.
3D Dataset
- Mainly generated via simulation, representing spot distributions under 3D imaging conditions.
- Provides 3D image patches and coordinate-based annotations.
- Includes
meta_test.csvandmeta_valid.csvfor easy split management.
Noise Dataset
- Contains simulated noisy images aimed at testing model robustness to noise.
- Structure mirrors the 3D dataset, with patches, annotations, and metadata files.
Citation
If you use this dataset in your research, please cite the U-FISH paper and Dataset(DOI: https://doi.org/10.57967/hf/6150).
