Upload README.md with huggingface_hub

README.md

@@ -0,0 +1,89 @@
+---
+license: cc-by-4.0
+task_categories:
+  - image-segmentation
+task_ids:
+  - instance-segmentation
+  - semantic-segmentation
+language:
+  - en
+tags:
+  - medical-imaging
+  - electron-microscopy
+  - nuclei-segmentation
+  - 3d-segmentation
+  - zebrafish
+  - neuroscience
+pretty_name: NucMM-Z (Neuronal Nuclei from Zebrafish)
+size_categories:
+  - 1K<n<10K
+---
+
+# NucMM-Z Dataset
+
+## Overview
+
+**NucMM-Z** (Neuronal Nuclei from Zebrafish) is a 3D electron microscopy (EM) dataset for nuclei instance segmentation from zebrafish brain tissue.
+
+| Property | Value |
+|----------|-------|
+| **Modality** | Electron Microscopy (EM) |
+| **Task** | Nuclei instance segmentation |
+| **Anatomy** | Zebrafish brain |
+| **Volume Size** | 64 × 64 × 64 voxels per patch |
+| **Train Volumes** | 27 |
+| **Val Volumes** | 27 |
+| **Total Size** | ~1.09 GB |
+
+## Dataset Structure
+
+```
+NucMM-Z/
+├── image.tif           # Full raw volume (~1 GB)
+├── mask.h5             # Full annotation volume
+├── README.txt          # Original readme
+├── Image/
+│   ├── train/          # 27 training patches (.h5)
+│   └── val/            # 27 validation patches (.h5)
+└── Label/
+    ├── train/          # 27 training labels (.h5)
+    └── val/            # 27 validation labels (.h5)
+```
+
+## Label Format
+
+- **Instance Segmentation**: Each nucleus has a unique integer ID
+- Background: 0
+- Typical density: 50-300 nuclei per 64×64×64 volume
+
+## Usage with EasyMedSeg
+
+```python
+from dataloader import NucMMZImageDataset, NucMMZVideoDataset
+
+# Image mode (2D slices) - Recommended
+dataset = NucMMZImageDataset(split='train')
+sample = dataset[0]  # Returns dict with 'image' and 'mask'
+
+# Video mode (3D volumes as frame sequences)
+dataset = NucMMZVideoDataset(split='train')
+video = dataset[0]  # Returns dict with 'frames' and 'masks'
+```
+
+## Benchmark Results (SAM2)
+
+| Mode | Model | Mean Dice | Mean IoU |
+|------|-------|-----------|----------|
+| **Image** | sam2_hiera_large | **0.3438** | 0.2566 |
+| Video | sam2_video_hiera_large | 0.0631 | 0.0425 |
+
+**Recommendation**: Use image mode for this dataset.
+
+## Source
+
+- **Original**: [PyTorch Connectomics NucMM](https://connectomics-bazaar.github.io/proj/NucMM/index.html)
+- **Paper**: Wei et al., MICCAI 2020
+
+## License
+
+CC BY 4.0