---
license: cc-by-4.0
language:
- en
- ru
tags:
- minecraft
- biome
- classification
- game
- computer-vision
- time-of-day
pretty_name: Minecraft Biome, Dimension & Time Dataset
size_categories:
- 10K<n<100K
---

# 🌍 Minecraft Vision Dataset

Manually collected Minecraft screenshots for classification tasks.
Useful for training AI agents, bots, and computer vision models.

## 📦 What's inside
- Biomes, dimensions, time of day, and more.
- See the repository file browser for the full list of classes and current image counts.

## 📂 Dataset structure
The root contains one folder per class. New classes are added over time.

## 🔍 Current statistics
Exact numbers of classes and images are always visible on the [dataset page](https://huggingface.co/datasets/Nininkkka/Minecraft-vision-dataset).  
Browse the "Files and versions" tab – everything is there.

## 🔄 Continuous updates
This dataset is regularly expanded. No manual changelog is kept – check the commit history for updates.

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# 🎮 Minecraft Vision Dataset - Recommended Groups

⚠️ **Important:** Don't mix groups in one training run. Pick **one** below.

---

## 🧩 Recommended Groups

1. **🌍 Core biomes (128x128, 7 classes):**  
   `caves, end, forests, nether, oceans, plains, sky`  
   *(Most popular & balanced)*

2. **🌞 Time of day (128x128, 4 classes):**  
   `time-day, time-noon, time-night, time-midnight`

3. **📸 High resolution (384x384, 5 classes):**  
   `caves_384x384, desert_384x384, nether_384x384, end_384x384, forests_384x384`

---

## 🚀 Quick filter example (PyTorch)
```python
from datasets import load_dataset
ds = load_dataset("Nininkkka/Minecraft-vision-dataset", split="train", streaming=True)

# Filter Group 1
def filter_group1(x):
    path = x["image"]["path"]
    return "/v1/" in path and any(b in path for b in ["caves/","end/","forests/","nether/","oceans/","plains/","sky/"])

group1 = ds.filter(filter_group1)