hmnshudhmn24/minecraft-mobs-yolo-dataset

🎮 Minecraft Mobs YOLO Dataset

2,585+ pre-split images with YOLO bounding box annotations for Minecraft mob detection across 5 macro-classes.

🧭 Overview

This dataset contains 2,585 images of Minecraft mobs annotated with bounding boxes in YOLO format. Pre-split into Train (80%) and Validation (20%) sets — ready to plug into any Ultralytics YOLO pipeline.

🧟 Classes (5 Macro-Classes)

📊 Dataset Details

Background images with zero bounding boxes are included for hard negative mining to reduce false positives.

🗂️ Dataset Structure

minecraftmobsyolo/ ├── train/ │ ├── images/ # Training images │ └── labels/ # YOLO annotation .txt files ├── val/ │ ├── images/ # Validation images │ └── labels/ # YOLO annotation .txt files ├── data.yaml # YOLO config file ├── README.md └── LICENSE

⚙️ data.yaml

nc: 5 names: ["creeper", "skeleton", "spider", "zombie", "enderman"] train: train/images val: val/images

⚡ Quick Start

from ultralytics import YOLO

model = YOLO("yolov8n.pt")

model.train( data="minecraftmobsyolo/data.yaml", epochs=50, imgsz=640, batch=16, name="minecraftmobsdetector" )

results = model.val() print(results)

💡 Use Cases

• —Minecraft mob detection and tracking
• —YOLO model training and fine-tuning
• —Object detection with hard negative mining
• —Gaming AI research
• —Real-time mob radar systems
• —Computer vision project demonstrations