metadata
language:
- en
license: mit
library_name: pytorch
tags:
- computer-vision
- object-detection
- fcos
- minecraft
- gaming
datasets:
- twoturtles/minecraft-mobs
metrics:
- mean_average_precision
FCOS Minecraft Mob Detector
Detects 9 Minecraft entities (chicken, cow, creeper, enderman, pig, sheep, skeleton, spider, zombie) using FCOS (Fully Convolutional One-Stage) object detection.
Code
For training details and usage see minecraft-fcos
The code allows you to run the model over Minecraft in realtime.
Model Details
- Architecture: FCOS with ResNet50-FPN backbone
- Input: 640x640 RGB images
- Output: Bounding boxes and class labels for 9 entity types
- Training: Transfer learning on FCOS-pretrained weights
- Framework: PyTorch + torchvision
Performance
| Metric | Value |
|---|---|
| mAP | 0.595 |
| mAP_50 | 0.84 |
Sample Detection
