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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](https://github.com/twoturtles/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
|