| | --- |
| | 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 |
| |
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| | 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) |
| |
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| | The code allows you to run the model over Minecraft in realtime. |
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|
| | ## 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 |
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| |  |
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