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fcos-pneumonia-detection-model-checkpoints
Francesco2035/fcos-pneumonia-detection-model-checkpoints
fcos-pneumonia-detection-model-checkpoints is a machine learning model from Francesco2035. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
This repository contains the pretrained checkpoints of four FCOS-style pneumonia detection models developed for the Numerical Analysis for Machine Learning project at Politecnico di Milano.
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Updated Sep 15, 2026
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- Access
- Public
- Created
- Sep 4, 2026
- Updated
- Sep 15, 2026
- SHA
- 7ea7a2f7
Model card
From the Hugging Face model README
FCOS Pneumonia Detection — Model Checkpoints
This repository contains the pretrained checkpoints of four FCOS-style pneumonia detection models developed for the Numerical Analysis for Machine Learning project at Politecnico di Milano.
Models
Four detector configurations are provided:
- R50-IN: ResNet-50 + FCOS-style detector, initialized with ImageNet pretrained weights
- R50-CX: ResNet-50 + FCOS-style detector, initialized with Chest-Xray pretrained weights
- R101-IN: ResNet-101 + FCOS-style detector, initialized with ImageNet pretrained weights
- R101-CX: ResNet-101 + FCOS-style detector, initialized with Chest-Xray pretrained weights
All models are trained for pneumonia detection and localization on the RSNA Pneumonia Detection Challenge dataset.
Model Configuration
| Model | Backbone | Initialization | Task |
|---|---|---|---|
| R50-IN | ResNet-50 | ImageNet | Pneumonia detection and localization |
| R50-CX | ResNet-50 | Chest-Xray | Pneumonia detection and localization |
| R101-IN | ResNet-101 | ImageNet | Pneumonia detection and localization |
| R101-CX | ResNet-101 | Chest-Xray | Pneumonia detection and localization |
Common configuration:
- Detector: FCOS-style anchor-free object detector
- Input resolution: 512 × 512
- Dataset: RSNA Pneumonia Detection Challenge
Usage
The checkpoints are intended to be used with the source code available in the corresponding GitHub repository.
For example, to analyze an R101-IN checkpoint:
uv run python main.py \
--mode analyze \
--checkpoint path/to/resnet101_imagenet_long_ft.pt \
--backbone imagenet \
--resnet-depth 101
- Created
- Sep 4, 2026
- Updated
- Sep 15, 2026