Rochard112/melanoma-detection-model
By Rochard112 · ↓ 0 · ♥ 0 · Updated 2025-09-28
What's in this repo
This page lists the files in Rochard112/melanoma-detection-model, including melanoma_model.onnx.
- 1 ONNX models (.onnx files)
- 5 files, including 1 .md, 1 .onnx, 1 .json, 1 .zip
- Last updated 2025-09-28
ONNX files
| File | Size | Download |
|---|---|---|
| melanoma_model.onnx | — | Download |
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
README
Melanoma Detection Model
Model Information
- Architecture: EfficientNet-B0
- Format: ONNX
- Size: 16.59 MB
- Efficiency Score: 1.00
- Inference Time: 0.0715s
Optimization Targets
This model is optimized for Safe Scan validator incentives:
- F-Beta Score (β=2): 60% weight - prioritizes recall over precision
- Accuracy: 30% weight
- ROC-AUC: 10% weight
- Model Size: <50MB for full efficiency bonus
Usage
import onnxruntime as ort
import numpy as np
# Load model
session = ort.InferenceSession('melanoma_model.onnx')
# Preprocess image (512x512 RGB, normalized [0,1])
image = preprocess_image(your_image) # Shape: (1, 3, 512, 512)
# Run inference
output = session.run(None, {'input': image})
prediction = output[0][0] # Shape: (2,)
License
MIT License - Compatible with Safe Scan requirements
Competition
Safe Scan Subnet 76 - Melanoma Detection Competition
Files (5)
.gitattributes
README.md
melanoma_model.onnx
ONNX
model_metadata.json
training_code.zip
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