The purpose of this my project (repo: GitHub - gcjordi/skincancer_edgeai_jetsonnano_demo: Skin Cancer Detector - Edge AI classifier - Jetson Nano (DEMO)) is to be a demo for the “Certification Jetson AI Specialist”
It’s a demo (no medical uses at the moment)
It’s a demo for Edge AI Computing based on NVIDIA JETSON NANO 2GB DEVELOPER KIT
Based on the structure: GitHub - dusty-nv/jetson-inference: Hello AI World guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.
Dataset: HAM10000 (only part for demo)
Functionality: classify skin lesions (malignant cancer or benign tumor) using Edge AI Computing, with a simple image taken by the user.
P.S: It can also work in WebApp: GitHub - gcjordi/skinlesionanalyzer_webapp_jgc: WebApp para analizador de lesiones de piel mediante ML
RUN (in terminal) (ONLY TEST MODE, NOT REAL MEDICAL TEST):
cd jetson-inference/
docker/run.sh
cd python/training/classification
python3 train.py --model-dir=models/tools --batch-size=4 --workers=1 --epochs=1 data/skin/
python3 onnx_export.py --model-dir=models/skin (previously renamed name folder: tools to skin)
imagenet --model=models/skin/resnet18.onnx --labels=data/skin/labels.txt --input_blob=input_0 --output_blob=output_0 /dev/video0