Kidney Stone Detection

The goal of this project is to build a kidney stone detection model which detects kidney stones from X-Ray images using bounding box annotations.
A YOLOv8 model was trained based on a training set of kidney X-Ray images.
The application's UI design and model deployment were done using Streamlit.
Dataset: https://www.kaggle.com/datasets/safurahajiheidari/kidney-stone-images
Application URL: https://kidneystone-vitalinsight.streamlit.app/

Name		Name	Last commit message	Last commit date
Latest commit History 3 Commits
.idea		.idea
.vscode		.vscode
__pycache__		__pycache__
data		data
runs/detect		runs/detect
static		static
templates		templates
README.md		README.md
app.py		app.py
app_preview.png		app_preview.png
data.yaml		data.yaml
data_exploration.py		data_exploration.py
flask_app.py		flask_app.py
ks_detection.pt		ks_detection.pt
logo.jpg		logo.jpg
model_definition.py		model_definition.py
model_inference.py		model_inference.py
packages.txt		packages.txt
requirements.txt		requirements.txt
sample_image.jpg		sample_image.jpg
streamlit_app.py		streamlit_app.py
yolov8s.pt		yolov8s.pt

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