app.py

import gradio as gr
import kagglehub
import os
from processing import analyze_pneumothorax

# Download dataset
dataset_path = kagglehub.dataset_download("kmader/siim-medical-images")
print("Path to dataset files:", dataset_path)

# Find a DICOM file in the dataset (for testing)
def find_dicom_file(dataset_path):
    for root, _, files in os.walk(dataset_path):
        for file in files:
            if file.endswith(".dcm"):
                return os.path.join(root, file)
    return None

test_dicom_path = find_dicom_file(dataset_path)

if test_dicom_path is None:
    print("No DICOM files found in the dataset.")
else:
    print(f"Found a DICOM file for testing: {test_dicom_path}")

iface = gr.Interface(
    fn=analyze_pneumothorax,
    inputs=gr.File(type="filepath", label="Upload DICOM Image"),
    outputs=gr.Image(type="pil", label="Segmented Image"),
    title="Pneumothorax Segmentation",
    description="This is a simplified application that uses machine learning to analyze images using segmentation."
)

iface.launch()