File size: 2,737 Bytes
3469608 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 | """Gradio app - Diabetic Retinopathy Clinical Report Generator.
Pipeline: upload fundus image -> trained DR model grades severity (0-4) ->
Gemini drafts a structured clinical report around that grade.
Run locally: python app.py
This file is also the HuggingFace Spaces entry point.
"""
from __future__ import annotations
import gradio as gr
from src.dr_grader import grade_fundus
from src.report_generator import generate_report
from src.config import CLASS_NAMES
DISCLAIMER = (
"⚠️ **Research/education demo only - not for clinical use.** "
"The grade is produced by an automated model and the report is AI-generated; "
"both must be reviewed by a qualified ophthalmologist."
)
def _per_class_from_ordinal(ordinal):
"""Convert CORN ordinal probabilities P(>0..>3) into a per-class distribution."""
ge = [1.0] + list(ordinal) # P(y>=0..4)
pc = []
for k in range(5):
nxt = ge[k + 1] if k + 1 < len(ge) else 0.0
pc.append(max(0.0, ge[k] - nxt))
total = sum(pc) or 1.0
return {CLASS_NAMES[k]: pc[k] / total for k in range(5)}
def analyze(image):
if image is None:
return "Please upload a fundus image.", None, {}, ""
result = grade_fundus(image)
grade, label = result["grade"], result["label"]
grade_md = f"## Grade {grade}: {label}"
confidences = _per_class_from_ordinal(result["ordinal_probabilities"])
try:
report = generate_report(grade, result["processed_image"])
except Exception as exc: # noqa: BLE001 - surface config/API issues in the UI
report = f"_Report generation unavailable: {exc}_"
return grade_md, result["processed_image"], confidences, report
with gr.Blocks(title="DR Clinical Report Generator") as demo:
gr.Markdown("# 🩺 Diabetic Retinopathy - Clinical Report Generator")
gr.Markdown(
"Upload a retinal fundus image. A trained EfficientNet-B4 + Swin Transformer "
"model grades diabetic-retinopathy severity (0-4), and Gemini drafts a "
"structured clinical report around that grade."
)
gr.Markdown(DISCLAIMER)
with gr.Row():
with gr.Column():
inp = gr.Image(type="pil", label="Upload fundus image")
btn = gr.Button("Analyze", variant="primary")
with gr.Column():
grade_out = gr.Markdown()
conf_out = gr.Label(num_top_classes=5, label="Severity probabilities")
proc_out = gr.Image(label="Preprocessed (RFOV Crop + CLAHE)", type="pil")
gr.Markdown("### Clinical report")
report_out = gr.Markdown()
btn.click(analyze, inputs=inp, outputs=[grade_out, proc_out, conf_out, report_out])
if __name__ == "__main__":
demo.launch()
|