|
|
|
|
|
|
|
|
|
|
|
import gradio as gr |
|
|
import cv2 |
|
|
import numpy as np |
|
|
import mediapipe as mp |
|
|
|
|
|
mp_face_mesh = mp.solutions.face_mesh |
|
|
face_mesh = mp_face_mesh.FaceMesh(static_image_mode=True, max_num_faces=1, refine_landmarks=True, min_detection_confidence=0.5) |
|
|
|
|
|
def estimate_heart_rate(frame, landmarks): |
|
|
h, w, _ = frame.shape |
|
|
forehead_pts = [landmarks[10], landmarks[338], landmarks[297], landmarks[332]] |
|
|
mask = np.zeros((h, w), dtype=np.uint8) |
|
|
pts = np.array([[int(pt.x * w), int(pt.y * h)] for pt in forehead_pts], np.int32) |
|
|
cv2.fillConvexPoly(mask, pts, 255) |
|
|
green_channel = cv2.split(frame)[1] |
|
|
mean_intensity = cv2.mean(green_channel, mask=mask)[0] |
|
|
heart_rate = int(60 + 30 * np.sin(mean_intensity / 255.0 * np.pi)) |
|
|
return heart_rate |
|
|
|
|
|
def estimate_spo2_rr(heart_rate): |
|
|
spo2 = min(100, max(90, 97 + (heart_rate % 5 - 2))) |
|
|
rr = int(12 + abs(heart_rate % 5 - 2)) |
|
|
return spo2, rr |
|
|
|
|
|
def get_risk_color(value, normal_range): |
|
|
low, high = normal_range |
|
|
if value < low: |
|
|
return "🔻 LOW" |
|
|
elif value > high: |
|
|
return "🔺 HIGH" |
|
|
else: |
|
|
return "✅ Normal" |
|
|
|
|
|
def generate_flags_extended(params): |
|
|
hb, wbc, platelets, iron, ferritin, tibc, bilirubin, creatinine, tsh, cortisol, fbs, hba1c = params |
|
|
flags = [] |
|
|
if hb < 13.5: |
|
|
flags.append("Hemoglobin Low - Possible Anemia") |
|
|
if wbc < 4.0 or wbc > 11.0: |
|
|
flags.append("Abnormal WBC Count - Possible Infection") |
|
|
if platelets < 150: |
|
|
flags.append("Platelet Drop Risk - Bruising Possible") |
|
|
if iron < 60: |
|
|
flags.append("Iron Deficiency Detected") |
|
|
if ferritin < 30: |
|
|
flags.append("Low Ferritin - Iron Store Low") |
|
|
if tibc > 400: |
|
|
flags.append("High TIBC - Iron Absorption Issue") |
|
|
if bilirubin > 1.2: |
|
|
flags.append("Jaundice Detected - Elevated Bilirubin") |
|
|
if creatinine > 1.2: |
|
|
flags.append("Kidney Function Concern - High Creatinine") |
|
|
if tsh < 0.4 or tsh > 4.0: |
|
|
flags.append("Thyroid Imbalance - Check TSH") |
|
|
if cortisol < 5 or cortisol > 25: |
|
|
flags.append("Stress Hormone Abnormality - Cortisol") |
|
|
if fbs > 110: |
|
|
flags.append("High Fasting Blood Sugar") |
|
|
if hba1c > 5.7: |
|
|
flags.append("Elevated HbA1c - Diabetes Risk") |
|
|
flags.append("Mood / Stress analysis requires separate behavioral model") |
|
|
return flags |
|
|
|
|
|
def analyze_face(image): |
|
|
if image is None: |
|
|
return {}, None |
|
|
|
|
|
frame_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) |
|
|
result = face_mesh.process(frame_rgb) |
|
|
|
|
|
if result.multi_face_landmarks: |
|
|
landmarks = result.multi_face_landmarks[0].landmark |
|
|
heart_rate = estimate_heart_rate(frame_rgb, landmarks) |
|
|
spo2, rr = estimate_spo2_rr(heart_rate) |
|
|
|
|
|
hb, wbc, platelets = 12.3, 6.4, 210 |
|
|
iron, ferritin, tibc = 55, 45, 340 |
|
|
bilirubin, creatinine = 1.5, 1.3 |
|
|
tsh, cortisol = 2.5, 18 |
|
|
fbs, hba1c = 120, 6.2 |
|
|
|
|
|
flags = generate_flags_extended([hb, wbc, platelets, iron, ferritin, tibc, bilirubin, creatinine, tsh, cortisol, fbs, hba1c]) |
|
|
|
|
|
sections = { |
|
|
"🩸 Hematology": [ |
|
|
f"Hemoglobin (Hb): {hb} g/dL - {get_risk_color(hb, (13.5, 17.5))}", |
|
|
f"WBC Count: {wbc} x10^3/uL - {get_risk_color(wbc, (4.0, 11.0))}", |
|
|
f"Platelet Count: {platelets} x10^3/uL - {get_risk_color(platelets, (150, 450))}" |
|
|
], |
|
|
"🧬 Iron & Liver Panel": [ |
|
|
f"Iron: {iron} µg/dL - {get_risk_color(iron, (60, 170))}", |
|
|
f"Ferritin: {ferritin} ng/mL - {get_risk_color(ferritin, (30, 300))}", |
|
|
f"TIBC: {tibc} µg/dL - {get_risk_color(tibc, (250, 400))}", |
|
|
f"Bilirubin: {bilirubin} mg/dL - {get_risk_color(bilirubin, (0.3, 1.2))}" |
|
|
], |
|
|
"🧪 Kidney, Thyroid & Stress": [ |
|
|
f"Creatinine: {creatinine} mg/dL - {get_risk_color(creatinine, (0.6, 1.2))}", |
|
|
f"TSH: {tsh} µIU/mL - {get_risk_color(tsh, (0.4, 4.0))}", |
|
|
f"Cortisol: {cortisol} µg/dL - {get_risk_color(cortisol, (5, 25))}" |
|
|
], |
|
|
"🧁 Metabolic Panel": [ |
|
|
f"Fasting Blood Sugar: {fbs} mg/dL - {get_risk_color(fbs, (70, 110))}", |
|
|
f"HbA1c: {hba1c}% - {get_risk_color(hba1c, (4.0, 5.7))}" |
|
|
], |
|
|
"❤️ Vital Signs": [ |
|
|
f"SpO2: {spo2}% - {get_risk_color(spo2, (95, 100))}", |
|
|
f"Heart Rate: {heart_rate} bpm - {get_risk_color(heart_rate, (60, 100))}", |
|
|
f"Respiratory Rate: {rr} breaths/min - {get_risk_color(rr, (12, 20))}", |
|
|
"Blood Pressure: Low (simulated)" |
|
|
], |
|
|
"⚠️ Risk Flags": flags |
|
|
} |
|
|
return sections, frame_rgb |
|
|
else: |
|
|
return {"⚠️ Error": ["Face not detected"]}, None |
|
|
|
|
|
|
|
|
demo = gr.Blocks(css=""" |
|
|
@media only screen and (max-width: 768px) { |
|
|
.gr-block.gr-column { width: 100% !important; } |
|
|
} |
|
|
""") |
|
|
with demo: |
|
|
gr.Markdown(""" |
|
|
# 🧠 Face-Based AI Lab Test Inference |
|
|
Upload a clear face image to simulate categorized lab reports with visual grouping. |
|
|
""") |
|
|
|
|
|
with gr.Row(): |
|
|
with gr.Column(scale=1): |
|
|
image_input = gr.Image(type="numpy", label="📸 Upload a Face Image") |
|
|
submit_btn = gr.Button("🔍 Analyze Now") |
|
|
with gr.Column(scale=2): |
|
|
accordion_output = gr.Accordion("📂 Diagnostic Summary", open=True) |
|
|
with accordion_output: |
|
|
result_html = gr.HighlightedText(label="📊 Grouped Report", combine_adjacent=True) |
|
|
result_image = gr.Image(label="🧍 Annotated Face Scan") |
|
|
|
|
|
def format_report(sections): |
|
|
lines = [] |
|
|
for title, values in sections.items(): |
|
|
lines.append((f"{title}",)) |
|
|
for item in values: |
|
|
lines.append((f" - {item}",)) |
|
|
return lines |
|
|
|
|
|
submit_btn.click( |
|
|
fn=analyze_face, |
|
|
inputs=image_input, |
|
|
outputs=[result_html, result_image], |
|
|
preprocess=False, |
|
|
postprocess=False, |
|
|
_js="(data) => [data]" |
|
|
).then( |
|
|
fn=format_report, |
|
|
inputs=None, |
|
|
outputs=result_html |
|
|
) |
|
|
|
|
|
gr.Markdown("---\n✅ Optimized for Mobile · Risk Indicators: 🔻 Low, 🔺 High, ✅ Normal") |
|
|
|
|
|
demo.launch() |
|
|
|
