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| # Face Detection-Based AI Automation of Lab Tests | |
| # Gradio App with Mobile-Responsive UI and Risk-Level Coloring | |
| 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 | |
| # Mobile-optimized UI with styled labels | |
| 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() | |