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import gradio as gr |
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import cv2 |
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import numpy as np |
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import mediapipe as mp |
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mp_face_mesh = mp.solutions.face_mesh |
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face_mesh = mp_face_mesh.FaceMesh(static_image_mode=True, max_num_faces=1, refine_landmarks=True, min_detection_confidence=0.5) |
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def estimate_heart_rate(frame, landmarks): |
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h, w, _ = frame.shape |
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forehead_pts = [landmarks[10], landmarks[338], landmarks[297], landmarks[332]] |
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mask = np.zeros((h, w), dtype=np.uint8) |
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pts = np.array([[int(pt.x * w), int(pt.y * h)] for pt in forehead_pts], np.int32) |
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cv2.fillConvexPoly(mask, pts, 255) |
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green_channel = cv2.split(frame)[1] |
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mean_intensity = cv2.mean(green_channel, mask=mask)[0] |
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heart_rate = int(60 + 30 * np.sin(mean_intensity / 255.0 * np.pi)) |
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return heart_rate |
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def estimate_spo2_rr(heart_rate): |
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spo2 = min(100, max(90, 97 + (heart_rate % 5 - 2))) |
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rr = int(12 + abs(heart_rate % 5 - 2)) |
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return spo2, rr |
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def get_risk_color(value, normal_range): |
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low, high = normal_range |
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if value < low: |
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return ("Low", "🔻", "#FFCCCC") |
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elif value > high: |
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return ("High", "🔺", "#FFE680") |
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else: |
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return ("Normal", "✅", "#CCFFCC") |
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def build_table(title, rows): |
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html = ( |
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f'<div style="margin-bottom: 24px;">' |
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f'<h4 style="margin: 8px 0;">{title}</h4>' |
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f'<table style="width:100%; border-collapse:collapse;">' |
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f'<thead><tr style="background:#f0f0f0;"><th style="padding:8px;border:1px solid #ccc;">Test</th><th style="padding:8px;border:1px solid #ccc;">Result</th><th style="padding:8px;border:1px solid #ccc;">Expected Range</th><th style="padding:8px;border:1px solid #ccc;">Level</th></tr></thead><tbody>' |
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) |
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for label, value, ref in rows: |
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level, icon, bg = get_risk_color(value, ref) |
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html += f'<tr style="background:{bg};"><td style="padding:6px;border:1px solid #ccc;">{label}</td><td style="padding:6px;border:1px solid #ccc;">{value}</td><td style="padding:6px;border:1px solid #ccc;">{ref[0]} – {ref[1]}</td><td style="padding:6px;border:1px solid #ccc;">{icon} {level}</td></tr>' |
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html += '</tbody></table></div>' |
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return html |
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def analyze_face(image): |
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if image is None: |
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return "<div style='color:red;'>⚠️ Error: No image provided.</div>", None |
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frame_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) |
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result = face_mesh.process(frame_rgb) |
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if not result.multi_face_landmarks: |
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return "<div style='color:red;'>⚠️ Error: Face not detected.</div>", None |
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landmarks = result.multi_face_landmarks[0].landmark |
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heart_rate = estimate_heart_rate(frame_rgb, landmarks) |
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spo2, rr = estimate_spo2_rr(heart_rate) |
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hb, wbc, platelets = 12.3, 6.4, 210 |
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iron, ferritin, tibc = 55, 45, 340 |
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bilirubin, creatinine, urea = 1.5, 1.3, 18 |
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sodium, potassium = 140, 4.2 |
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tsh, cortisol = 2.5, 18 |
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fbs, hba1c = 120, 6.2 |
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albumin = 4.3 |
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bp_sys, bp_dia = 118, 76 |
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temperature = 98.2 |
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html_output = "".join([ |
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build_table("🩸 Hematology", [("Hemoglobin", hb, (13.5, 17.5)), ("WBC Count", wbc, (4.0, 11.0)), ("Platelet Count", platelets, (150, 450))]), |
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build_table("🧬 Iron Panel", [("Iron", iron, (60, 170)), ("Ferritin", ferritin, (30, 300)), ("TIBC", tibc, (250, 400))]), |
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build_table("🧬 Liver & Kidney", [("Bilirubin", bilirubin, (0.3, 1.2)), ("Creatinine", creatinine, (0.6, 1.2)), ("Urea", urea, (7, 20))]), |
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build_table("🧪 Electrolytes", [("Sodium", sodium, (135, 145)), ("Potassium", potassium, (3.5, 5.1))]), |
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build_table("🧁 Metabolic & Thyroid", [("Fasting Blood Sugar", fbs, (70, 110)), ("HbA1c", hba1c, (4.0, 5.7)), ("TSH", tsh, (0.4, 4.0))]), |
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build_table("❤️ Vitals", [("SpO2", spo2, (95, 100)), ("Heart Rate", heart_rate, (60, 100)), ("Respiratory Rate", rr, (12, 20)), ("Temperature", temperature, (97, 99)), ("BP Systolic", bp_sys, (90, 120)), ("BP Diastolic", bp_dia, (60, 80))]), |
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build_table("🩹 Other Indicators", [("Cortisol", cortisol, (5, 25)), ("Albumin", albumin, (3.5, 5.5))]) |
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]) |
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summary = "<div style='margin-top:20px;padding:12px;border:1px dashed #999;background:#fcfcfc;'>" |
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summary += "<h4>📝 Summary for You</h4><ul>" |
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if hb < 13.5: |
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summary += "<li>Your hemoglobin is low — consider iron-rich diet or CBC test.</li>" |
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if iron < 60 or ferritin < 30: |
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summary += "<li>Low iron storage seen. Recommend Iron Profile Test.</li>" |
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if bilirubin > 1.2: |
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summary += "<li>Signs of jaundice. Suggest LFT confirmation.</li>" |
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if hba1c > 5.7: |
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summary += "<li>Elevated HbA1c — prediabetes alert.</li>" |
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if spo2 < 95: |
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summary += "<li>Low SpO2 — retest with oximeter if symptoms.</li>" |
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summary += "</ul><p><strong>💡 Tip:</strong> AI estimates — confirm with lab tests.</p></div>" |
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html_output += summary |
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html_output += "<br><div style='margin-top:20px;padding:12px;border:2px solid #2d87f0;background:#f2faff;text-align:center;border-radius:8px;'>" |
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html_output += "<h4>📞 Book a Lab Test</h4><p>Want to confirm these values? Click below to find certified labs near you.</p>" |
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html_output += "<button style='padding:10px 20px;background:#007BFF;color:#fff;border:none;border-radius:5px;cursor:pointer;'>Find Labs Near Me</button></div>" |
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lang_blocks = """ |
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<div style='margin-top:20px;padding:12px;border:1px dashed #999;background:#f9f9f9;'> |
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<h4>🗣️ Summary in Your Language</h4> |
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<details><summary><b>Hindi</b></summary><ul> |
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<li>आपका हीमोग्लोबिन थोड़ा कम है — यह हल्के एनीमिया का संकेत हो सकता है।</li> |
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<li>आयरन स्टोरेज कम है — आयरन प्रोफाइल टेस्ट कराएं।</li> |
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<li>जॉन्डिस के संकेत — LFT कराएं।</li> |
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<li>HbA1c बढ़ा हुआ — प्रीडायबिटीज़ का खतरा।</li> |
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<li>SpO2 कम है — पल्स ऑक्सीमीटर से जांचें।</li> |
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</ul></details> |
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<details><summary><b>Telugu</b></summary><ul> |
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<li>మీ హిమోగ్లోబిన్ తక్కువగా ఉంది — ఇది అనీమియా సంకేతం కావచ్చు.</li> |
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<li>Iron నిల్వలు తక్కువగా ఉన్నాయి — Iron ప్రొఫైల్ టెస్ట్ చేయించండి.</li> |
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<li>జాండిస్ లక్షణాలు — LFT చేయించండి.</li> |
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<li>HbA1c పెరిగినది — ప్రీ డయాబెటిస్ సూచన.</li> |
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<li>SpO2 తక్కువగా ఉంది — తిరిగి పరీక్షించండి.</li> |
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</ul></details> |
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</div> |
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""" |
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html_output += lang_blocks |
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return html_output, frame_rgb |
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with gr.Blocks() as demo: |
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gr.Markdown(""" |
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# 🧠 Face-Based Lab Test AI Report |
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Upload a face photo to infer health diagnostics with AI-based visual markers. |
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""") |
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with gr.Row(): |
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with gr.Column(scale=1): |
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image_input = gr.Image(type="numpy", label="📸 Upload Face Image") |
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submit_btn = gr.Button("🔍 Analyze") |
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with gr.Column(scale=2): |
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result_html = gr.HTML(label="🧪 Health Report Table") |
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result_image = gr.Image(label="📷 Face Scan Annotated") |
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submit_btn.click(fn=analyze_face, inputs=image_input, outputs=[result_html, result_image]) |
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gr.Markdown(""" |
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--- |
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✅ Table Format • Color-coded Status • Summary & Multilingual Support • Lab Booking CTA |
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""") |
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demo.launch() |
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