Update app.py

app.py

@@ -1,5 +1,5 @@
 # Face Detection-Based AI Automation of Lab Tests
-# Gradio App with Mobile-Responsive UI and Risk-Level Coloring
+# Gradio App - Cleaned for Hugging Face Compatibility
 
 import gradio as gr
 import cv2
@@ -66,100 +66,64 @@ def generate_flags_extended(params):
 
 def analyze_face(image):
     if image is None:
-        return {}, None
+        return "⚠️ Error: No image provided.", 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")
+    if not result.multi_face_landmarks:
+        return "⚠️ Error: Face not detected.", None
+
+    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])
+
+    report = f"""
+### 🩸 Hematology
+- Hemoglobin (Hb): {hb} g/dL - {get_risk_color(hb, (13.5, 17.5))}
+- WBC Count: {wbc} x10^3/uL - {get_risk_color(wbc, (4.0, 11.0))}
+- Platelet Count: {platelets} x10^3/uL - {get_risk_color(platelets, (150, 450))}
+
+### 🧬 Iron & Liver Panel
+- Iron: {iron} µg/dL - {get_risk_color(iron, (60, 170))}
+- Ferritin: {ferritin} ng/mL - {get_risk_color(ferritin, (30, 300))}
+- TIBC: {tibc} µg/dL - {get_risk_color(tibc, (250, 400))}
+- Bilirubin: {bilirubin} mg/dL - {get_risk_color(bilirubin, (0.3, 1.2))}
+
+### 🧪 Kidney, Thyroid & Stress
+- Creatinine: {creatinine} mg/dL - {get_risk_color(creatinine, (0.6, 1.2))}
+- TSH: {tsh} µIU/mL - {get_risk_color(tsh, (0.4, 4.0))}
+- Cortisol: {cortisol} µg/dL - {get_risk_color(cortisol, (5, 25))}
+
+### 🧁 Metabolic Panel
+- Fasting Blood Sugar: {fbs} mg/dL - {get_risk_color(fbs, (70, 110))}
+- HbA1c: {hba1c}% - {get_risk_color(hba1c, (4.0, 5.7))}
+
+### ❤️ Vital Signs
+- SpO2: {spo2}% - {get_risk_color(spo2, (95, 100))}
+- Heart Rate: {heart_rate} bpm - {get_risk_color(heart_rate, (60, 100))}
+- Respiratory Rate: {rr} breaths/min - {get_risk_color(rr, (12, 20))}
+- Blood Pressure: Low (simulated)
+
+### ⚠️ Risk Flags
+- {"\n- ".join(flags)}
+"""
+    return report, frame_rgb
+
+demo = gr.Interface(
+    fn=analyze_face,
+    inputs=gr.Image(type="numpy", label="📸 Upload Face Image"),
+    outputs=[gr.Markdown(label="🧪 Diagnostic Report"), gr.Image(label="🧍 Annotated Face")],
+    title="Face-Based AI Lab Test Inference",
+    description="Upload a clear face image to get lab test estimates and vital signs via facial analysis."
+)
 
 demo.launch()