Update app.py

app.py

@@ -130,41 +130,88 @@ CLINICAL_GUIDANCE = (
 # ============================================================
 WELCOME_HTML = f"""
 <div style="max-width:980px;margin:0 auto;">
-  <div style="padding:14px 16px;border-radius:14px;background:rgba(255,255,255,0.04);border:1px solid rgba(255,255,255,0.10);">
-    <div style="font-size:18px;font-weight:900;margin-bottom:6px;">
-      TB X-ray Assistant <span style="opacity:0.75;font-weight:700;font-size:13px;">(research / decision support)</span>
+
+  <div style="padding:20px;border-radius:18px;background:rgba(255,255,255,0.05);border:1px solid rgba(255,255,255,0.12);">
+
+    <div style="font-size:24px;font-weight:950;margin-bottom:8px;">
+      Chest X-ray TB Screening Assistant
+    </div>
+
+    <div style="font-size:15px;line-height:1.55;opacity:0.92;">
+      This app helps review chest X-ray images for signs that may be seen with pulmonary tuberculosis,
+      also called TB. It is meant to support medical review, not replace a doctor, radiologist, or lab test.
+    </div>
+
+    <div style="margin-top:18px;padding:14px;border-radius:14px;background:rgba(59,130,246,0.10);border:1px solid rgba(59,130,246,0.22);">
+      <div style="font-size:17px;font-weight:900;margin-bottom:8px;">How the app works</div>
+
+      <div style="font-size:14px;line-height:1.55;">
+        <b>Step 1 — Upload a chest X-ray image.</b><br/>
+        You can upload a normal X-ray image, phone photo, WhatsApp image, or screenshot.
+        <br/><br/>
+
+        <b>Step 2 — The app checks the lung area.</b><br/>
+        It tries to find the lung region first, so the AI focuses on the chest instead of borders,
+        labels, or background.
+        <br/><br/>
+
+        <b>Step 3 — The AI checks for TB-like patterns.</b><br/>
+        The app gives a simple result and shows image views that help explain what was checked.
+      </div>
     </div>
 
-    <div style="opacity:0.9;font-size:13px;line-height:1.35;">
-      Upload chest X-rays to get an AI screening score, heatmaps, and a simple consensus output.
+    <div style="margin-top:18px;font-size:17px;font-weight:900;">
+      What the result means
     </div>
 
-    <div style="margin-top:10px;display:flex;flex-wrap:wrap;gap:8px;">
-      <span style="font-size:12px;padding:6px 10px;border-radius:999px;background:rgba(255,255,255,0.06);border:1px solid rgba(255,255,255,0.10);">
-        <b>{MODEL_NAME_TBNET}</b> + Grad-CAM
-      </span>
-      <span style="font-size:12px;padding:6px 10px;border-radius:999px;background:rgba(255,255,255,0.06);border:1px solid rgba(255,255,255,0.10);">
-        Auto lung mask + fail-safe
-      </span>
-      <span style="font-size:12px;padding:6px 10px;border-radius:999px;background:rgba(255,255,255,0.06);border:1px solid rgba(255,255,255,0.10);">
-        <b>{MODEL_NAME_RADIO}</b> (optional)
-      </span>
-      <span style="font-size:12px;padding:6px 10px;border-radius:999px;background:rgba(255,255,255,0.06);border:1px solid rgba(255,255,255,0.10);">
-        Consensus: ✅ LOW · ⚠️ INDET · ⚠️ SCREEN+ · 🚩 TB+
-      </span>
-      <span style="font-size:12px;padding:6px 10px;border-radius:999px;background:rgba(255,255,255,0.06);border:1px solid rgba(255,255,255,0.10);">
-        Phone/WhatsApp Mode
-      </span>
+    <div style="margin-top:10px;display:grid;grid-template-columns:repeat(auto-fit,minmax(210px,1fr));gap:10px;">
+
+      <div style="padding:12px;border-radius:14px;background:rgba(34,197,94,0.12);border:1px solid rgba(34,197,94,0.25);">
+        <div style="font-weight:900;">✅ Low</div>
+        <div style="font-size:13px;line-height:1.45;margin-top:4px;">
+          The AI did not find a strong TB-like pattern in the image.
+        </div>
+      </div>
+
+      <div style="padding:12px;border-radius:14px;background:rgba(245,158,11,0.12);border:1px solid rgba(245,158,11,0.25);">
+        <div style="font-weight:900;">⚠️ Unclear</div>
+        <div style="font-size:13px;line-height:1.45;margin-top:4px;">
+          The image or AI result is not reliable enough. Medical review is advised.
+        </div>
+      </div>
+
+      <div style="padding:12px;border-radius:14px;background:rgba(245,158,11,0.18);border:1px solid rgba(245,158,11,0.32);">
+        <div style="font-weight:900;">⚠️ Needs review</div>
+        <div style="font-size:13px;line-height:1.45;margin-top:4px;">
+          The AI found a possible TB-like pattern. A clinician or radiologist should review it.
+        </div>
+      </div>
+
+      <div style="padding:12px;border-radius:14px;background:rgba(239,68,68,0.16);border:1px solid rgba(239,68,68,0.32);">
+        <div style="font-weight:900;">🚩 TB-like pattern seen</div>
+        <div style="font-size:13px;line-height:1.45;margin-top:4px;">
+          The AI found stronger TB-like features. Prompt medical review is recommended.
+        </div>
+      </div>
+
     </div>
 
-    <div style="margin-top:10px;opacity:0.85;font-size:12.5px;">
-      <b>Tip:</b> Turn on Phone/WhatsApp Mode for phone photos, WhatsApp-forwards, or screenshots with borders.
+    <div style="margin-top:18px;padding:13px;border-radius:14px;background:rgba(148,163,184,0.10);border:1px solid rgba(148,163,184,0.22);font-size:14px;line-height:1.5;">
+      <b>When to use Phone/WhatsApp Mode:</b><br/>
+      Turn it on if the X-ray is a phone photo, WhatsApp-forwarded image, screenshot, cropped image,
+      or has black/white borders. It helps the app handle common image-quality issues.
     </div>
+
   </div>
 
-  <div style="margin-top:12px;padding:10px 12px;border-left:5px solid #f59e0b;border-radius:12px;background:rgba(245,158,11,0.10);font-size:12.5px;line-height:1.35;">
-    <b>Clinical disclaimer:</b> Not diagnostic. If TB is suspected clinically, pursue CBNAAT/GeneXpert/sputum and/or CT chest regardless of AI output.
+  <div style="margin-top:14px;padding:14px 16px;border-left:6px solid #f59e0b;border-radius:14px;background:rgba(245,158,11,0.12);font-size:14px;line-height:1.55;">
+    <b>Important medical notice:</b><br/>
+    This app is not a diagnostic test. A low AI result does <b>not</b> rule out TB, especially early,
+    subtle, diffuse, or miliary TB. If symptoms or clinical suspicion are present, please seek
+    clinician/radiologist review and consider CBNAAT/GeneXpert, sputum testing, and/or CT chest
+    regardless of the AI result.
   </div>
+
 </div>
 """
 
@@ -198,6 +245,153 @@ def badge_color_for_state(state: str) -> str:
     return "rgba(148,163,184,0.12)"     # gray
 
 
+# ============================================================
+# PATIENT-FRIENDLY RESULT HELPERS
+# ============================================================
+def patient_state_label(state: str) -> str:
+    return {
+        "LOW": "✅ Low TB-like pattern",
+        "INDET": "⚠️ Unclear result",
+        "SCREEN+": "⚠️ Needs medical review",
+        "TB+": "🚩 TB-like pattern seen",
+        "N/A": "⚠️ Not available",
+    }.get(state, "⚠️ Unclear result")
+
+
+def patient_state_meaning(state: str) -> str:
+    return {
+        "LOW": (
+            "The AI did not find a strong TB-like pattern in this X-ray. "
+            "This does not completely rule out TB."
+        ),
+        "INDET": (
+            "The result is not clear enough to rely on. This may happen because of image quality, "
+            "cropping, unusual positioning, or disagreement between AI checks."
+        ),
+        "SCREEN+": (
+            "The AI found a possible TB-like pattern. This should be reviewed by a clinician or radiologist."
+        ),
+        "TB+": (
+            "The AI found stronger TB-like features. This is not a diagnosis, but prompt medical review is recommended."
+        ),
+        "N/A": (
+            "The app could not safely calculate a result for this image."
+        ),
+    }.get(state, "The result is unclear and should be reviewed clinically.")
+
+
+def patient_quality_text(q: float) -> Tuple[str, str]:
+    if q >= 75:
+        return "Good image quality", "The image looks clear enough for AI screening."
+    if q >= 55:
+        return "Acceptable image quality", "The image can be checked, but some quality limits may affect accuracy."
+    return "Low image quality", "The image may be blurry, dark, overexposed, cropped, or compressed. The result is less reliable."
+
+
+def patient_lung_mask_text(cov: float) -> Tuple[str, str]:
+    if cov < FAIL_COV:
+        return "Lung area not found safely", "The app could not confidently find enough lung area, so TB scoring may be disabled."
+    if cov < WARN_COV:
+        return "Lung area partly found", "The app found only part of the lung area. The result may be less reliable."
+    return "Lung area found", "The app found enough lung area to run the AI screening."
+
+
+def patient_attention_text(diffuse: bool) -> str:
+    if diffuse:
+        return "The AI attention was spread out and not focused in one clear area. This makes the result less certain."
+    return "The AI attention was focused enough to create a useful heatmap."
+
+
+def patient_score_text(prob: Optional[float]) -> str:
+    if prob is None:
+        return "No TB score was calculated because the safety check stopped the AI from giving a possibly unreliable result."
+    return (
+        f"For transparency, the AI screening score was <b>{prob:.3f}</b>. "
+        "A higher score means the AI saw more TB-like pattern, but the score alone is not a diagnosis."
+    )
+
+
+def patient_radio_text(use_radio: bool, radio_state: str, radio_primary_val: Optional[float]) -> str:
+    if not use_radio:
+        return "The second AI check was turned off."
+    if radio_state == "N/A" or radio_primary_val is None:
+        return "The second AI check was not available for this image."
+    return (
+        f"The second AI check gave: <b>{patient_state_label(radio_state)}</b>. "
+        f"For transparency, its score was <b>{radio_primary_val:.3f}</b>."
+    )
+
+
+def patient_agreement_text(tb_state: str, radio_state: str, use_radio: bool) -> str:
+    if not use_radio:
+        return "Only the main AI check was used for this image."
+
+    if radio_state == "N/A":
+        return "Only the main AI check was available for this image."
+
+    if tb_state == radio_state:
+        return "Both AI checks gave a similar result."
+
+    if tb_state == "LOW" and radio_state in ("SCREEN+", "TB+"):
+        return "The two AI checks disagreed. Because one check found a possible TB-like pattern, treat this as unclear and review medically."
+
+    if radio_state == "LOW" and tb_state in ("SCREEN+", "TB+"):
+        return "The two AI checks disagreed. Because one check found a possible TB-like pattern, treat this as unclear and review medically."
+
+    return "The two AI checks were not fully aligned, so medical review is advised."
+
+
+def patient_final_state(tb_state: str, radio_state: str, use_radio: bool, consensus_label: str) -> str:
+    if tb_state == "TB+" or radio_state == "TB+" or consensus_label == "AGREE: TB+":
+        return "TB+"
+
+    if tb_state == "SCREEN+" or radio_state == "SCREEN+" or consensus_label == "AGREE: SCREEN+":
+        return "SCREEN+"
+
+    if tb_state == "INDET" or radio_state == "INDET":
+        return "INDET"
+
+    if tb_state == "LOW" and (not use_radio or radio_state in ("LOW", "N/A")):
+        return "LOW"
+
+    return "INDET"
+
+
+def patient_next_step_text(final_state: str) -> str:
+    if final_state == "TB+":
+        return (
+            "Please arrange prompt clinician/radiologist review. If TB is clinically suspected, "
+            "microbiological confirmation such as CBNAAT/GeneXpert and sputum testing is recommended."
+        )
+
+    if final_state == "SCREEN+":
+        return (
+            "Please get clinician/radiologist review. This is not a diagnosis, but the image should not be ignored."
+        )
+
+    if final_state == "INDET":
+        return (
+            "Do not rely on this AI result alone. Repeat with a better-quality image if possible and seek medical review "
+            "if symptoms or TB risk factors are present."
+        )
+
+    return (
+        "No strong TB-like pattern was found by the AI. However, if there are symptoms, TB exposure, weight loss, fever, "
+        "cough, immunosuppression, or strong clinical concern, medical review and testing are still advised."
+    )
+
+
+def patient_warning_html(warnings: List[str]) -> str:
+    if not warnings:
+        return "No major image-quality warnings were detected."
+
+    items = "".join([f"<li>{html_escape(w)}</li>" for w in warnings[:4]])
+    extra = "" if len(warnings) <= 4 else f"<li>{len(warnings) - 4} more note(s) in the technical details.</li>"
+    return f"<ul style='margin:6px 0 0 18px;padding:0;'>{items}{extra}</ul>"
+
+
+    
+
 # ============================================================
 # LUNG U-NET (INFERENCE)
 # ============================================================
@@ -1063,14 +1257,28 @@ def run_analysis(
     gallery_items = []
     details_md: List[str] = []
 
-    # Top banner
     summary_md.append(f"""
-<div style="border:1px solid rgba(255,255,255,0.10); border-radius:14px; padding:12px; margin:10px 0;">
-  <div style="font-size:18px; font-weight:900;">Results</div>
-  <div style="margin-top:6px; opacity:0.92;">
-    Each image shows: <b>{MODEL_NAME_TBNET}</b> result, <b>{MODEL_NAME_RADIO}</b> result (optional), then a <b>final consensus</b>.
-    <br/>
-    <b>Key:</b> ✅ LOW &nbsp; | &nbsp; ⚠️ INDETERMINATE &nbsp; | &nbsp; ⚠️ SCREEN+ &nbsp; | &nbsp; 🚩 TB+
+<div style="border:1px solid rgba(255,255,255,0.14);border-radius:18px;padding:16px;margin:12px 0;background:rgba(255,255,255,0.035);">
+  <div style="font-size:20px;font-weight:950;margin-bottom:8px;">Your X-ray screening results</div>
+
+  <div style="font-size:14px;line-height:1.55;opacity:0.94;">
+    The app checks each image and gives a simple result. Please read the result together with the
+    <b>image reliability</b> and <b>what to do next</b> sections.
+  </div>
+
+  <div style="margin-top:12px;display:grid;grid-template-columns:repeat(auto-fit,minmax(190px,1fr));gap:8px;">
+    <div style="padding:10px;border-radius:12px;background:rgba(34,197,94,0.12);border:1px solid rgba(34,197,94,0.24);font-size:13px;">
+      ✅ <b>Low</b><br/>No strong TB-like pattern found.
+    </div>
+    <div style="padding:10px;border-radius:12px;background:rgba(245,158,11,0.12);border:1px solid rgba(245,158,11,0.24);font-size:13px;">
+      ⚠️ <b>Unclear</b><br/>Result is not reliable enough.
+    </div>
+    <div style="padding:10px;border-radius:12px;background:rgba(245,158,11,0.18);border:1px solid rgba(245,158,11,0.30);font-size:13px;">
+      ⚠️ <b>Needs review</b><br/>Possible TB-like pattern.
+    </div>
+    <div style="padding:10px;border-radius:12px;background:rgba(239,68,68,0.16);border:1px solid rgba(239,68,68,0.30);font-size:13px;">
+      🚩 <b>TB-like pattern seen</b><br/>Prompt review advised.
+    </div>
   </div>
 </div>
 """)
@@ -1099,7 +1307,7 @@ def run_analysis(
             img_size=224,
         )
 
-        # RADIO (optional)
+        # RADIO / second AI check (optional)
         radio_text_long = f"{MODEL_NAME_RADIO} disabled."
         radio_raw_overlay = None
         radio_masked_overlay = None
@@ -1147,7 +1355,7 @@ def run_analysis(
                 radio_band = None
                 radio_masked_ran = False
 
-        # Consensus
+        # Consensus / final result
         consensus_label, consensus_detail, tb_state, radio_state = build_consensus(
             tb_prob=out["prob"],
             tb_band=out["band"],
@@ -1163,84 +1371,106 @@ def run_analysis(
         attention = "Diffuse / non-focal" if out.get("diffuse_risk", False) else "Focal / localized"
 
         warns = out.get("warnings", [])
-        top_warns = warns[:3] if warns else []
-        top_warn_line = " • ".join([html_escape(w) for w in top_warns]) if top_warns else "None"
-
         radio_primary_line = "N/A" if radio_primary_val is None else f"{radio_primary_val:.4f}"
         radio_raw_line = "N/A" if radio_raw_val is None else f"{radio_raw_val:.4f}"
         radio_masked_line = "Not run" if radio_masked_val is None else f"{radio_masked_val:.4f}"
 
-        if consensus_label == "DISAGREE":
-            next_step = "✅ Next step: Treat as <b>indeterminate</b> → radiologist review + microbiology if clinically suspected."
-        elif consensus_label in ("AGREE: TB+", "AGREE: SCREEN+"):
-            next_step = "✅ Next step: Prompt clinician/radiologist review; consider microbiological confirmation if clinically suspected."
-        elif consensus_label in ("AGREE: LOW",):
-            next_step = "✅ Next step: If symptoms/risk factors exist, still correlate clinically and consider further testing."
-        else:
-            next_step = "✅ Next step: Correlate clinically; radiologist review recommended if uncertainty or symptoms present."
-
-        state_badge_tb = f"""
-<span style="padding:4px 10px; border-radius:999px; background:{badge_color_for_state(tb_state)}; font-weight:800;">
-  {pretty_state(tb_state)}
-</span>"""
-        state_badge_radio = f"""
-<span style="padding:4px 10px; border-radius:999px; background:{badge_color_for_state(radio_state)}; font-weight:800;">
-  {pretty_state(radio_state)}
-</span>"""
-
-        tb_card = f"""
-<div style="border:1px solid rgba(255,255,255,0.12); border-radius:14px; padding:12px; margin:10px 0;">
-  <div style="font-size:16px; font-weight:900; margin-bottom:6px;">{html_escape(name)} — {MODEL_NAME_TBNET}</div>
-  <div style="margin-bottom:6px;"><b>State:</b> {state_badge_tb}</div>
-  <div><b>Result:</b> {html_escape(tb_label)} &nbsp; <span style="opacity:0.9;">(p={tb_prob_line})</span></div>
-  <div style="margin-top:6px; opacity:0.92;">
-    <b>Reliability:</b> Quality <b>{q:.0f}/100</b> &nbsp; | &nbsp; Lung mask <b>{cov*100:.1f}%</b> &nbsp; | &nbsp; Attention <b>{attention}</b>
+        final_state = patient_final_state(
+            tb_state=tb_state,
+            radio_state=radio_state,
+            use_radio=use_radio,
+            consensus_label=consensus_label,
+        )
+
+        final_label = patient_state_label(final_state)
+        final_meaning = patient_state_meaning(final_state)
+
+        quality_title, quality_text = patient_quality_text(q)
+        mask_title, mask_text = patient_lung_mask_text(cov)
+
+        tb_score_text = patient_score_text(out["prob"])
+        radio_user_text = patient_radio_text(use_radio, radio_state, radio_primary_val)
+        agreement_text = patient_agreement_text(tb_state, radio_state, use_radio)
+        next_step_user = patient_next_step_text(final_state)
+        warning_html = patient_warning_html(warns)
+
+        final_badge = f"""
+<span style="display:inline-block;padding:7px 13px;border-radius:999px;background:{badge_color_for_state(final_state)};font-weight:900;font-size:15px;">
+  {final_label}
+</span>
+"""
+
+        patient_card = f"""
+<div style="border:1px solid rgba(255,255,255,0.16);border-radius:18px;padding:16px;margin:14px 0;background:rgba(255,255,255,0.035);">
+
+  <div style="font-size:18px;font-weight:950;margin-bottom:8px;">
+    Result for: {html_escape(name)}
+  </div>
+
+  <div style="margin:8px 0 12px 0;">
+    {final_badge}
   </div>
-  <div style="margin-top:6px; opacity:0.92;"><b>Top notes:</b> {top_warn_line}</div>
-  <div style="margin-top:10px; padding:10px 12px; border-left:6px solid rgba(96,165,250,0.9); background: rgba(96,165,250,0.10); border-radius:12px;">
-    {recommendation_for_band(out.get("band"))}
+
+  <div style="font-size:14px;line-height:1.55;opacity:0.95;margin-bottom:14px;">
+    {html_escape(final_meaning)}
   </div>
-</div>
-"""
 
-        if not use_radio:
-            radio_card = f"""
-<div style="border:1px solid rgba(255,255,255,0.10); border-radius:14px; padding:12px; margin:10px 0; opacity:0.9;">
-  <div style="font-size:16px; font-weight:900; margin-bottom:6px;">{html_escape(name)} — {MODEL_NAME_RADIO}</div>
-  <div>RADIO is disabled. Enable it to view its independent output and heatmaps.</div>
-</div>
-"""
-        else:
-            gate_info = f"Masked gate={float(radio_gate):.2f} | LungCov={cov:.2f} | Masked ran={radio_masked_ran}"
-            radio_card = f"""
-<div style="border:1px solid rgba(255,255,255,0.12); border-radius:14px; padding:12px; margin:10px 0;">
-  <div style="font-size:16px; font-weight:900; margin-bottom:6px;">{html_escape(name)} — {MODEL_NAME_RADIO}</div>
-  <div style="margin-bottom:6px;"><b>State:</b> {state_badge_radio}</div>
-  <div><b>Result:</b> {html_escape(radio_result_short)}</div>
-  <div style="margin-top:6px; opacity:0.92;">
-    <b>Scores:</b> PRIMARY <b>{radio_primary_line}</b> &nbsp; | &nbsp; RAW <b>{radio_raw_line}</b> &nbsp; | &nbsp; MASKED <b>{radio_masked_line}</b>
+  <div style="display:grid;grid-template-columns:repeat(auto-fit,minmax(230px,1fr));gap:10px;margin-top:10px;">
+
+    <div style="padding:12px;border-radius:14px;background:rgba(59,130,246,0.10);border:1px solid rgba(59,130,246,0.22);">
+      <div style="font-weight:900;margin-bottom:5px;">1) What the main AI check found</div>
+      <div style="font-size:13.5px;line-height:1.5;">
+        <b>{patient_state_label(tb_state)}</b><br/>
+        {tb_score_text}
+      </div>
+    </div>
+
+    <div style="padding:12px;border-radius:14px;background:rgba(99,102,241,0.10);border:1px solid rgba(99,102,241,0.22);">
+      <div style="font-weight:900;margin-bottom:5px;">2) Second AI check</div>
+      <div style="font-size:13.5px;line-height:1.5;">
+        {radio_user_text}
+      </div>
+    </div>
+
+    <div style="padding:12px;border-radius:14px;background:rgba(148,163,184,0.10);border:1px solid rgba(148,163,184,0.22);">
+      <div style="font-weight:900;margin-bottom:5px;">3) Image reliability</div>
+      <div style="font-size:13.5px;line-height:1.5;">
+        <b>{quality_title}</b><br/>
+        {quality_text}<br/><br/>
+        <b>{mask_title}</b><br/>
+        {mask_text}
+      </div>
+    </div>
+
+  </div>
+
+  <div style="margin-top:12px;padding:12px;border-radius:14px;background:rgba(245,158,11,0.12);border:1px solid rgba(245,158,11,0.28);">
+    <div style="font-weight:950;margin-bottom:5px;">What to do next</div>
+    <div style="font-size:14px;line-height:1.55;">
+      {next_step_user}
+    </div>
   </div>
-  <div style="margin-top:6px; opacity:0.85;">{html_escape(gate_info)}</div>
-</div>
-"""
 
-        consensus_card = f"""
-<div style="border:1px solid rgba(255,255,255,0.14); border-radius:16px; padding:12px; margin:10px 0;">
-  <div style="font-size:16px; font-weight:950; margin-bottom:6px;">{html_escape(name)} — Final consensus</div>
-  <div style="margin-bottom:6px;">
-    <b>Comparison:</b> TBNet {pretty_state(tb_state)} &nbsp; vs &nbsp; RADIO {pretty_state(radio_state)}
+  <div style="margin-top:12px;padding:12px;border-radius:14px;background:rgba(255,255,255,0.045);border:1px solid rgba(255,255,255,0.12);">
+    <div style="font-weight:900;margin-bottom:5px;">Why this result may or may not be reliable</div>
+    <div style="font-size:13.5px;line-height:1.5;">
+      {html_escape(agreement_text)}
+      <br/><br/>
+      {html_escape(patient_attention_text(out.get("diffuse_risk", False)))}
+      <br/><br/>
+      <b>Image notes:</b>
+      {warning_html}
+    </div>
   </div>
-  <div style="margin-bottom:6px;"><b>Consensus:</b> {html_escape(consensus_label)}</div>
-  <div style="opacity:0.9; margin-bottom:10px;">{html_escape(consensus_detail)}</div>
-  <div style="padding:10px 12px; border-left:6px solid rgba(245,158,11,0.95); background: rgba(245,158,11,0.12); border-radius:12px;">
-    {next_step}
+
+  <div style="margin-top:12px;font-size:12.5px;line-height:1.45;opacity:0.82;">
+    This is an AI screening output only. It cannot confirm or exclude TB. Clinical symptoms and doctor/radiologist review remain important.
   </div>
+
 </div>
 """
 
-        summary_md.append(tb_card)
-        summary_md.append(radio_card)
-        summary_md.append(consensus_card)
+        summary_md.append(patient_card)
 
         # Gallery
         orig_rgb = cv2.cvtColor(cv2.resize(out["orig_gray"], (512, 512)), cv2.COLOR_GRAY2RGB)
@@ -1248,27 +1478,27 @@ def run_analysis(
         mask_overlay = cv2.resize(out["mask_overlay"], (512, 512))
         overlay_big = cv2.resize(out["overlay"], (512, 512))
 
-        gallery_items.append((orig_rgb, f"{name} • ORIGINAL"))
-        gallery_items.append((vis_rgb, f"{name} • PHONE-PROC" if phone_mode else f"{name} • INPUT"))
-        gallery_items.append((mask_overlay, f"{name} • Lung mask overlay"))
+        gallery_items.append((orig_rgb, f"{name} • Original image"))
+        gallery_items.append((vis_rgb, f"{name} • Image checked by the app" if not phone_mode else f"{name} • Phone/WhatsApp cleaned image"))
+        gallery_items.append((mask_overlay, f"{name} • Lung area found by the app"))
         if out["proc_gray"] is not None:
             proc_rgb = cv2.cvtColor(cv2.resize(out["proc_gray"], (512, 512)), cv2.COLOR_GRAY2RGB)
-            gallery_items.append((proc_rgb, f"{name} • Masked model input (224x224)"))
-        gallery_items.append((overlay_big, f"{name} • TBNet Grad-CAM overlay"))
+            gallery_items.append((proc_rgb, f"{name} • Lung-only image checked by AI"))
+        gallery_items.append((overlay_big, f"{name} • Main AI heatmap"))
 
         if radio_raw_overlay is not None:
-            gallery_items.append((cv2.resize(radio_raw_overlay, (512, 512)), f"{name} • RADIO RAW heatmap"))
+            gallery_items.append((cv2.resize(radio_raw_overlay, (512, 512)), f"{name} • Second AI heatmap"))
         if radio_masked_overlay is not None:
-            gallery_items.append((cv2.resize(radio_masked_overlay, (512, 512)), f"{name} • RADIO MASKED heatmap"))
+            gallery_items.append((cv2.resize(radio_masked_overlay, (512, 512)), f"{name} • Second AI lung-only heatmap"))
 
-        # Details (collapsible per image) — FIXED (no welcome HTML here)
+        # Technical details (collapsed per image)
         warn_txt = "\n".join([f"- {w}" for w in out["warnings"]]) if out["warnings"] else "- None"
         details_md.append(
             f"""
 <details>
-  <summary><b>{html_escape(name)}</b> — detailed report</summary>
+  <summary><b>{html_escape(name)}</b> — technical details</summary>
 
-**TBNet**
+**Main AI check / TBNet**
 - Result: **{html_escape(tb_label)}**
 - Probability: {tb_prob_line}
 - Band: {out.get("band", "YELLOW")}
@@ -1276,16 +1506,23 @@ def run_analysis(
 - Lung mask coverage: {cov*100:.1f}%
 - Attention: {attention}
 
-**Consensus**
-- TBNet state: {pretty_state(tb_state)}
-- RADIO state: {pretty_state(radio_state)}
+**Final comparison**
+- Main AI state: {pretty_state(tb_state)}
+- Second AI state: {pretty_state(radio_state)}
 - Consensus label: **{html_escape(consensus_label)}**
-- Detail: {html_escape(consensus_detail)}
+- Technical detail: {html_escape(consensus_detail)}
 
-**Warnings**
+**Image / safety warnings**
 {warn_txt}
 
-**RADIO (full)**
+**Second AI / RADIO full output**
+- Short result: {html_escape(radio_result_short)}
+- Primary score: {radio_primary_line}
+- Raw score: {radio_raw_line}
+- Masked score: {radio_masked_line}
+- Masked ran: {radio_masked_ran}
+- Band: {radio_band}
+
 {radio_text_long}
 
 </details>
@@ -1309,99 +1546,129 @@ def build_ui():
     .card {border:1px solid rgba(255,255,255,0.12); border-radius:14px; padding:14px; margin:10px 0;}
     """
 
-    with gr.Blocks(title="TB X-ray Assistant (TBNet + RADIO)") as demo:
+    with gr.Blocks(title="Chest X-ray TB Screening Assistant") as demo:
 
-        # ---------------------------
-        # Welcome screen (shown first)
-        # ---------------------------
+        # Welcome screen
         with gr.Column(visible=True) as welcome_screen:
-            gr.Markdown('<div class="title">Welcome — TB X-ray Assistant (HF Spaces)</div>')
+            gr.Markdown('<div class="title">Welcome — Chest X-ray TB Screening Assistant</div>')
             gr.HTML(WELCOME_HTML)
-            continue_btn = gr.Button("Continue →", variant="primary")
+            continue_btn = gr.Button("Start checking X-ray images →", variant="primary")
 
-        # ---------------------------
-        # Main app UI (hidden initially)
-        # ---------------------------
+        # Main app UI
         with gr.Column(visible=False) as main_app:
-            gr.Markdown('<div class="title">TB X-ray Assistant (Auto Lung Mask • Research Use)</div>')
+            gr.Markdown('<div class="title">Upload chest X-ray images</div>')
+
             gr.Markdown(
-                f"<div class='subtitle'>Auto lung mask → <b>{MODEL_NAME_TBNET}</b> + Grad-CAM • "
-                f"Optional <b>{MODEL_NAME_RADIO}</b> (C-RADIOv4 + heads) • Clear per-model results + consensus</div>"
+                "<div class='subtitle'>"
+                "Upload one or more chest X-ray images. The app will check the image, show a simple AI screening result, "
+                "and suggest what to do next. This is not a diagnosis."
+                "</div>"
             )
 
             gr.Markdown(
-                "<div class='warnbox'><b>Clinical disclaimer:</b> Decision support only (not diagnostic). "
-                "If TB is clinically suspected, pursue microbiology / CT as appropriate regardless of AI output.</div>"
+                "<div class='warnbox'><b>Important:</b> This app supports medical review only. "
+                "If TB is clinically suspected, please seek clinician/radiologist review and consider CBNAAT/GeneXpert, "
+                "sputum testing, and/or CT chest regardless of the AI result.</div>"
             )
 
             with gr.Row():
-                with gr.Column(scale=1):
-                    gr.Markdown("#### Model settings")
-
-                    tb_weights = gr.Textbox(label="TBNet weights (.pt)", value=DEFAULT_TB_WEIGHTS)
-                    lung_weights = gr.Textbox(label="Lung U-Net weights (.pt)", value=DEFAULT_LUNG_WEIGHTS)
-
-                    backbone = gr.Dropdown(
-                        choices=["efficientnet_b0"],
-                        value="efficientnet_b0",
-                        label="TBNet backbone"
-                    )
+                with gr.Column(scale=2):
+                    gr.Markdown("### 1) Upload X-ray image(s)")
 
-                    threshold = gr.Slider(
-                        0.01, 0.99, value=TBNET_SCREEN_THR, step=0.01,
-                        label=f"Reference threshold (TBNet screen+) = {TBNET_SCREEN_THR:.2f}"
+                    files = gr.Files(
+                        label="Upload chest X-ray images",
+                        file_types=[".png", ".jpg", ".jpeg", ".bmp"]
                     )
 
                     phone_mode = gr.Checkbox(
                         value=False,
-                        label="Phone/WhatsApp Mode (safe: conditional crop + conditional CLAHE)"
+                        label="This image is a phone photo, WhatsApp image, screenshot, or has borders"
                     )
+
                     gr.Markdown(
-                        "<div class='subtitle'>Enable for WhatsApp images, phone photos, or screenshots. "
-                        "Leave off for clean digital exports.</div>"
+                        "<div class='subtitle'>"
+                        "Turn this on for images taken from a phone camera, WhatsApp, screenshots, cropped images, "
+                        "or images with black/white borders."
+                        "</div>"
                     )
 
-                    use_radio = gr.Checkbox(value=True, label=f"Enable {MODEL_NAME_RADIO}")
-                    radio_gate = gr.Slider(
-                        0.10, 0.40, value=RADIO_GATE_DEFAULT, step=0.01,
-                        label="RADIO masked gate (run masked head if lung coverage ≥ gate)"
+                    use_radio = gr.Checkbox(
+                        value=True,
+                        label="Use a second AI check for comparison"
                     )
 
-                    gr.Markdown(
-                        "<div class='warnbox'><b>Fail-safe:</b> If lung segmentation is too small or looks unreliable, "
-                        f"{MODEL_NAME_TBNET} scoring is disabled to avoid unsafe outputs.</div>"
-                    )
+                    run_btn = gr.Button("Check X-ray image(s)", variant="primary")
+                    status = gr.Textbox(label="Status", value="Ready to check images.", interactive=False)
 
-                    gr.Markdown(
-                        f"<div class='subtitle'>Device: <b>{DEVICE}</b> (FORCE_CPU={FORCE_CPU})</div>"
-                    )
+                with gr.Column(scale=1):
+                    gr.Markdown("### 2) What you will get")
+
+                    gr.Markdown("""
+<div class='legend'>
+<b>The report will show:</b><br/><br/>
+✅ A simple result: Low / Unclear / Needs review / TB-like pattern seen<br/>
+✅ Image reliability: whether the image was clear enough<br/>
+✅ Lung area check: whether the app found the lung region<br/>
+✅ Heatmap images: where the AI focused<br/>
+✅ Suggested next step
+</div>
+""")
+
+                    with gr.Accordion("Advanced settings — usually leave unchanged", open=False):
+                        tb_weights = gr.Textbox(label="Main AI model weights", value=DEFAULT_TB_WEIGHTS)
+                        lung_weights = gr.Textbox(label="Lung area model weights", value=DEFAULT_LUNG_WEIGHTS)
+
+                        backbone = gr.Dropdown(
+                            choices=["efficientnet_b0"],
+                            value="efficientnet_b0",
+                            label="Main AI backbone"
+                        )
+
+                        threshold = gr.Slider(
+                            0.01, 0.99, value=TBNET_SCREEN_THR, step=0.01,
+                            label=f"Screening threshold = {TBNET_SCREEN_THR:.2f}"
+                        )
+
+                        radio_gate = gr.Slider(
+                            0.10, 0.40, value=RADIO_GATE_DEFAULT, step=0.01,
+                            label="Second AI lung-mask gate"
+                        )
+
+                        gr.Markdown(
+                            f"<div class='subtitle'>Device: <b>{DEVICE}</b> | FORCE_CPU={FORCE_CPU}</div>"
+                        )
 
                     back_btn = gr.Button("← Back to Welcome", variant="secondary")
 
-                with gr.Column(scale=2):
-                    gr.Markdown("#### Upload images")
-                    files = gr.Files(
-                        label="Upload one or multiple X-ray images",
-                        file_types=[".png", ".jpg", ".jpeg", ".bmp"]
-                    )
-                    run_btn = gr.Button("Run Analysis", variant="primary")
-                    status = gr.Textbox(label="Status", value="Ready.", interactive=False)
+            gr.Markdown("### Results")
+            summary = gr.HTML(
+                "<div style='padding:14px;border-radius:14px;background:rgba(255,255,255,0.04);"
+                "border:1px solid rgba(255,255,255,0.10);'>"
+                "Upload one or more images, then click <b>Check X-ray image(s)</b>."
+                "</div>"
+            )
 
-                    gr.Markdown("""
-<div class='legend'><b>Gallery legend:</b><br/>
-1) ORIGINAL &nbsp;•&nbsp; 2) INPUT / PHONE-PROC &nbsp;•&nbsp; 3) Lung mask overlay &nbsp;•&nbsp;
-4) Masked model input &nbsp;•&nbsp; 5) TBNet Grad-CAM &nbsp;•&nbsp; 6) RADIO heatmaps</div>
+            gr.Markdown("### Image views")
+            gr.Markdown("""
+<div class='legend'>
+<b>How to read the image views:</b><br/>
+<b>Original</b> = your uploaded image<br/>
+<b>Image checked by the app</b> = image after basic cleanup if selected<br/>
+<b>Lung area found by the app</b> = area the app thinks is lung<br/>
+<b>AI heatmap</b> = area the AI focused on most
+</div>
 """)
 
-            gr.Markdown("#### Summary (per image)")
-            summary = gr.Markdown("Upload images and click <b>Run Analysis</b>.")
-            gallery = gr.Gallery(label="Visual outputs", columns=3, height=560)
+            gallery = gr.Gallery(label="Image views", columns=3, height=560)
 
             with gr.Row():
                 with gr.Column(scale=1):
                     disclaimer_box = gr.Markdown(CLINICAL_DISCLAIMER)
                 with gr.Column(scale=2):
-                    gr.Markdown("#### Detailed report (expand per image)")
+                    gr.Markdown("### Technical details")
+                    gr.Markdown(
+                        "This section is mainly for clinicians, researchers, or developers."
+                    )
                     details = gr.Markdown("")
 
             run_btn.click(
@@ -1419,9 +1686,7 @@ def build_ui():
                 outputs=[summary, gallery, details, disclaimer_box, status]
             )
 
-        # ---------------------------
         # Transitions
-        # ---------------------------
         continue_btn.click(
             fn=lambda: (gr.update(visible=False), gr.update(visible=True)),
             inputs=[],
@@ -1443,7 +1708,7 @@ if __name__ == "__main__":
         server_name="0.0.0.0",
         server_port=int(os.environ.get("PORT", 7860)),
         show_error=True,
-        ssr_mode=False,   # avoids Gradio SSR localhost/proxy issue
+        ssr_mode=False,
         css="""
         .title {font-size: 28px; font-weight: 900; margin-bottom: 6px;}
         .subtitle {font-size: 14px; opacity: 0.88; margin-bottom: 14px;}