Make calibration report point-centric with visual overlays

jetson/main.py

@@ -9,6 +9,7 @@ import os
 import cv2
 import time
 import base64
+import json
 import argparse
 import threading
 import numpy as np
@@ -47,6 +48,158 @@ def _init_calibration_steps():
     }
 
 
+def _build_point_report(side, matched_image_points=None):
+    """Build report of expected template points and which were matched."""
+    template = get_half_court_intersections(side)
+    matched_image_points = matched_image_points or {}
+    points = []
+    found_count = 0
+
+    for name, world_pt in template.items():
+        img_pt = matched_image_points.get(name)
+        is_found = img_pt is not None
+        if is_found:
+            found_count += 1
+        points.append({
+            'name': name,
+            'found': is_found,
+            'world_xyz': [float(world_pt[0]), float(world_pt[1]), float(world_pt[2])],
+            'image_xy': [float(img_pt[0]), float(img_pt[1])] if is_found else None,
+        })
+
+    target_count = len(points)
+    return {
+        'target_count': target_count,
+        'found_count': found_count,
+        'missing_count': target_count - found_count,
+        'points': points,
+    }
+
+
+def _render_point_schematic(side, point_report):
+    """Render flat half-court scheme with found/missing points."""
+    width = 760
+    height = 460
+    margin = 48
+    canvas = np.zeros((height, width, 3), dtype=np.uint8)
+    canvas[:] = (12, 18, 32)
+
+    # Half-court dimensions
+    half_len = HALF_COURT_LENGTH  # 6.7m
+    court_w = COURT_WIDTH  # 6.1m
+    kitchen_x = HALF_COURT_LENGTH - 2.13  # 4.57m from baseline
+
+    draw_w = width - 2 * margin
+    draw_h = height - 2 * margin
+
+    def to_px(local_x, y):
+        px = int(margin + (local_x / half_len) * draw_w)
+        py = int(margin + (y / court_w) * draw_h)
+        return px, py
+
+    # Court frame
+    tl = to_px(0, 0)
+    br = to_px(half_len, court_w)
+    cv2.rectangle(canvas, tl, br, (200, 200, 200), 2)
+
+    # Kitchen and center service line
+    p1 = to_px(kitchen_x, 0)
+    p2 = to_px(kitchen_x, court_w)
+    cv2.line(canvas, p1, p2, (180, 180, 180), 1)
+    c1 = to_px(0, court_w / 2)
+    c2 = to_px(kitchen_x, court_w / 2)
+    cv2.line(canvas, c1, c2, (140, 140, 140), 1)
+
+    # Net line
+    n1 = to_px(half_len, 0)
+    n2 = to_px(half_len, court_w)
+    cv2.line(canvas, n1, n2, (100, 160, 240), 2)
+
+    # Helper: convert world X to local baseline->net axis for each side
+    def to_local_x(world_x):
+        if side == 'left':
+            return world_x
+        return COURT_LENGTH - world_x
+
+    for point in point_report.get('points', []):
+        world = point.get('world_xyz') or [0.0, 0.0, 0.0]
+        local_x = to_local_x(world[0])
+        local_y = world[1]
+        px, py = to_px(local_x, local_y)
+        color = (70, 220, 130) if point.get('found') else (80, 80, 230)
+        cv2.circle(canvas, (px, py), 8, color, -1)
+        cv2.circle(canvas, (px, py), 12, color, 1)
+        cv2.putText(canvas, point.get('name', '?'), (px + 10, py - 8),
+                    cv2.FONT_HERSHEY_SIMPLEX, 0.42, color, 1)
+
+    summary = f"Target: {point_report.get('target_count', 0)}  Found: {point_report.get('found_count', 0)}  Missing: {point_report.get('missing_count', 0)}"
+    cv2.putText(canvas, summary, (margin, height - 14),
+                cv2.FONT_HERSHEY_SIMPLEX, 0.6, (220, 220, 220), 1)
+
+    ok, jpg = cv2.imencode('.jpg', canvas, [cv2.IMWRITE_JPEG_QUALITY, 90])
+    if not ok:
+        return None
+    return base64.b64encode(jpg.tobytes()).decode('ascii')
+
+
+def _render_points_on_frame(frame, point_report):
+    """Render only detected template points on top of the camera frame."""
+    overlay = frame.copy()
+    found_count = 0
+    for point in point_report.get('points', []):
+        img_pt = point.get('image_xy')
+        if not img_pt:
+            continue
+        found_count += 1
+        x = int(img_pt[0])
+        y = int(img_pt[1])
+        cv2.circle(overlay, (x, y), 9, (70, 220, 130), 2)
+        cv2.circle(overlay, (x, y), 3, (70, 220, 130), -1)
+        cv2.putText(overlay, point.get('name', '?'), (x + 12, y - 6),
+                    cv2.FONT_HERSHEY_SIMPLEX, 0.45, (70, 220, 130), 1)
+
+    title = f"Template points: {found_count}/{point_report.get('target_count', 0)}"
+    cv2.rectangle(overlay, (8, 8), (360, 36), (0, 0, 0), -1)
+    cv2.putText(overlay, title, (14, 28),
+                cv2.FONT_HERSHEY_SIMPLEX, 0.6, (200, 255, 220), 1)
+
+    ok, jpg = cv2.imencode('.jpg', overlay, [cv2.IMWRITE_JPEG_QUALITY, 88])
+    if not ok:
+        return None
+    return base64.b64encode(jpg.tobytes()).decode('ascii')
+
+
+def _save_calibration_report(report_payload):
+    """Persist last calibration report so it can be read outside UI."""
+    if not _args or not getattr(_args, 'calibration_dir', None):
+        return
+
+    report_dir = os.path.join(_args.calibration_dir, 'calibration_reports')
+    os.makedirs(report_dir, exist_ok=True)
+
+    # Save compact JSON without large base64 payloads.
+    compact = {
+        'timestamp': report_payload.get('timestamp'),
+        'result': {},
+    }
+    for sid, entry in (report_payload.get('result') or {}).items():
+        clean = dict(entry)
+        clean.pop('debug_image', None)
+        clean.pop('points_overlay_image', None)
+        clean.pop('schematic_image', None)
+        compact['result'][sid] = clean
+
+    latest_path = os.path.join(report_dir, 'latest.json')
+    ts_path = os.path.join(report_dir, f"report_{int(time.time())}.json")
+
+    for path in [latest_path, ts_path]:
+        try:
+            with open(path, 'w') as f:
+                json.dump(compact, f, indent=2)
+        except Exception as exc:
+            print(f"[CALIBRATION] Failed to write report {path}: {exc}")
+
+
 def auto_calibrate():
     """Calibrate cameras by detecting court line intersections and matching
     them to the known pickleball court template.
@@ -64,9 +217,11 @@ def auto_calibrate():
     results = {}
 
     for sensor_id, reader in _cam_readers.items():
+        side = 'left' if sensor_id == 0 else 'right'
         steps = _init_calibration_steps()
         frame = reader.grab()
         if frame is None:
+            point_report = _build_point_report(side)
             steps['green_mask'] = {'status': 'fail', 'detail': 'No frame available'}
             steps['line_segments'] = {'status': 'fail', 'detail': 'Calibration aborted'}
             steps['merged_lines'] = {'status': 'fail', 'detail': 'Calibration aborted'}
@@ -78,11 +233,13 @@ def auto_calibrate():
                 'ok': False,
                 'error': f'CAM {sensor_id}: No frame available',
                 'steps': steps,
+                'point_report': point_report,
+                'schematic_image': _render_point_schematic(side, point_report),
+                'points_overlay_image': None,
             }
             continue
 
         h, w = frame.shape[:2]
-        side = 'left' if sensor_id == 0 else 'right'
         debug_frame = frame.copy()
 
         # Step 1: Detect green court mask
@@ -93,6 +250,7 @@ def auto_calibrate():
 
         green_pct = np.count_nonzero(green_mask) / (w * h) * 100
         if green_pct < 5:
+            point_report = _build_point_report(side)
             steps['green_mask'] = {'status': 'fail', 'detail': f'Green area too small: {green_pct:.1f}%'}
             steps['line_segments'] = {'status': 'fail', 'detail': 'Calibration aborted'}
             steps['merged_lines'] = {'status': 'fail', 'detail': 'Calibration aborted'}
@@ -108,6 +266,9 @@ def auto_calibrate():
                 'error': f'CAM {sensor_id}: Green area too small ({green_pct:.0f}%)',
                 'debug_image': base64.b64encode(jpeg.tobytes()).decode('ascii'),
                 'steps': steps,
+                'point_report': point_report,
+                'schematic_image': _render_point_schematic(side, point_report),
+                'points_overlay_image': _render_points_on_frame(debug_frame, point_report),
             }
             continue
         steps['green_mask'] = {'status': 'ok', 'detail': f'Green area: {green_pct:.1f}%'}
@@ -153,6 +314,7 @@ def auto_calibrate():
             if quad is not None:
                 cal, cam_pos, mapping_info = _calibrate_from_quad(quad, side, w, h)
                 if cal is not None:
+                    point_report = _build_point_report(side)
                     steps['template_match'] = {
                         'status': 'ok',
                         'detail': 'Low intersections, used quad fallback mapping'
@@ -170,9 +332,11 @@ def auto_calibrate():
                         n_lines=len(merged),
                         n_intersections=len(intersections),
                         n_points_matched=0,
+                        point_report=point_report,
                     )
                     continue
 
+            point_report = _build_point_report(side)
             steps['template_match'] = {'status': 'fail', 'detail': 'Not enough intersections for template fit'}
             steps['camera_pose'] = {'status': 'fail', 'detail': 'solvePnP skipped'}
             steps['overlay'] = {'status': 'fail', 'detail': 'No calibration output'}
@@ -184,6 +348,9 @@ def auto_calibrate():
                 'error': f'CAM {sensor_id}: {len(intersections)} intersections (need 4+) from {len(merged)} lines',
                 'debug_image': base64.b64encode(jpeg.tobytes()).decode('ascii'),
                 'steps': steps,
+                'point_report': point_report,
+                'schematic_image': _render_point_schematic(side, point_report),
+                'points_overlay_image': _render_points_on_frame(debug_frame, point_report),
             }
             continue
 
@@ -197,6 +364,7 @@ def auto_calibrate():
             if quad is not None:
                 cal, cam_pos, mapping_info = _calibrate_from_quad(quad, side, w, h)
                 if cal is not None:
+                    point_report = _build_point_report(side)
                     steps['template_match'] = {
                         'status': 'ok',
                         'detail': 'Template match weak, used quad fallback mapping'
@@ -214,9 +382,11 @@ def auto_calibrate():
                         n_lines=len(merged),
                         n_intersections=len(intersections),
                         n_points_matched=0,
+                        point_report=point_report,
                     )
                     continue
 
+            point_report = _build_point_report(side)
             steps['template_match'] = {'status': 'fail', 'detail': 'Could not match intersections to template'}
             steps['camera_pose'] = {'status': 'fail', 'detail': 'solvePnP skipped'}
             steps['overlay'] = {'status': 'fail', 'detail': 'No calibration output'}
@@ -228,10 +398,14 @@ def auto_calibrate():
                 'error': f'CAM {sensor_id}: Could not match court pattern',
                 'debug_image': base64.b64encode(jpeg.tobytes()).decode('ascii'),
                 'steps': steps,
+                'point_report': point_report,
+                'schematic_image': _render_point_schematic(side, point_report),
+                'points_overlay_image': _render_points_on_frame(debug_frame, point_report),
             }
             continue
 
         n_matched = len(match['image_points'])
+        point_report = _build_point_report(side, match['image_points'])
         steps['template_match'] = {
             'status': 'ok',
             'detail': f'Matched {n_matched}/{len(template)} template points'
@@ -259,6 +433,9 @@ def auto_calibrate():
                 'error': f'CAM {sensor_id}: solvePnP failed ({exc})',
                 'debug_image': base64.b64encode(jpeg.tobytes()).decode('ascii'),
                 'steps': steps,
+                'point_report': point_report,
+                'schematic_image': _render_point_schematic(side, point_report),
+                'points_overlay_image': _render_points_on_frame(debug_frame, point_report),
             }
             continue
 
@@ -288,14 +465,22 @@ def auto_calibrate():
             n_lines=len(merged),
             n_intersections=len(intersections),
             n_points_matched=n_matched,
+            point_report=point_report,
         )
 
+    report_payload = {
+        'timestamp': time.time(),
+        'result': results,
+    }
+    state['last_calibration_report'] = report_payload
+    _save_calibration_report(report_payload)
+
     return results
 
 
 def _finalize_calibration(cal, cam_pos, sensor_id, side, debug_frame,
                           results, method_info, steps, n_segments, n_lines,
-                          n_intersections, n_points_matched):
+                          n_intersections, n_points_matched, point_report):
     """Save calibration and build result dict."""
     steps['camera_pose'] = {
         'status': 'ok',
@@ -322,11 +507,16 @@ def _finalize_calibration(cal, cam_pos, sensor_id, side, debug_frame,
     _, jpeg = cv2.imencode('.jpg', debug_frame, [cv2.IMWRITE_JPEG_QUALITY, 85])
 
     matched_lines_3d = _get_half_court_lines_3d(side)
+    schematic_image = _render_point_schematic(side, point_report)
+    points_overlay_image = _render_points_on_frame(debug_frame, point_report)
 
     results[str(sensor_id)] = {
         'ok': True,
         'camera_position': cam_pos.tolist(),
         'debug_image': base64.b64encode(jpeg.tobytes()).decode('ascii'),
+        'points_overlay_image': points_overlay_image,
+        'schematic_image': schematic_image,
+        'point_report': point_report,
         'matched_lines_3d': matched_lines_3d,
         'points_matched': n_points_matched,
         'intersections_detected': n_intersections,

src/web/app.py

@@ -25,6 +25,7 @@ state = {
     'events': [],            # recent VAR events
     'last_var': None,        # last VAR event with snapshot
     'calibrate_fn': None,    # callback for calibration trigger
+    'last_calibration_report': None,
 }
 
 
@@ -147,5 +148,39 @@ def api_calibration_data():
     return jsonify(result)
 
 
+@app.route('/api/calibration/report')
+def api_calibration_report():
+    """Return last detailed calibration report (state fallback to disk)."""
+    full = request.args.get('full') == '1'
+
+    report = state.get('last_calibration_report')
+    if report is not None:
+        if full:
+            return jsonify(report)
+
+        compact = {'timestamp': report.get('timestamp'), 'result': {}}
+        for sid, entry in (report.get('result') or {}).items():
+            clean = dict(entry)
+            clean.pop('debug_image', None)
+            clean.pop('points_overlay_image', None)
+            clean.pop('schematic_image', None)
+            compact['result'][sid] = clean
+        return jsonify(compact)
+
+    cal_dir = state.get('calibration_dir')
+    if not cal_dir:
+        return jsonify({'ok': False, 'error': 'Calibration dir not configured'}), 404
+
+    report_path = Path(cal_dir) / 'calibration_reports' / 'latest.json'
+    if not report_path.exists():
+        return jsonify({'ok': False, 'error': 'No calibration report found'}), 404
+
+    try:
+        with open(report_path, 'r') as f:
+            return jsonify(json.load(f))
+    except Exception as exc:
+        return jsonify({'ok': False, 'error': str(exc)}), 500
+
+
 def run(host='0.0.0.0', port=8080):
     app.run(host=host, port=port, threaded=True)

src/web/templates/index.html

@@ -314,11 +314,6 @@
             border-radius: 6px;
             background: #0d0d20;
         }
-        .flow-grid {
-            display: grid;
-            grid-template-columns: 1fr 1fr;
-            gap: 12px;
-        }
         .flow-card {
             border: 1px solid #2a2a4a;
             border-radius: 6px;
@@ -333,40 +328,77 @@
             text-transform: uppercase;
             font-weight: 700;
         }
-        .flow-steps {
+        .cal-report-card {
+            border: 1px solid #2a2a4a;
+            border-radius: 6px;
+            background: #0d0d20;
+            padding: 12px;
             display: flex;
             flex-direction: column;
+            gap: 10px;
+        }
+        .cal-point-summary {
+            font-size: 14px;
+            color: #d7d7e0;
+            line-height: 1.4;
+        }
+        .cal-point-summary b {
+            color: #4ecca3;
+        }
+        .cal-point-strip {
+            display: flex;
+            flex-wrap: wrap;
             gap: 6px;
         }
-        .flow-step {
+        .point-chip {
+            font-size: 11px;
+            border-radius: 999px;
+            padding: 3px 8px;
             border: 1px solid #2a2a4a;
-            border-radius: 4px;
+            color: #aaa;
-            padding: 6px 8px;
+            background: #111128;
-            background: #10102a;
-            font-size: 12px;
         }
-        .flow-step .step-head {
+        .point-chip.found {
-            display: flex;
+            border-color: #2e8f6e;
-            justify-content: space-between;
+            color: #bff1df;
+            background: #12392f;
+        }
+        .point-chip.missing {
+            border-color: #8d3b3b;
+            color: #ffd8d8;
+            background: #3c1b1b;
+        }
+        .cal-report-images {
+            display: grid;
+            grid-template-columns: 1fr;
             gap: 8px;
         }
-        .flow-step .step-name {
+        .cal-image-box {
-            color: #ddd;
+            position: relative;
-            font-weight: 600;
+            border: 1px solid #2a2a4a;
+            border-radius: 6px;
+            overflow: hidden;
+            padding: 8px;
+            background: #10102a;
         }
-        .flow-step .step-status {
+        .cal-image-title {
-            color: #888;
+            font-size: 10px;
-            font-size: 11px;
+            color: #7fd8be;
+            margin-bottom: 6px;
             text-transform: uppercase;
+            letter-spacing: 0.4px;
         }
-        .flow-step .step-detail {
+        .cal-image-box img {
-            margin-top: 4px;
+            width: 100%;
-            color: #8e8eb0;
+            border-radius: 4px;
-            font-size: 11px;
+            border: 1px solid #333;
+            display: block;
+            cursor: pointer;
+        }
+        .cal-image-box img[src=""],
+        .cal-image-box img:not([src]) {
+            display: none;
         }
-        .flow-step.ok .step-status { color: #4ecca3; }
-        .flow-step.fail .step-status { color: #ff6666; }
-        .flow-step.pending .step-status { color: #aaa; }
         .calibration-3d-wrap {
             border: 1px solid #2a2a4a;
             border-radius: 6px;
@@ -376,44 +408,13 @@
         .calibration-3d-wrap .viewport-3d {
             border-top: none;
         }
-        .cal-debug-images {
+        .report-link {
-            display: grid;
+            color: #79c9ff;
-            grid-template-columns: 1fr 1fr;
+            text-decoration: none;
-            gap: 8px;
+            font-size: 12px;
         }
-        .cal-debug-card {
+        .report-link:hover {
-            position: relative;
+            text-decoration: underline;
-            border: 1px solid #2a2a4a;
-            border-radius: 6px;
-            overflow: hidden;
-            background: #0d0d20;
-            padding: 8px;
-        }
-        .cal-debug-card img {
-            width: 100%;
-            border-radius: 4px;
-            border: 1px solid #333;
-            display: block;
-            cursor: pointer;
-        }
-        .cal-debug-card .cal-live {
-            opacity: 0.5;
-        }
-        .cal-debug-card img[src=""],
-        .cal-debug-card img:not([src]) {
-            display: none;
-        }
-        .cal-debug-label {
-            position: absolute;
-            top: 4px;
-            left: 4px;
-            background: rgba(0,0,0,0.7);
-            color: #4ecca3;
-            padding: 2px 6px;
-            border-radius: 3px;
-            font-size: 10px;
-            font-weight: 600;
-            z-index: 1;
         }
 
         /* Fullscreen image overlay */
@@ -450,8 +451,7 @@
                 max-width: 100%;
             }
             .cal-cameras,
-            .flow-grid,
+            .cal-report-images {
-            .cal-debug-images {
                 grid-template-columns: 1fr;
             }
         }
@@ -512,25 +512,38 @@
                 <div id="calPos0" style="color:#4ecca3"></div>
                 <div id="calPos1" style="color:#ff88cc"></div>
             </div>
-        </div>
+            <div style="margin-top:8px">
-        <div class="flow-grid">
+                <a class="report-link" href="/api/calibration/report" target="_blank" rel="noopener">Open Last Calibration JSON Report</a>
-            <div class="flow-card">
-                <div class="flow-title">CAM 0 Calibration Steps</div>
-                <div id="calFlowCam0" class="flow-steps"></div>
-            </div>
-            <div class="flow-card">
-                <div class="flow-title">CAM 1 Calibration Steps</div>
-                <div id="calFlowCam1" class="flow-steps"></div>
             </div>
         </div>
-        <div class="cal-debug-images">
+        <div class="cal-report-card">
-            <div class="cal-debug-card">
+            <div class="flow-title">CAM 0 Point Report</div>
-                <div class="cal-debug-label">CAM 0 RESULT</div>
+            <div id="calPointSummary0" class="cal-point-summary">Waiting for calibration...</div>
-                <img id="calDebugImg0" alt="CAM 0 calibration result">
+            <div id="calPointStrip0" class="cal-point-strip"></div>
+            <div class="cal-report-images">
+                <div class="cal-image-box">
+                    <div class="cal-image-title">Detected points on frame</div>
+                    <img id="calPointsImg0" alt="CAM 0 points overlay">
+                </div>
+                <div class="cal-image-box">
+                    <div class="cal-image-title">Flat court scheme</div>
+                    <img id="calSchemeImg0" alt="CAM 0 flat scheme">
+                </div>
+            </div>
+        </div>
+        <div class="cal-report-card">
+            <div class="flow-title">CAM 1 Point Report</div>
+            <div id="calPointSummary1" class="cal-point-summary">Waiting for calibration...</div>
+            <div id="calPointStrip1" class="cal-point-strip"></div>
+            <div class="cal-report-images">
+                <div class="cal-image-box">
+                    <div class="cal-image-title">Detected points on frame</div>
+                    <img id="calPointsImg1" alt="CAM 1 points overlay">
+                </div>
+                <div class="cal-image-box">
+                    <div class="cal-image-title">Flat court scheme</div>
+                    <img id="calSchemeImg1" alt="CAM 1 flat scheme">
                 </div>
-            <div class="cal-debug-card">
-                <div class="cal-debug-label">CAM 1 RESULT</div>
-                <img id="calDebugImg1" alt="CAM 1 calibration result">
             </div>
         </div>
         <div class="calibration-3d-wrap">
@@ -538,11 +551,11 @@
             <div class="viewport-3d" id="calibration-3d"></div>
         </div>
         <div class="flow-card">
-            <div class="flow-title">Workflow Legend</div>
+            <div class="flow-title">What You See</div>
             <div style="font-size:12px;color:#aaa;line-height:1.5">
-                1) detect court ROI → 2) detect line segments → 3) merge lines → 4) get intersections →
+                Each camera shows a target point set and found/missing points.
-                5) match to template points → 6) solve camera pose → 7) overlay reconstructed geometry.
+                Left image: found template points on the real frame.
-                Green steps are confirmed, red steps failed, gray steps are pending/skipped.
+                Right image: flat half-court scheme with found/missing markers.
             </div>
         </div>
     </div>
@@ -608,60 +621,66 @@ window.addEventListener('popstate', function() {
 if (activeTab !== 'camera') switchTab(activeTab);
 
 // ===================== Calibration =====================
-var CALIBRATION_STEP_ORDER = [
+function renderPointReport(camId, camResult) {
-    'green_mask',
+    var summaryEl = document.getElementById('calPointSummary' + camId);
-    'line_segments',
+    var stripEl = document.getElementById('calPointStrip' + camId);
-    'merged_lines',
+    var pointsImg = document.getElementById('calPointsImg' + camId);
-    'intersections',
+    var schemeImg = document.getElementById('calSchemeImg' + camId);
-    'template_match',
+    if (!summaryEl || !stripEl || !pointsImg || !schemeImg) return;
-    'camera_pose',
-    'overlay'
-];
 
-var CALIBRATION_STEP_LABELS = {
+    if (!camResult) {
-    green_mask: '1. Court ROI',
+        summaryEl.innerHTML = 'Waiting for calibration...';
-    line_segments: '2. White Segments',
+        stripEl.innerHTML = '';
-    merged_lines: '3. Merge Lines',
+        pointsImg.removeAttribute('src');
-    intersections: '4. Intersections',
+        schemeImg.removeAttribute('src');
-    template_match: '5. Template Match',
+        return;
-    camera_pose: '6. Camera Pose',
-    overlay: '7. Geometry Overlay'
-};
-
-function renderCalibrationSteps(containerId, steps, fallbackError) {
-    var el = document.getElementById(containerId);
-    if (!el) return;
-
-    var html = '';
-    for (var i = 0; i < CALIBRATION_STEP_ORDER.length; i++) {
-        var key = CALIBRATION_STEP_ORDER[i];
-        var item = steps && steps[key] ? steps[key] : { status: 'pending', detail: 'No data yet' };
-        var status = item.status || 'pending';
-        var detail = item.detail || '';
-        html += '<div class="flow-step ' + status + '">';
-        html += '  <div class="step-head">';
-        html += '    <div class="step-name">' + CALIBRATION_STEP_LABELS[key] + '</div>';
-        html += '    <div class="step-status">' + status + '</div>';
-        html += '  </div>';
-        html += '  <div class="step-detail">' + detail + '</div>';
-        html += '</div>';
     }
 
-    if (fallbackError) {
+    var report = camResult.point_report || {};
-        html += '<div class="flow-step fail">';
+    var target = report.target_count || 0;
-        html += '  <div class="step-head"><div class="step-name">Error</div><div class="step-status">fail</div></div>';
+    var found = report.found_count || 0;
-        html += '  <div class="step-detail">' + fallbackError + '</div>';
+    var missing = report.missing_count || 0;
-        html += '</div>';
+    var method = camResult.method ? (' | ' + camResult.method) : '';
+    var ok = !!camResult.ok;
+
+    if (ok) {
+        summaryEl.innerHTML =
+            'Target points: <b>' + target + '</b> | Found: <b>' + found + '</b> | Missing: <b>' + missing + '</b>' + method;
+    } else {
+        summaryEl.innerHTML =
+            'Target points: <b>' + target + '</b> | Found: <b>' + found + '</b> | Missing: <b>' + missing + '</b><br>' +
+            '<span style="color:#ff8080">' + (camResult.error || 'Calibration failed') + '</span>';
     }
 
-    el.innerHTML = html;
+    var chips = '';
+    var points = report.points || [];
+    for (var i = 0; i < points.length; i++) {
+        var p = points[i];
+        var cls = p.found ? 'found' : 'missing';
+        chips += '<span class="point-chip ' + cls + '">' + p.name + '</span>';
+    }
+    stripEl.innerHTML = chips;
+
+    if (camResult.points_overlay_image) {
+        pointsImg.src = 'data:image/jpeg;base64,' + camResult.points_overlay_image;
+    } else if (camResult.debug_image) {
+        pointsImg.src = 'data:image/jpeg;base64,' + camResult.debug_image;
+    } else {
+        pointsImg.removeAttribute('src');
+    }
+
+    if (camResult.schematic_image) {
+        schemeImg.src = 'data:image/jpeg;base64,' + camResult.schematic_image;
+    } else {
+        schemeImg.removeAttribute('src');
+    }
 }
 
 function updateCalibrationFlow(result) {
     var cam0 = result && result['0'] ? result['0'] : null;
     var cam1 = result && result['1'] ? result['1'] : null;
-    renderCalibrationSteps('calFlowCam0', cam0 ? cam0.steps : null, cam0 && cam0.error ? cam0.error : '');
+    renderPointReport('0', cam0);
-    renderCalibrationSteps('calFlowCam1', cam1 ? cam1.steps : null, cam1 && cam1.error ? cam1.error : '');
+    renderPointReport('1', cam1);
 }
 
 function doCalibrate() {
@@ -670,10 +689,7 @@ function doCalibrate() {
     btn.disabled = true;
     btn.textContent = 'Calibrating...';
     errEl.style.display = 'none';
-    updateCalibrationFlow({
+    updateCalibrationFlow(null);
-        '0': { steps: { green_mask: { status: 'pending', detail: 'Running calibration flow...' } } },
-        '1': { steps: { green_mask: { status: 'pending', detail: 'Running calibration flow...' } } }
-    });
 
     fetch('/api/calibration/trigger', { method: 'POST' })
         .then(function(r) { return r.json(); })
@@ -681,23 +697,12 @@ function doCalibrate() {
             btn.disabled = false;
             updateCalibrationFlow(data.result || null);
 
-            // Show debug images from calibration
-            if (data.result) {
-                for (var sid in data.result) {
-                    var r = data.result[sid];
-                    if (r.debug_image) {
-                        var imgEl = document.getElementById('calDebugImg' + sid);
-                        if (imgEl) imgEl.src = 'data:image/jpeg;base64,' + r.debug_image;
-                    }
-                }
-            }
-
             if (data.ok) {
                 btn.textContent = 'Re-run Calibration Flow';
                 errEl.style.display = 'none';
                 updateCalibrationStatus();
 
-                // Show computed camera positions and line stats
+                // Show computed camera positions
                 var posEl = document.getElementById('calPositions');
                 if (posEl && data.result) {
                     posEl.style.display = 'block';
@@ -750,7 +755,7 @@ function doCalibrate() {
 }
 
 // ===================== Fullscreen image viewer =====================
-document.querySelectorAll('.cal-debug-card img').forEach(function(img) {
+document.querySelectorAll('.cal-image-box img').forEach(function(img) {
     img.addEventListener('click', function() {
         if (!this.src || this.src === location.href) return;
         document.getElementById('fullscreenImg').src = this.src;