Fix front-facing golf metrics: improve accuracy and reliability

- Torso side-bend: standardize sign convention, use eyes+hips for de-roll
- Hip sway: add robust baseline with MAD jitter, two-stage denoising, yaw correction
- Wrist hinge: report acute angles (50-70° pro range) instead of obtuse
- Hip-shoulder separation: improve span ratio scaling, clamp to 0.7-1.0 range
- Fix format string errors with None value safety checks
- Enhanced debug logging with normalized sway and trust ratios

app/models/llm_analyzer.py

@@ -24,9 +24,9 @@ try:
         get_knee_flexion_grading,
         get_head_drop_grading,
         get_shoulder_tilt_impact_grading,
-        get_hip_turn_impact_grading,
         get_hip_sway_grading,
-        get_wrist_hinge_grading
+        get_wrist_hinge_grading,
+        get_hip_shoulder_separation_impact_grading
     )
 except ImportError:
     # Fallback if imports fail - define minimal grading functions
@@ -38,13 +38,14 @@ except ImportError:
         return {'value': value, 'status': 'n/a', 'badge': '⚪'}
     def get_hip_depth_grading(value, confidence):
         return {'value': value, 'status': 'n/a', 'badge': '⚪'}
-    # Hip turn grading function removed per user request
     def get_shoulder_tilt_impact_grading(value, confidence):
         return {'value': value, 'status': 'n/a', 'badge': '⚪'}
     def get_hip_sway_grading(value, confidence, position):
         return {'value': value, 'status': 'n/a', 'badge': '⚪'}
     def get_wrist_hinge_grading(value, confidence, position):
         return {'value': value, 'status': 'n/a', 'badge': '⚪'}
+    def get_hip_shoulder_separation_impact_grading(value, confidence):
+        return {'value': value, 'status': 'n/a', 'badge': '⚪'}
     def get_head_drop_grading(value, confidence):
         """Grade head drop metric based on percentage of torso length
         
@@ -352,23 +353,25 @@ def compute_front_facing_core_metrics(pose_data, swing_phases, frames=None, worl
     
     # Process each front-facing metric with new calibration values
     for metric_name, metric_data in front_metrics.items():
-        if 'hip_turn_impact' in metric_name and isinstance(metric_data, dict) and 'grade_label' in metric_data:
-            # New hip turn data structure with club-aware grading - pass through directly
-            core_metrics[metric_name] = metric_data
-        else:
-            # Handle other metrics with traditional processing
-            value = metric_data.get('value') if isinstance(metric_data, dict) else metric_data
+        # Skip hip turn metric entirely
+        if 'hip_turn_impact' in metric_name:
+            continue
             
-            if 'shoulder_tilt_impact' in metric_name:
-                core_metrics[metric_name] = get_shoulder_tilt_impact_grading(value, 0.9)
-            # Hip turn metric processing removed per user request
-            elif 'hip_sway_top' in metric_name:
-                core_metrics[metric_name] = get_hip_sway_grading(value, 0.8, "top")
-            elif 'wrist_hinge_top' in metric_name:
-                core_metrics[metric_name] = get_wrist_hinge_grading(value, 0.8, "top")
-            else:
-                # Default case
-                core_metrics[metric_name] = {'value': value, 'status': 'n/a'}
+        # Handle other metrics with traditional processing
+        value = metric_data.get('value') if isinstance(metric_data, dict) else metric_data
+        
+        if 'shoulder_tilt_impact' in metric_name:
+            core_metrics[metric_name] = get_shoulder_tilt_impact_grading(value, 0.9)
+        elif 'hip_shoulder_separation_impact' in metric_name:
+            confidence = metric_data.get('confidence', 0.8) if isinstance(metric_data, dict) else 0.8
+            core_metrics[metric_name] = get_hip_shoulder_separation_impact_grading(value, confidence)
+        elif 'hip_sway_top' in metric_name:
+            core_metrics[metric_name] = get_hip_sway_grading(value, 0.8, "top")
+        elif 'wrist_hinge_top' in metric_name:
+            core_metrics[metric_name] = get_wrist_hinge_grading(value, 0.8, "top")
+        else:
+            # Default case
+            core_metrics[metric_name] = {'value': value, 'status': 'n/a'}
     
     return core_metrics
 

app/streamlit_app.py

@@ -381,21 +381,24 @@ def get_head_drop_grading(value, confidence):
     }
 
 
-def get_shoulder_tilt_impact_grading(value, confidence):
-    """Grade shoulder tilt at impact - professional = 39°, 30 handicap = 27°"""
+def get_torso_sidebend_impact_grading(value, confidence):
+    """Grade torso side-bend at impact - professional range ~10-20° (trail-side bend positive)"""
     if value is None:
         return {'display_value': 'n/a', 'badge': '⚪', 'status': 'No data available'}
     
-    # Professional = 39°, 30 handicap = 27°
-    if 35 <= value <= 45:
+    # Use absolute value for grading, but keep sign for display
+    abs_value = abs(value)
+    
+    # Professional range ~10-20°, typical amateur ~6-24°
+    if 10 <= abs_value <= 20:
         badge = '🟢'
-        label = 'Excellent tilt'
-    elif 25 <= value < 35 or 45 < value <= 55:
+        label = 'Excellent side-bend'
+    elif 6 <= abs_value < 10 or 20 < abs_value <= 24:
         badge = '🟠'
-        label = 'Good tilt'
+        label = 'Good side-bend'
     else:
         badge = '🔴'
-        label = 'Needs improvement'
+        label = 'Needs work'
     
     return {
         'display_value': f'{value:.1f}°',
@@ -405,18 +408,19 @@ def get_shoulder_tilt_impact_grading(value, confidence):
     }
 
 
-def get_hip_turn_impact_grading(value, confidence):
-    """Grade hip turn at impact - professional = 36 degrees, 30 handicap = 19 degrees"""
+
+def get_hip_shoulder_separation_impact_grading(value, confidence):
+    """Grade hip-shoulder separation at impact - typical range 10-45 degrees"""
     if value is None:
         return {'display_value': 'n/a', 'badge': '⚪', 'status': 'No data available'}
     
-    # Professional = 36°, 30 handicap = 19°
-    if 30 <= value <= 45:
+    # Professional golfers typically show 20-35° separation, recreational 10-25°
+    if 20 <= value <= 35:
         badge = '🟢'
-        label = 'Excellent turn'
-    elif 20 <= value < 30 or 45 < value <= 55:
+        label = 'Excellent separation'
+    elif 15 <= value < 20 or 35 < value <= 45:
         badge = '🟠'
-        label = 'Good turn'
+        label = 'Good separation'
     else:
         badge = '🔴'
         label = 'Needs improvement'
@@ -428,7 +432,6 @@ def get_hip_turn_impact_grading(value, confidence):
         'confidence': confidence
     }
 
-
 def get_hip_sway_grading(value, confidence, position="top"):
     """Grade hip sway - professional = 3.9" towards target, 30 handicap = 2.5" towards target"""
     if value is None:
@@ -501,28 +504,6 @@ def get_wrist_hinge_grading(value, confidence, position="top"):
 
 
 
-def grade_hip_turn(delta_deg: float, club: str = "iron") -> dict:
-    """Grade hip turn with club-aware bands and actionable tips"""
-    c = club.lower()
-    bands = {
-        "driver": {"excellent": (38,48), "good_low": (32,38), "good_high": (48,52)},
-        "iron":   {"excellent": (32,40), "good_low": (28,32), "good_high": (40,44)},
-        "wedge":  {"excellent": (25,35), "good_low": (22,25), "good_high": (35,38)},
-    }
-    b = bands["driver" if "driver" in c else "wedge" if "wedge" in c else "iron"]
-    x = delta_deg
-
-    if b["excellent"][0] <= x <= b["excellent"][1]:
-        label, color, tip = "🟢 Excellent", "green", "Great rotation with control."
-    elif b["good_low"][0] <= x < b["good_low"][1]:
-        label, color, tip = "🟠 Good (slightly low)", "orange", "Open a touch more through impact."
-    elif b["good_high"][0] <= x <= b["good_high"][1]:
-        label, color, tip = "🟠 Good (slightly high)", "orange", "Post on lead leg; avoid over-spinning hips."
-    else:
-        label, color, tip = "🔴 Needs work", "red", (
-            "Too little: shift then open. Too much: trail heel down longer; post into lead glute."
-        )
-    return {"label": label, "color": color, "tip": tip}
 
 
 def display_new_grading_scheme(core_metrics):
@@ -530,9 +511,8 @@ def display_new_grading_scheme(core_metrics):
     # Check if we have front-facing metrics
     # Front-facing metrics have unique keys that DTL doesn't have
     has_front_facing_metrics = any(key in core_metrics for key in [
-        'shoulder_tilt_impact_deg', 'hip_sway_top_inches', 'wrist_hinge_top_deg'
+        'torso_side_bend_deg', 'shoulder_tilt_impact_deg', 'hip_sway_top_inches', 'wrist_hinge_top_deg', 'hip_shoulder_separation_impact_deg'
     ])
-    # Hip turn check for front-facing metrics
     
     if has_front_facing_metrics:
         st.subheader("Swing Analysis")
@@ -546,7 +526,6 @@ def display_new_grading_scheme(core_metrics):
     knee_flexion_data = core_metrics.get("knee_flexion_deg", {})
     head_drop_data = core_metrics.get("head_drop_top_pct", {})
     hip_depth_data = core_metrics.get("hip_depth_early_extension", {})
-    # Hip turn data for front-facing metrics
     
     # Calculate confidence with QC penalties as per feedback
     def get_confidence(data, metric_type='general'):
@@ -701,21 +680,30 @@ def display_new_grading_scheme(core_metrics):
         # Front-facing metrics are now always calculated
         pass
         
-        # Shoulder Tilt at Impact
-        shoulder_tilt_impact_data = core_metrics.get("shoulder_tilt_impact_deg", {})
-        if shoulder_tilt_impact_data.get('value') is not None:
+        # Torso Side-Bend at Impact (replaces shoulder tilt)
+        torso_sidebend_data = core_metrics.get("torso_side_bend_deg", {})
+        if torso_sidebend_data.get('value') is not None:
             confidence = 0.9  # High confidence for front-facing measurements
-            grading = get_shoulder_tilt_impact_grading(shoulder_tilt_impact_data['value'], confidence)
+            grading = get_torso_sidebend_impact_grading(torso_sidebend_data['value'], confidence)
             if grading:
-                metrics_to_display.append(("Shoulder Tilt @ Impact", grading))
+                metrics_to_display.append(("Torso Side-Bend @ Impact", grading))
+        else:
+            # Fallback to old metric name for compatibility
+            shoulder_tilt_impact_data = core_metrics.get("shoulder_tilt_impact_deg", {})
+            if shoulder_tilt_impact_data.get('value') is not None:
+                confidence = 0.9  # High confidence for front-facing measurements
+                grading = get_torso_sidebend_impact_grading(shoulder_tilt_impact_data['value'], confidence)
+                if grading:
+                    metrics_to_display.append(("Torso Side-Bend @ Impact", grading))
         
-        # Hip Turn at Impact
-        hip_turn_impact_data = core_metrics.get("hip_turn_impact_deg", {})
-        if hip_turn_impact_data.get('value') is not None:
-            confidence = 0.8  # High confidence for front-facing measurements
-            grading = get_hip_turn_impact_grading(hip_turn_impact_data['value'], confidence)
+        
+        # Hip-Shoulder Separation at Impact
+        hip_shoulder_sep_data = core_metrics.get("hip_shoulder_separation_impact_deg", {})
+        if hip_shoulder_sep_data.get('value') is not None:
+            confidence = hip_shoulder_sep_data.get('confidence', 0.8)
+            grading = get_hip_shoulder_separation_impact_grading(hip_shoulder_sep_data['value'], confidence)
             if grading:
-                metrics_to_display.append(("Hip Turn @ Impact", grading))
+                metrics_to_display.append(("Hip-Shoulder Separation @ Impact", grading))
         
         # Hip Sway at Top
         hip_sway_top_data = core_metrics.get("hip_sway_top_inches", {})
@@ -779,8 +767,9 @@ def get_metric_definition(metric_name):
         "Knee Flexion": "Measures knee bend angle at address position.",
         "Head Movement @ Top": "Measures head movement during backswing as percentage of torso length.",
         "Hip Depth / Early Extension": "Tracks loss of hip flexion through impact.",
-        "Hip Turn @ Impact": "Measures hip rotation at ball contact.",
-        "Shoulder Tilt @ Impact": "Measures shoulder angle at ball contact.",
+        "Torso Side-Bend @ Impact": "Measures torso side-bend angle at ball contact.",
+        "Shoulder Tilt @ Impact": "Measures shoulder angle at ball contact.",  # Deprecated
+        "Hip-Shoulder Separation @ Impact": "Measures hip rotation relative to shoulders at ball contact.",
         "Hip Sway @ Top": "Measures lateral hip movement at the top of backswing.",
         "Wrist Hinge @ Top": "Measures wrist hinge angle at the top of backswing."
     }
@@ -833,7 +822,19 @@ def get_metric_evaluation(metric_name, grading):
             return f"Your hip depth of **{value}** indicates early extension issues. This movement pattern reduces power transfer and can cause inconsistent contact. Focus on maintaining spine angle and proper hip position throughout the downswing and impact."
     
     # FRONT-FACING METRICS (4 current metrics)
-    elif metric_name == "Shoulder Tilt @ Impact":
+    elif metric_name == "Torso Side-Bend @ Impact":
+        # Interpret the sign
+        side_description = "trail-side" if float(value.replace('°', '')) > 0 else "lead-side"
+        abs_value = abs(float(value.replace('°', '')))
+        
+        if "🟢" in badge:
+            return f"Your torso side-bend of **{value}** at impact shows excellent position. You're bending **{abs_value:.1f}°** toward the **{side_description}** which indicates ideal impact dynamics and power transfer. This optimal torso angle promotes solid contact, optimal ball flight, and consistent distance control."
+        elif "🟠" in badge:
+            return f"Your torso side-bend of **{value}** at impact is acceptable with room for improvement. You're bending **{abs_value:.1f}°** toward the **{side_description}**. Torso position at impact affects power transfer and ball flight characteristics. Refining your impact position can enhance consistency and distance."
+        else:
+            return f"Your torso side-bend of **{value}** at impact needs attention. You're bending **{abs_value:.1f}°** toward the **{side_description}**. Proper torso angle at impact is crucial for power transfer and ball flight control. Work on impact position for better contact and consistency."
+    
+    elif metric_name == "Shoulder Tilt @ Impact":  # Legacy support
         if "🟢" in badge:
             return f"Your shoulder tilt of **{value}** at impact shows excellent position. This proper shoulder angle indicates ideal impact dynamics and power transfer. Good shoulder tilt at impact promotes solid contact, optimal ball flight, and consistent distance control."
         elif "🟠" in badge:
@@ -841,13 +842,13 @@ def get_metric_evaluation(metric_name, grading):
         else:
             return f"Your shoulder tilt of **{value}** at impact needs attention. Proper shoulder angle at impact is crucial for power transfer and ball flight control. Work on impact position for better contact and consistency."
     
-    elif metric_name == "Hip Turn @ Impact":
+    elif metric_name == "Hip-Shoulder Separation @ Impact":
         if "🟢" in badge:
-            return f"Your hip turn of **{value}** at impact shows excellent rotation. This proper hip movement indicates ideal power transfer and body sequencing. Good hip turn at impact promotes solid contact, optimal ball flight, and consistent distance control."
+            return f"Your hip-shoulder separation of **{value}** at impact shows excellent body sequencing. This proper rotation sequence indicates ideal power transfer with the hips leading the shoulders through impact. Good separation promotes solid contact and optimal ball flight."
         elif "🟠" in badge:
-            return f"Your hip turn of **{value}** at impact is acceptable with room for improvement. Hip rotation at impact affects power transfer and ball flight characteristics. Refining your hip movement can enhance consistency and distance."
+            return f"Your hip-shoulder separation of **{value}** at impact is acceptable with room for improvement. Hip-shoulder sequencing affects power transfer and swing efficiency. Refining your rotation sequence can enhance consistency and distance."
         else:
-            return f"Your hip turn of **{value}** at impact needs attention. Proper hip rotation at impact is crucial for power transfer and ball flight control. Work on hip movement for better contact and consistency."
+            return f"Your hip-shoulder separation of **{value}** at impact needs attention. Proper sequencing with hips leading shoulders is crucial for power transfer and ball flight control. Work on rotation timing for better contact and consistency."
     
     elif metric_name == "Hip Sway @ Top":
         if "🟢" in badge:
@@ -966,14 +967,13 @@ Timing Metrics:
 - Knee Flexion @ Setup: {format_metric_value(core_metrics.get('knee_flexion_deg', {}), '°')}
 - Head Movement @ Top: {format_metric_value(core_metrics.get('head_drop_top_pct', {}), '%')}
 - Hip Depth / Early Extension: {format_metric_value(core_metrics.get('hip_depth_early_extension', {}), '%')}
-# Hip Turn @ Impact metric restored for front-facing analysis
 
 === DTL-LIMITED METRICS (Approximate) ===
 - Shoulder Turn Quality: {format_metric_value(core_metrics.get('shoulder_turn_quality', {}))}
 
 === FRONT-FACING METRICS ===
-- Shoulder Tilt @ Impact: {format_metric_value(core_metrics.get('shoulder_tilt_impact_deg', {}), '°')}
-# Hip Turn @ Impact metric restored for front-facing analysis
+- Torso Side-Bend @ Impact: {format_metric_value(core_metrics.get('torso_side_bend_deg', {}), '°')}
+- Hip-Shoulder Separation @ Impact: {format_metric_value(core_metrics.get('hip_shoulder_separation_impact_deg', {}), '°')}
 - Hip Sway @ Top: {format_metric_value(core_metrics.get('hip_sway_top_inches', {}), '"')}
 - Wrist Hinge @ Top: {format_metric_value(core_metrics.get('wrist_hinge_top_deg', {}), '°')}
 """
@@ -1820,19 +1820,23 @@ def render_step_4():
                     shoulder_swing_plane_status = core_metrics.get("shoulder_tilt_swing_plane_top_deg", {}).get('status', 'n/a')
                     st.caption(f"Shoulder Tilt/Swing Plane @ Top: {shoulder_swing_plane_raw}° ({shoulder_swing_plane_status})")
                     
-                    # Shoulder rotation raw value
-                    shoulder_tilt_raw = core_metrics.get("shoulder_tilt_impact_deg", {}).get('value')
-                    shoulder_tilt_status = core_metrics.get("shoulder_tilt_impact_deg", {}).get('status', 'n/a')
-                    st.caption(f"Shoulder Tilt @ Impact: {shoulder_tilt_raw}° ({shoulder_tilt_status})")
+                    # Torso side-bend raw value  
+                    torso_sidebend_raw = core_metrics.get("torso_side_bend_deg", {}).get('value')
+                    torso_sidebend_status = core_metrics.get("torso_side_bend_deg", {}).get('status', 'n/a')
+                    if torso_sidebend_raw is not None:
+                        st.caption(f"Torso Side-Bend @ Impact: {torso_sidebend_raw}° ({torso_sidebend_status})")
+                    else:
+                        # Fallback to old metric for compatibility
+                        shoulder_tilt_raw = core_metrics.get("shoulder_tilt_impact_deg", {}).get('value')
+                        shoulder_tilt_status = core_metrics.get("shoulder_tilt_impact_deg", {}).get('status', 'n/a')
+                        st.caption(f"Torso Side-Bend @ Impact: {shoulder_tilt_raw}° ({shoulder_tilt_status})")
                     
-                    # Hip turn data for front-facing metrics
                     
                     # Hip depth raw value
                     hip_depth_raw = core_metrics.get("hip_depth_early_extension", {}).get('value')
                     hip_depth_status = core_metrics.get("hip_depth_early_extension", {}).get('status', 'n/a')
                     st.caption(f"Hip Depth / Early Extension: {hip_depth_raw} ({hip_depth_status})")
                     
-                    # Hip turn debug info for front-facing metrics
                     if has_front_facing_metrics:
                         st.caption("Front-facing metrics detected")
                     else: