Confidence Level Slider

app.py

@@ -1,5 +1,5 @@
 # ============================================================
-# 🚦 Stage 3 — Wrong Direction Detection (Stable + Confidence + Hysteresis)
+# 🚦 Stage 3 — Wrong Direction Detection (Stable + Confidence + Hysteresis + Filter)
 # ============================================================
 
 import os, cv2, json, tempfile, numpy as np, gradio as gr
@@ -34,7 +34,7 @@ class Track:
         self.status = "OK"
         self.status_history = []
         self.confidence = 1.0
-        self.ema_sim = 1.0  # for exponential smoothing
+        self.ema_sim = 1.0
 
     def update(self, bbox):
         self.kf.predict()
@@ -78,7 +78,7 @@ def smooth_direction(points, window=5):
 # ============================================================
 # 🧭 Wrong-Direction Detection Core
 # ============================================================
-def process_video(video_file, stage2_json, show_only_wrong=False):
+def process_video(video_file, stage2_json, show_only_wrong=False, conf_threshold=0.0):
     data = json.load(open(stage2_json))
     lane_flows = np.array(data.get("flow_centers", [[1,0]]))
     drive_zone = np.array(data.get("drive_zone", []))
@@ -91,7 +91,6 @@ def process_video(video_file, stage2_json, show_only_wrong=False):
     out = cv2.VideoWriter(out_path, cv2.VideoWriter_fourcc(*'mp4v'), fps, (w, h))
 
     tracks, next_id = {}, 0
-    SIM_THRESH = 0.5          # base reference
     DELAY_FRAMES = 8
     MIN_FLOW_SPEED = 1.2
     HYST_OK = 0.55
@@ -160,7 +159,14 @@ def process_video(video_file, stage2_json, show_only_wrong=False):
 
                 trk.stable_status(new_status, new_conf=trk.ema_sim, window=10, agree_ratio=0.6)
 
-                if (not show_only_wrong) or (trk.status == "WRONG"):
+                # --- Filter by UI controls ---
+                show_label = True
+                if trk.confidence < conf_threshold:
+                    show_label = False
+                if show_only_wrong and trk.status != "WRONG":
+                    show_label = False
+
+                if show_label:
                     color = (0, 0, 255) if trk.status == "WRONG" else (0, 255, 0)
                     label = f"ID:{tid} {trk.status} ({trk.confidence:.2f})"
                     cv2.putText(frame, label, tuple(np.int32(pos)),
@@ -176,12 +182,12 @@ def process_video(video_file, stage2_json, show_only_wrong=False):
 # 🎛️ Gradio Interface
 # ============================================================
 description = """
-### 🚦 Stage 3 — Wrong Direction Detection (Stable + Confidence + Hysteresis)
+### 🚦 Stage 3 — Wrong Direction Detection (Stable + Confidence + Filter)
 - ✅ Cosine similarity with exponential smoothing  
 - ✅ Hysteresis (OK≥0.55 / WRONG≤0.45) for stability  
 - ✅ 10-frame consensus voting (flicker-free)  
-- ✅ Confidence score beside each ID  
-- ✅ Optional “Show Only Wrong Labels” toggle
+- ✅ Confidence-based label filtering  
+- ✅ “Show Only Wrong” toggle
 """
 
 demo = gr.Interface(
@@ -189,10 +195,11 @@ demo = gr.Interface(
     inputs=[
         gr.File(label="Input Video"),
         gr.File(label="Stage 2 Flow JSON"),
-        gr.Checkbox(label="Show ONLY Wrong Labels Overlay", value=False)
+        gr.Checkbox(label="Show ONLY Wrong Labels Overlay", value=False),
+        gr.Slider(0.0, 1.0, value=0.0, step=0.05, label="Confidence Level Filter (Show ≥ this value)")
     ],
     outputs=gr.Video(label="Output Video"),
-    title="🚗 Stage 3 – Stable Wrong-Direction Detection (with Confidence)",
+    title="🚗 Stage 3 – Stable Wrong-Direction Detection (with Confidence Filter)",
     description=description
 )