predict point postition

Author: arch

funscript_editor/algorithms/opticalflow.py

@@ -100,7 +100,7 @@ def update(self, frame_roi):
                 self.trajectories = new_trajectories
 
 
-            if self.frame_idx % self.feature_detect_interval == 0:
+            if len(self.trajectories) == 0 or self.frame_idx % self.feature_detect_interval == 0:
                 mask = np.zeros_like(frame_gray)
                 mask[:] = 255
                 p = cv2.goodFeaturesToTrack(frame_gray, mask = mask, **self.feature_params)
@@ -225,15 +225,20 @@ def tracking(self) -> str:
 
         signal = Signal(self.video_info.fps)
         points = signal.get_local_min_max_points(result)
+        categorized_points = signal.categorize_points(result, points)
 
-        val = 0
         for k in self.funscripts:
-            for p in points:
+            for bottom_point in categorized_points['max']:
                 self.funscripts[k].add_action(
-                        val,
-                        FFmpegStream.frame_to_millisec(self.get_absolute_framenumber(p * (1+self.params.skip_frames)), self.video_info.fps)
+                        0,
+                        FFmpegStream.frame_to_millisec(self.get_absolute_framenumber(bottom_point * (1+self.params.skip_frames)), self.video_info.fps)
+                    )
+
+            for top_point in categorized_points['min']:
+                self.funscripts[k].add_action(
+                        100,
+                        FFmpegStream.frame_to_millisec(self.get_absolute_framenumber(top_point * (1+self.params.skip_frames)), self.video_info.fps)
                     )
-                val = 0 if val  != 0 else 100
 
         return status
 

funscript_editor/algorithms/signal.py

@@ -485,7 +485,7 @@ def categorize_points(self, signal: list, points: list) -> dict:
             dict: dictionary with grouped points { 'min': [], 'max': [] }
         """
         avg = Signal.moving_average(signal, w=round(self.fps * self.params.avg_sec_for_local_min_max_extraction))
-        smothed_signal = Signal.moving_average(signal, w=3)
+        smothed_signal = Signal.moving_average(signal, w=self.params.local_min_max_filter_len)
 
         grouped_points = {'min': [], 'max': []}
         for idx in points: