From 17aa78da2a395ca17099c23b03b796a3be9928f2 Mon Sep 17 00:00:00 2001
From: raccoonliukai <903896015@qq.com>
Date: Fri, 27 Sep 2019 17:18:00 +0800
Subject: [PATCH] fix(shotdetect): fix bug with thre_algo after histcmp

---
 gnes/preprocessor/helper.py           | 7 ++++---
 gnes/preprocessor/video/shotdetect.py | 3 ++-
 2 files changed, 6 insertions(+), 4 deletions(-)

diff --git a/gnes/preprocessor/helper.py b/gnes/preprocessor/helper.py
index 373d3ac7..71cbf1d8 100644
--- a/gnes/preprocessor/helper.py
+++ b/gnes/preprocessor/helper.py
@@ -354,20 +354,21 @@ def motion_algo(distances: List[float], **kwargs) -> List[int]:
         'motion_step': 15
     }
     arg_dict.update(kwargs)
+    neigh_avg = kwargs.get('neigh_avg', 2)
 
     shots = []
-    num_frames = len(distances) + 2 * 2 + 1
+    num_frames = len(distances) + 2 * neigh_avg + 1
     p = peakutils.indexes(np.array(distances).astype('float32'), thres=arg_dict['threshold'], min_dist=arg_dict['min_dist']) if len(distances) else []
     if len(p) == 0:
         return [0, num_frames]
 
     shots.append(0)
-    shots.append(p[0] + 2 + 1)
+    shots.append(p[0] + neigh_avg + 1)
     for i in range(1, len(p)):
         # We check that the peak is not due to a motion in the image
         valid_dist = not arg_dict['motion_step'] or not check_motion(distances[p[i]-arg_dict['motion_step']:p[i]], distances[p[i]])
         if valid_dist:
-            shots.append(p[i] + 2 + 1)
+            shots.append(p[i] + neigh_avg + 1)
     if shots[-1] < num_frames - arg_dict['min_dist']:
         shots.append(num_frames)
     elif shots[-1] > num_frames:
diff --git a/gnes/preprocessor/video/shotdetect.py b/gnes/preprocessor/video/shotdetect.py
index 1fd6bec4..1da422f4 100644
--- a/gnes/preprocessor/video/shotdetect.py
+++ b/gnes/preprocessor/video/shotdetect.py
@@ -63,8 +63,9 @@ def detect_shots(self, frames: 'np.ndarray') -> List[List['np.ndarray']]:
                 compare_descriptor(pair[0], pair[1], self.distance_metric)
                 for pair in zip(descriptors[:-1], descriptors[1:])
             ]
+            self._detector_kwargs['neigh_avg'] = 0
 
-        shot_bounds = detect_peak_boundary(dists, self.detect_method)
+        shot_bounds = detect_peak_boundary(dists, self.detect_method, **self._detector_kwargs)
 
         shots = []
         for ci in range(0, len(shot_bounds) - 1):