Merge branch 'master' of https://github.com/mikel-brostrom/boxmot

boxmot/trackers/basetracker.py

@@ -60,6 +60,20 @@ def update(self, dets: np.ndarray, img: np.ndarray, embs: np.ndarray = None) ->
         """
         raise NotImplementedError("The update method needs to be implemented by the subclass.")
 
+    def check_inputs(self, dets, img):
+        assert isinstance(
+            dets, np.ndarray
+        ), f"Unsupported 'dets' input format '{type(dets)}', valid format is np.ndarray"
+        assert isinstance(
+            img, np.ndarray
+        ), f"Unsupported 'img_numpy' input format '{type(img)}', valid format is np.ndarray"
+        assert (
+            len(dets.shape) == 2
+        ), "Unsupported 'dets' dimensions, valid number of dimensions is two"
+        assert (
+            dets.shape[1] == 6
+        ), "Unsupported 'dets' 2nd dimension lenght, valid lenghts is 6"
+
     def id_to_color(self, id: int, saturation: float = 0.75, value: float = 0.95) -> tuple:
         """
         Generates a consistent unique BGR color for a given ID using hashing.

boxmot/trackers/botsort/bot_sort.py

@@ -234,18 +234,8 @@ def __init__(
 
     @PerClassDecorator
     def update(self, dets: np.ndarray, img: np.ndarray, embs: np.ndarray = None) -> np.ndarray:
-        assert isinstance(
-            dets, np.ndarray
-        ), f"Unsupported 'dets' input format '{type(dets)}', valid format is np.ndarray"
-        assert isinstance(
-            img, np.ndarray
-        ), f"Unsupported 'img_numpy' input format '{type(img)}', valid format is np.ndarray"
-        assert (
-            len(dets.shape) == 2
-        ), "Unsupported 'dets' dimensions, valid number of dimensions is two"
-        assert (
-            dets.shape[1] == 6
-        ), "Unsupported 'dets' 2nd dimension lenght, valid lenghts is 6"
+
+        self.check_inputs(dets, img)
 
         self.frame_count += 1
         activated_starcks = []

boxmot/trackers/bytetrack/byte_tracker.py

@@ -143,15 +143,8 @@ def __init__(
 
     @PerClassDecorator
     def update(self, dets: np.ndarray, img: np.ndarray = None, embs: np.ndarray = None) -> np.ndarray:
-        assert isinstance(
-            dets, np.ndarray
-        ), f"Unsupported 'dets' input format '{type(dets)}', valid format is np.ndarray"
-        assert (
-            len(dets.shape) == 2
-        ), "Unsupported 'dets' dimensions, valid number of dimensions is two"
-        assert (
-            dets.shape[1] == 6
-        ), "Unsupported 'dets' 2nd dimension lenght, valid lenghts is 6"
+
+        self.check_inputs(dets, img)
 
         dets = np.hstack([dets, np.arange(len(dets)).reshape(-1, 1)])
         self.frame_count += 1

boxmot/trackers/deepocsort/deep_ocsort.py

@@ -286,10 +286,7 @@ def update(self, dets: np.ndarray, img: np.ndarray, embs: np.ndarray = None) ->
         """
         #dets, s, c = dets.data
         #print(dets, s, c)
-        assert isinstance(dets, np.ndarray), f"Unsupported 'dets' input type '{type(dets)}', valid format is np.ndarray"
-        assert isinstance(img, np.ndarray), f"Unsupported 'img' input type '{type(img)}', valid format is np.ndarray"
-        assert len(dets.shape) == 2, "Unsupported 'dets' dimensions, valid number of dimensions is two"
-        assert dets.shape[1] == 6, "Unsupported 'dets' 2nd dimension lenght, valid lenghts is 6"
+        self.check_inputs(dets, img)
 
         self.frame_count += 1
         self.height, self.width = img.shape[:2]

boxmot/trackers/hybridsort/hybridsort.py

@@ -386,6 +386,9 @@ def update(self, dets: np.ndarray, img: np.ndarray, embs: np.ndarray = None) ->
         Returns the a similar array, where the last column is the object ID.
         NOTE: The number of objects returned may differ from the number of detections provided.
         """
+
+        self.check_inputs(dets, img)
+
         if dets is None:
             return np.empty((0, 7))
 

boxmot/trackers/imprassoc/impr_assoc_tracker.py

@@ -242,18 +242,7 @@ def __init__(
 
     @PerClassDecorator
     def update(self, dets: np.ndarray, img: np.ndarray, embs: np.ndarray = None) -> np.ndarray:
-        assert isinstance(
-            dets, np.ndarray
-        ), f"Unsupported 'dets' input format '{type(dets)}', valid format is np.ndarray"
-        assert isinstance(
-            img, np.ndarray
-        ), f"Unsupported 'img_numpy' input format '{type(img)}', valid format is np.ndarray"
-        assert (
-            len(dets.shape) == 2
-        ), "Unsupported 'dets' dimensions, valid number of dimensions is two"
-        assert (
-            dets.shape[1] == 6
-        ), "Unsupported 'dets' 2nd dimension lenght, valid lenghts is 6"
+        self.check_inputs(dets, img)
 
         self.frame_count += 1
         activated_starcks = []

boxmot/trackers/ocsort/ocsort.py

@@ -226,15 +226,7 @@ def update(self, dets: np.ndarray, img: np.ndarray, embs: np.ndarray = None) ->
         NOTE: The number of objects returned may differ from the number of detections provided.
         """
 
-        assert isinstance(
-            dets, np.ndarray
-        ), f"Unsupported 'dets' input format '{type(dets)}', valid format is np.ndarray"
-        assert (
-            len(dets.shape) == 2
-        ), "Unsupported 'dets' dimensions, valid number of dimensions is two"
-        assert (
-            dets.shape[1] == 6
-        ), "Unsupported 'dets' 2nd dimension lenght, valid lenghts is 6"
+        self.check_inputs(dets, img)
 
         self.frame_count += 1
         h, w = img.shape[0:2]