Improve 640x640 model detection of small objects (#20190)

* Allow larger models to have smaller regions

* remove unnecessary hailo resize

* Update benchmark

* Fix table

* Update nvidia specs

frigate/detectors/plugins/hailo8l.py

@@ -33,10 +33,6 @@ def preprocess_tensor(image: np.ndarray, model_w: int, model_h: int) -> np.ndarr
         image = image[0]
 
     h, w = image.shape[:2]
-
-    if (w, h) == (320, 320) and (model_w, model_h) == (640, 640):
-        return cv2.resize(image, (model_w, model_h), interpolation=cv2.INTER_LINEAR)
-
     scale = min(model_w / w, model_h / h)
     new_w, new_h = int(w * scale), int(h * scale)
     resized_image = cv2.resize(image, (new_w, new_h), interpolation=cv2.INTER_CUBIC)

frigate/util/object.py

@@ -269,7 +269,20 @@ def is_object_filtered(obj, objects_to_track, object_filters):
 
 def get_min_region_size(model_config: ModelConfig) -> int:
     """Get the min region size."""
-    return max(model_config.height, model_config.width)
+    largest_dimension = max(model_config.height, model_config.width)
+
+    if largest_dimension > 320:
+        # We originally tested allowing any model to have a region down to half of the model size
+        # but this led to many false positives. In this case we specifically target larger models
+        # which can benefit from a smaller region in some cases to detect smaller objects.
+        half = int(largest_dimension / 2)
+
+        if half % 4 == 0:
+            return half
+
+        return int((half + 3) / 4) * 4
+
+    return largest_dimension
 
 
 def create_tensor_input(frame, model_config: ModelConfig, region):