Nms
non_max_suppression_fast(boxes, overlapThresh)
¶
Applies non-maximum suppression to bounding boxes.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
boxes
|
ndarray
|
Array of bounding boxes with confidence scores. |
required |
overlapThresh
|
float
|
Overlap threshold for suppression. |
required |
Returns:
Name | Type | Description |
---|---|---|
list |
List of bounding boxes after non-maximum suppression. |
Source code in inference/core/nms.py
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|
w_np_non_max_suppression(prediction, conf_thresh=0.25, iou_thresh=0.45, class_agnostic=False, max_detections=300, max_candidate_detections=3000, timeout_seconds=None, num_masks=0, box_format='xywh')
¶
Applies non-maximum suppression to predictions.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
prediction
|
ndarray
|
Array of predictions. Format for single prediction is [bbox x 4, max_class_confidence, (confidence) x num_of_classes, additional_element x num_masks] |
required |
conf_thresh
|
float
|
Confidence threshold. Defaults to 0.25. |
0.25
|
iou_thresh
|
float
|
IOU threshold. Defaults to 0.45. |
0.45
|
class_agnostic
|
bool
|
Whether to ignore class labels. Defaults to False. |
False
|
max_detections
|
int
|
Maximum number of detections. Defaults to 300. |
300
|
max_candidate_detections
|
int
|
Maximum number of candidate detections. Defaults to 3000. |
3000
|
timeout_seconds
|
Optional[int]
|
Timeout in seconds. Defaults to None. |
None
|
num_masks
|
int
|
Number of masks. Defaults to 0. |
0
|
box_format
|
str
|
Format of bounding boxes. Either 'xywh' or 'xyxy'. Defaults to 'xywh'. |
'xywh'
|
Returns:
Name | Type | Description |
---|---|---|
list |
List of filtered predictions after non-maximum suppression. Format of a single result is: [bbox x 4, max_class_confidence, max_class_confidence, id_of_class_with_max_confidence, additional_element x num_masks] |
Source code in inference/core/nms.py
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