From e36099a3422921cc09bdfbc4fd2366ee40cde8dc Mon Sep 17 00:00:00 2001 From: Blake Blackshear Date: Sat, 30 Oct 2021 07:24:26 -0500 Subject: [PATCH] improve box merging and keep tracking --- frigate/test/test_reduce_boxes.py | 27 ++++++++++++++ frigate/util.py | 2 +- frigate/video.py | 58 ++++++++++++++----------------- 3 files changed, 54 insertions(+), 33 deletions(-) create mode 100644 frigate/test/test_reduce_boxes.py diff --git a/frigate/test/test_reduce_boxes.py b/frigate/test/test_reduce_boxes.py new file mode 100644 index 000000000..db3803162 --- /dev/null +++ b/frigate/test/test_reduce_boxes.py @@ -0,0 +1,27 @@ +import cv2 +import numpy as np +from unittest import TestCase, main +from frigate.video import box_overlaps, reduce_boxes + + +class TestBoxOverlaps(TestCase): + def test_overlap(self): + assert box_overlaps((100, 100, 200, 200), (50, 50, 150, 150)) + + def test_overlap_2(self): + assert box_overlaps((50, 50, 150, 150), (100, 100, 200, 200)) + + def test_no_overlap(self): + assert not box_overlaps((100, 100, 200, 200), (250, 250, 350, 350)) + + +class TestReduceBoxes(TestCase): + def test_cluster(self): + clusters = reduce_boxes( + [(144, 290, 221, 459), (225, 178, 426, 341), (343, 105, 584, 250)] + ) + assert len(clusters) == 2 + + +if __name__ == "__main__": + main(verbosity=2) diff --git a/frigate/util.py b/frigate/util.py index 24a75b775..36848f0da 100755 --- a/frigate/util.py +++ b/frigate/util.py @@ -191,7 +191,7 @@ def draw_box_with_label( def calculate_region(frame_shape, xmin, ymin, xmax, ymax, multiplier=2): # size is the longest edge and divisible by 4 - size = int(max(xmax - xmin, ymax - ymin) // 4 * 4 * multiplier) + size = int((max(xmax - xmin, ymax - ymin) * multiplier) // 4 * 4) # dont go any smaller than 300 if size < 300: size = 300 diff --git a/frigate/video.py b/frigate/video.py index 3108db4a3..2e46bc590 100755 --- a/frigate/video.py +++ b/frigate/video.py @@ -379,26 +379,37 @@ def track_camera( logger.info(f"{name}: exiting subprocess") +def box_overlaps(b1, b2): + if b1[2] < b2[0] or b1[0] > b2[2] or b1[1] > b2[3] or b1[3] < b2[1]: + return False + return True + + def reduce_boxes(boxes): - if len(boxes) == 0: - return [] - reduced_boxes = cv2.groupRectangles( - [list(b) for b in itertools.chain(boxes, boxes)], 1, 0.2 - )[0] - return [tuple(b) for b in reduced_boxes] + clusters = [] + + for box in boxes: + matched = 0 + for cluster in clusters: + if box_overlaps(box, cluster): + matched = 1 + cluster[0] = min(cluster[0], box[0]) + cluster[1] = min(cluster[1], box[1]) + cluster[2] = max(cluster[2], box[2]) + cluster[3] = max(cluster[3], box[3]) + + if not matched: + clusters.append(list(box)) + + return [tuple(c) for c in clusters] -# modified from https://stackoverflow.com/a/40795835 def intersects_any(box_a, boxes): for box in boxes: - if ( - box_a[2] < box[0] - or box_a[0] > box[2] - or box_a[1] > box[3] - or box_a[3] < box[1] - ): + if box_overlaps(box_a, box): continue return True + return False def detect( @@ -489,9 +500,7 @@ def process_frames( # only get the tracked object boxes that intersect with motion tracked_object_boxes = [ - obj["box"] - for obj in object_tracker.tracked_objects.values() - if intersects_any(obj["box"], motion_boxes) + obj["box"] for obj in object_tracker.tracked_objects.values() ] # combine motion boxes with known locations of existing objects @@ -503,15 +512,6 @@ def process_frames( for a in combined_boxes ] - # combine overlapping regions - combined_regions = reduce_boxes(regions) - - # re-compute regions - regions = [ - calculate_region(frame_shape, a[0], a[1], a[2], a[3], 1.0) - for a in combined_regions - ] - # resize regions and detect detections = [] for region in regions: @@ -582,14 +582,8 @@ def process_frames( if refining: refine_count += 1 - # Limit to the detections overlapping with motion areas - # to avoid picking up stationary background objects - detections_with_motion = [ - d for d in detections if intersects_any(d[2], motion_boxes) - ] - # now that we have refined our detections, we need to track objects - object_tracker.match_and_update(frame_time, detections_with_motion) + object_tracker.match_and_update(frame_time, detections) # add to the queue if not full if detected_objects_queue.full():