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dedupe detected objects

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This commit is contained in:
Blake Blackshear 2020-01-02 06:32:02 -06:00
parent 9cc46a71cb
commit 5b4c6e50bc
3 changed files with 24 additions and 30 deletions
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2
frigate/object_detection.py
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@ -31,7 +31,7 @@ class PreppedQueueProcessor(threading.Thread):
frame = self.prepped_frame_queue.get()
# Actual detection.
frame['detected_objects'] = self.engine.DetectWithInputTensor(frame['frame'], threshold=0.4, top_k=5)
frame['detected_objects'] = self.engine.DetectWithInputTensor(frame['frame'], threshold=0.2, top_k=5)
self.fps.update()
self.avg_inference_speed = (self.avg_inference_speed*9 + self.engine.get_inference_time())/10

50
frigate/objects.py
View File

@ -122,33 +122,15 @@ class DetectedObjectsProcessor(threading.Thread):
# if self.camera.mask[y_location][x_location] == [0]:
# continue
# see if the current object is a duplicate
# TODO: still need to decide which copy to keep
obj['duplicate'] = False
for existing_obj in self.camera.detected_objects[frame['frame_time']]:
# compute intersection rectangle with existing object and new objects region
existing_obj_current_region = compute_intersection_rectangle(existing_obj['box'], obj['region'])
# compute intersection rectangle with new object and existing objects region
new_obj_existing_region = compute_intersection_rectangle(obj['box'], existing_obj['region'])
# compute iou for the two intersection rectangles that were just computed
iou = compute_intersection_over_union(existing_obj_current_region, new_obj_existing_region)
# if intersection is greater than ?, flag as duplicate
if iou > .7:
obj['duplicate'] = True
break
self.camera.detected_objects[frame['frame_time']].append(obj)
with self.camera.regions_in_process_lock:
self.camera.regions_in_process[frame['frame_time']] -= 1
# print(f"Remaining regions for {frame['frame_time']}: {self.camera.regions_in_process[frame['frame_time']]}")
# print(f"{frame['frame_time']} remaining regions {self.camera.regions_in_process[frame['frame_time']]}")
if self.camera.regions_in_process[frame['frame_time']] == 0:
del self.camera.regions_in_process[frame['frame_time']]
# print('Finished frame: ', frame['frame_time'])
# print(f"{frame['frame_time']} no remaining regions")
self.camera.finished_frame_queue.put(frame['frame_time'])
with self.camera.objects_parsed:
@ -183,9 +165,8 @@ class RegionRefiner(threading.Thread):
# just keep the unclipped objects
self.camera.detected_objects[frame_time] = [obj for obj in self.camera.detected_objects[frame_time] if obj['clipped'] == False]
# print(f"{frame_time} found {len(object_groups)} groups {object_groups}")
# print(f"{frame_time} found {len(object_groups)} groups")
clipped_object = False
# deduped_objects = []
# find the largest unclipped object in each group
for group in object_groups:
unclipped_objects = [obj for obj in group if obj['clipped'] == False]
@ -219,23 +200,36 @@ class RegionRefiner(threading.Thread):
self.camera.dynamic_region_fps.update()
clipped_object = True
# add the largest unclipped object
# TODO: this makes no sense
# deduped_objects.append(max(unclipped_objects, key=lambda obj: obj['area']))
# if we found a clipped object, then this frame is not ready for processing
if clipped_object:
continue
# dedupe the unclipped objects
deduped_objects = []
for obj in self.camera.detected_objects[frame_time]:
duplicate = None
for index, deduped_obj in enumerate(deduped_objects):
# if the IOU is more than 0.7, consider it a duplicate
if self.has_overlap(obj, deduped_obj, .5):
duplicate = index
break
# get the higher scoring object
if duplicate is None:
deduped_objects.append(obj)
else:
if deduped_objects[duplicate]['score'] < obj['score']:
deduped_objects[duplicate] = obj
self.camera.detected_objects[frame_time] = deduped_objects
# print(f"{frame_time} is actually finished")
# self.camera.detected_objects[frame_time] = deduped_objects
# keep adding frames to the refined queue as long as they are finished
with self.camera.regions_in_process_lock:
while self.camera.frame_queue.qsize() > 0 and self.camera.frame_queue.queue[0] not in self.camera.regions_in_process:
self.camera.refined_frame_queue.put(self.camera.frame_queue.get())
def has_overlap(self, new_obj, obj, overlap=0):
def has_overlap(self, new_obj, obj, overlap=.7):
# compute intersection rectangle with existing object and new objects region
existing_obj_current_region = compute_intersection_rectangle(obj['box'], new_obj['region'])

2
frigate/util.py
View File

@ -17,7 +17,7 @@ def ReadLabelFile(file_path):
def calculate_region(frame_shape, xmin, ymin, xmax, ymax):
# size is larger than longest edge
size = int(max(xmax-xmin, ymax-ymin)*1.5)
size = int(max(xmax-xmin, ymax-ymin)*2)
# if the size is too big to fit in the frame
if size > min(frame_shape[0], frame_shape[1]):
size = min(frame_shape[0], frame_shape[1])