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pass attribute labels as attributes

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This commit is contained in:
Blake Blackshear 2023-06-16 15:32:29 -05:00
parent 0996883a98
commit b466a951e3
2 changed files with 57 additions and 2 deletions
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16
frigate/object_processing.py
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@ -214,6 +214,7 @@ class TrackedObject:
"entered_zones": self.entered_zones.copy(),
"has_clip": self.has_clip,
"has_snapshot": self.has_snapshot,
"attributes": self.obj_data["attributes"],
}
if include_thumbnail:
@ -421,6 +422,21 @@ class CameraState:
color=color,
)
# draw any attributes
for attribute in obj["attributes"]:
box = attribute["box"]
draw_box_with_label(
frame_copy,
box[0],
box[1],
box[2],
box[3],
attribute["label"],
f"{attribute['score']:.0%}",
thickness=thickness,
color=color,
)
if draw_options.get("regions"):
for region in regions:
cv2.rectangle(

43
frigate/video.py
View File

@ -723,6 +723,14 @@ def process_frames(
stop_event,
exit_on_empty: bool = False,
):
# attribute labels are not tracked and are not assigned regions
attribute_label_map = {
"person": ["face", "amazon"],
"car": ["ups", "fedex", "amazon", "license_plate"],
}
all_attribute_labels = [
item for sublist in attribute_label_map.values() for item in sublist
]
fps = process_info["process_fps"]
detection_fps = process_info["detection_fps"]
current_frame_time = process_info["detection_frame"]
@ -758,6 +766,7 @@ def process_frames(
motion_boxes = motion_detector.detect(frame) if motion_enabled.value else []
regions = []
consolidated_detections = []
# if detection is disabled
if not detection_enabled.value:
@ -894,12 +903,42 @@ def process_frames(
consolidated_detections = get_consolidated_object_detections(
detected_object_groups
)
tracked_detections = [
d
for d in consolidated_detections
if d[0] not in all_attribute_labels
]
# now that we have refined our detections, we need to track objects
object_tracker.match_and_update(frame_time, consolidated_detections)
object_tracker.match_and_update(frame_time, tracked_detections)
# else, just update the frame times for the stationary objects
else:
object_tracker.update_frame_times(frame_time)
# group the attribute detections based on what label they apply to
attribute_detections = {}
for label, attribute_labels in attribute_label_map.items():
attribute_detections[label] = [
d for d in consolidated_detections if d[0] in attribute_labels
]
# build detections and add attributes
detections = {}
for obj in object_tracker.tracked_objects.values():
attributes = []
# if the objects label has associated attribute detections
if obj["label"] in attribute_detections.keys():
# add them to attributes if they intersect
for attribute_detection in attribute_detections[obj["label"]]:
if box_inside(obj["box"], (attribute_detection[2])):
attributes.append(
{
"label": attribute_detection[0],
"score": attribute_detection[1],
"box": attribute_detection[2],
}
)
detections[obj["id"]] = {**obj, "attributes": attributes}
# debug object tracking
if False:
bgr_frame = cv2.cvtColor(
@ -982,7 +1021,7 @@ def process_frames(
(
camera_name,
frame_time,
object_tracker.tracked_objects,
detections,
motion_boxes,
regions,
)