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Add object filter ratio (#2952)

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* Add object ratio config parameters

Issue: #2948

* Add config test for object filter ratios

Issue: #2948

* Address review comments

- Accept `ratio` default
- Rename `bounds` to `box` for consistency
- Add migration for new field

Issue: #2948

* Fix logical errors

- field migrations require default values
- `clipped` referenced the wrong index for region, since it shifted
- missed an inclusion of `ratio` for detections in `process_frames`
- revert naming `o[2]` as `box` since it is out of scope!

This has now been test-run against a video, so I believe the kinks are
worked out.

Issue: #2948

* Update contributing notes for `make`

Issue: #2948

* Fix migration

- Ensure that defaults match between Event and migration script
- Deconflict migration script number (from rebase)

Issue: #2948

* Filter objects out of ratio bounds

Issue: #2948

* Update migration file to 009

Issue: #2948
This commit is contained in:
Nick
2022-04-10 09:25:18 -04:00
committed by GitHub
parent 923d07b1a4
commit 045aac8933
13 changed files with 138 additions and 14 deletions
Download Patch File Download Diff File Expand all files Collapse all files

8
frigate/config.py
View File

@@ -210,6 +210,14 @@ class FilterConfig(FrigateBaseModel):
max_area: int = Field(
default=24000000, title="Maximum area of bounding box for object to be counted."
)
min_ratio: float = Field(
default=0,
title="Minimum ratio of bounding box's width/height for object to be counted.",
)
max_ratio: float = Field(
default=24000000,
title="Maximum ratio of bounding box's width/height for object to be counted.",
)
threshold: float = Field(
default=0.7,
title="Average detection confidence threshold for object to be counted.",

2
frigate/events.py
View File

@@ -105,6 +105,7 @@ class EventProcessor(threading.Thread):
region=event_data["region"],
box=event_data["box"],
area=event_data["area"],
ratio=event_data["ratio"],
has_clip=event_data["has_clip"],
has_snapshot=event_data["has_snapshot"],
).where(Event.id == event_data["id"]).execute()
@@ -124,6 +125,7 @@ class EventProcessor(threading.Thread):
region=event_data["region"],
box=event_data["box"],
area=event_data["area"],
ratio=event_data["ratio"],
has_clip=event_data["has_clip"],
has_snapshot=event_data["has_snapshot"],
).where(Event.id == event_data["id"]).execute()

1
frigate/models.py
View File

@@ -20,6 +20,7 @@ class Event(Model):
box = JSONField()
area = IntegerField()
retain_indefinitely = BooleanField(default=False)
ratio = FloatField(default=1.0)
class Recordings(Model):

9
frigate/object_processing.py
View File

@@ -192,6 +192,7 @@ class TrackedObject:
"score": self.obj_data["score"],
"box": self.obj_data["box"],
"area": self.obj_data["area"],
"ratio": self.obj_data["ratio"],
"region": self.obj_data["region"],
"stationary": self.obj_data["motionless_count"]
> self.camera_config.detect.stationary.threshold,
@@ -341,6 +342,14 @@ def zone_filtered(obj: TrackedObject, object_config):
if obj_settings.threshold > obj.computed_score:
return True
# if the object is not proportionally wide enough
if obj_settings.min_ratio > obj.obj_data["ratio"]:
return True
# if the object is proportionally too wide
if obj_settings.max_ratio < obj.obj_data["ratio"]:
return True
return False

3
frigate/objects.py
View File

@@ -150,7 +150,8 @@ class ObjectTracker:
"score": obj[1],
"box": obj[2],
"area": obj[3],
"region": obj[4],
"ratio": obj[4],
"region": obj[5],
"frame_time": frame_time,
}
)

30
frigate/test/test_config.py
View File

@@ -1268,6 +1268,36 @@ class TestConfig(unittest.TestCase):
ValidationError, lambda: frigate_config.runtime_config.cameras
)
def test_object_filter_ratios_work(self):
config = {
"mqtt": {"host": "mqtt"},
"objects": {
"track": ["person", "dog"],
"filters": {"dog": {"min_ratio": 0.2, "max_ratio": 10.1}},
},
"cameras": {
"back": {
"ffmpeg": {
"inputs": [
{"path": "rtsp://10.0.0.1:554/video", "roles": ["detect"]}
]
},
"detect": {
"height": 1080,
"width": 1920,
"fps": 5,
},
}
},
}
frigate_config = FrigateConfig(**config)
assert config == frigate_config.dict(exclude_unset=True)
runtime_config = frigate_config.runtime_config
assert "dog" in runtime_config.cameras["back"].objects.filters
assert runtime_config.cameras["back"].objects.filters["dog"].min_ratio == 0.2
assert runtime_config.cameras["back"].objects.filters["dog"].max_ratio == 10.1
if __name__ == "__main__":
unittest.main(verbosity=2)

2
frigate/util.py
View File

@@ -522,7 +522,7 @@ def clipped(obj, frame_shape):
# if the object is within 5 pixels of the region border, and the region is not on the edge
# consider the object to be clipped
box = obj[2]
region = obj[4]
region = obj[5]
if (
(region[0] > 5 and box[0] - region[0] <= 5)
or (region[1] > 5 and box[1] - region[1] <= 5)

43
frigate/video.py
View File

@@ -38,6 +38,10 @@ logger = logging.getLogger(__name__)
def filtered(obj, objects_to_track, object_filters):
object_name = obj[0]
object_score = obj[1]
object_box = obj[2]
object_area = obj[3]
object_ratio = obj[4]
if not object_name in objects_to_track:
return True
@@ -47,24 +51,35 @@ def filtered(obj, objects_to_track, object_filters):
# if the min area is larger than the
# detected object, don't add it to detected objects
if obj_settings.min_area > obj[3]:
if obj_settings.min_area > object_area:
return True
# if the detected object is larger than the
# max area, don't add it to detected objects
if obj_settings.max_area < obj[3]:
if obj_settings.max_area < object_area:
return True
# if the score is lower than the min_score, skip
if obj_settings.min_score > obj[1]:
if obj_settings.min_score > object_score:
return True
# if the object is not proportionally wide enough
if obj_settings.min_ratio > object_ratio:
return True
# if the object is proportionally too wide
if obj_settings.max_ratio < object_ratio:
return True
if not obj_settings.mask is None:
# compute the coordinates of the object and make sure
# the location isnt outside the bounds of the image (can happen from rounding)
y_location = min(int(obj[2][3]), len(obj_settings.mask) - 1)
# the location isn't outside the bounds of the image (can happen from rounding)
object_xmin = object_box[0]
object_xmax = object_box[2]
object_ymax = object_box[3]
y_location = min(int(object_ymax), len(obj_settings.mask) - 1)
x_location = min(
int((obj[2][2] - obj[2][0]) / 2.0) + obj[2][0],
int((object_xmax + object_xmin) / 2.0),
len(obj_settings.mask[0]) - 1,
)
@@ -429,11 +444,16 @@ def detect(
y_min = int((box[0] * size) + region[1])
x_max = int((box[3] * size) + region[0])
y_max = int((box[2] * size) + region[1])
width = x_max - x_min
height = y_max - y_min
area = width * height
ratio = width / height
det = (
d[0],
d[1],
(x_min, y_min, x_max, y_max),
(x_max - x_min) * (y_max - y_min),
area,
ratio,
region,
)
# apply object filters
@@ -580,6 +600,7 @@ def process_frames(
obj["score"],
obj["box"],
obj["area"],
obj["ratio"],
obj["region"],
)
for obj in object_tracker.tracked_objects.values()
@@ -615,8 +636,14 @@ def process_frames(
for group in detected_object_groups.values():
# apply non-maxima suppression to suppress weak, overlapping bounding boxes
# o[2] is the box of the object: xmin, ymin, xmax, ymax
boxes = [
(o[2][0], o[2][1], o[2][2] - o[2][0], o[2][3] - o[2][1])
(
o[2][0],
o[2][1],
o[2][2] - o[2][0],
o[2][3] - o[2][1],
)
for o in group
]
confidences = [o[1] for o in group]