#758

Committed 04 Sep 2023 08:37PM UTC coverage: 0.0% (-78.3%) from 78.333%

Build # #758

Build Type

push

circle-ci

Committed by

hershd23

Commit Message

Increased underline length in at line 75 in text_summarization.rst
	modified:   docs/source/benchmarks/text_summarization.rst

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/evadb/udfs/trackers/nor_fair.py

# coding=utf-8
# Copyright 2018-2023 EvaDB
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import numpy as np

from evadb.udfs.abstract.tracker_abstract_udf import EvaDBTrackerAbstractUDF
from evadb.utils.generic_utils import try_to_import_norfair
from evadb.utils.math_utils import get_centroid

DISTANCE_THRESHOLD_CENTROID: int = 30


class NorFairTracker(EvaDBTrackerAbstractUDF):
    @property
    def name(self) -> str:
        return "NorFairTracker"

    def setup(self, distance_threshold=DISTANCE_THRESHOLD_CENTROID) -> None:
        # https://github.com/tryolabs/norfair/blob/74b11edde83941dd6e32bcccd5fa849e16bf8564/norfair/tracker.py#L18
        try_to_import_norfair()
        from norfair import Tracker

        self.tracker = Tracker(
            distance_function="euclidean",
            distance_threshold=distance_threshold,
        )
        self.prev_frame_id = None

    def forward(self, frame_id, frame, labels, bboxes, scores):
        from norfair import Detection

        norfair_detections = [
            Detection(
                points=get_centroid(bbox),
                scores=np.array([score]),
                label=hash(label) % 10**8,
                data=(label, bbox, score),
            )
            for (bbox, score, label) in zip(bboxes, scores, labels)
        ]

        # calculate jump between consecutive update calls
        period = frame_id - self.prev_frame_id if self.prev_frame_id else 1
        self.prev_frame_id = frame_id

        # call tracker
        tracked_objects = self.tracker.update(
            detections=norfair_detections, period=period
        )
        bboxes_xyxy = []
        labels = []
        scores = []
        ids = []
        for obj in tracked_objects:
            det = obj.last_detection.data
            labels.append(det[0])
            bboxes_xyxy.append(det[1])
            scores.append(det[2])
            ids.append(obj.id)

        return np.array(ids), np.array(labels), np.array(bboxes_xyxy), np.array(scores)

1	# coding=utf-8
2	# Copyright 2018-2023 EvaDB
3	#
4	# Licensed under the Apache License, Version 2.0 (the "License");
5	# you may not use this file except in compliance with the License.
6	# You may obtain a copy of the License at
7	#
8	# http://www.apache.org/licenses/LICENSE-2.0
9	#
10	# Unless required by applicable law or agreed to in writing, software
11	# distributed under the License is distributed on an "AS IS" BASIS,
12	# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13	# See the License for the specific language governing permissions and
14	# limitations under the License.
15	import numpy as np	×
16
17	from evadb.udfs.abstract.tracker_abstract_udf import EvaDBTrackerAbstractUDF	×
18	from evadb.utils.generic_utils import try_to_import_norfair	×
19	from evadb.utils.math_utils import get_centroid	×
20
21	DISTANCE_THRESHOLD_CENTROID: int = 30	×
22
23
24	class NorFairTracker(EvaDBTrackerAbstractUDF):	×
25	@property	×
26	def name(self) -> str:	×
27	return "NorFairTracker"	×
28
29	def setup(self, distance_threshold=DISTANCE_THRESHOLD_CENTROID) -> None:	×
30	# https://github.com/tryolabs/norfair/blob/74b11edde83941dd6e32bcccd5fa849e16bf8564/norfair/tracker.py#L18
31	try_to_import_norfair()	×
32	from norfair import Tracker	×
33
34	self.tracker = Tracker(	×
35	distance_function="euclidean",
36	distance_threshold=distance_threshold,
37	)
38	self.prev_frame_id = None	×
39
40	def forward(self, frame_id, frame, labels, bboxes, scores):	×
41	from norfair import Detection	×
42
43	norfair_detections = [	×
44	Detection(
45	points=get_centroid(bbox),
46	scores=np.array([score]),
47	label=hash(label) % 10**8,
48	data=(label, bbox, score),
49	)
50	for (bbox, score, label) in zip(bboxes, scores, labels)
51	]
52
53	# calculate jump between consecutive update calls
54	period = frame_id - self.prev_frame_id if self.prev_frame_id else 1	×
55	self.prev_frame_id = frame_id	×
56
57	# call tracker
58	tracked_objects = self.tracker.update(	×
59	detections=norfair_detections, period=period
60	)
61	bboxes_xyxy = []	×
62	labels = []	×
63	scores = []	×
64	ids = []	×
65	for obj in tracked_objects:	×
66	det = obj.last_detection.data	×
67	labels.append(det[0])	×
68	bboxes_xyxy.append(det[1])	×
69	scores.append(det[2])	×
70	ids.append(obj.id)	×
71
72	return np.array(ids), np.array(labels), np.array(bboxes_xyxy), np.array(scores)	×

georgia-tech-db / eva / #758

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