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https://github.com/blakeblackshear/frigate.git
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2fb7200fb7
* Separate object reduction to own function and reduce confidence of boxes on edge of region * Add tests for different scenarios * Formatting
317 lines
9.4 KiB
Python
317 lines
9.4 KiB
Python
import unittest
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import cv2
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import numpy as np
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from norfair.drawing.color import Palette
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from norfair.drawing.drawer import Drawer
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from frigate.util.image import intersection
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from frigate.util.object import (
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get_cluster_boundary,
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get_cluster_candidates,
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get_cluster_region,
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get_region_from_grid,
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reduce_detections,
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)
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def draw_box(frame, box, color=(255, 0, 0), thickness=2):
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cv2.rectangle(
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frame,
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(box[0], box[1]),
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(box[2], box[3]),
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color,
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thickness,
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)
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def save_clusters_image(name, boxes, candidates, regions=[]):
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canvas = np.zeros((1000, 2000, 3), np.uint8)
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for cluster in candidates:
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color = Palette.choose_color(np.random.rand())
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for b in cluster:
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box = boxes[b]
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draw_box(canvas, box, color, 2)
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# bottom right
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text_anchor = (
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box[2],
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box[3],
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)
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canvas = Drawer.text(
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canvas,
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str(b),
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position=text_anchor,
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size=None,
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color=(255, 255, 255),
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thickness=None,
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)
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for r in regions:
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draw_box(canvas, r, (0, 255, 0), 2)
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cv2.imwrite(
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f"debug/frames/{name}.jpg",
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canvas,
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)
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def save_cluster_boundary_image(name, boxes, bounding_boxes):
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canvas = np.zeros((1000, 2000, 3), np.uint8)
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color = Palette.choose_color(np.random.rand())
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for box in boxes:
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draw_box(canvas, box, color, 2)
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for bound in bounding_boxes:
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draw_box(canvas, bound, (0, 255, 0), 2)
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cv2.imwrite(
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f"debug/frames/{name}.jpg",
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canvas,
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)
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class TestRegion(unittest.TestCase):
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def setUp(self):
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self.frame_shape = (1000, 2000)
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self.min_region_size = 160
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def test_cluster_candidates(self):
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boxes = [(100, 100, 200, 200), (202, 150, 252, 200), (900, 900, 950, 950)]
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cluster_candidates = get_cluster_candidates(
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self.frame_shape, self.min_region_size, boxes
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)
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# save_clusters_image("cluster_candidates", boxes, cluster_candidates)
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assert len(cluster_candidates) == 2
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def test_cluster_boundary(self):
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boxes = [(100, 100, 200, 200), (215, 215, 325, 325)]
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boundary_boxes = [
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get_cluster_boundary(box, self.min_region_size) for box in boxes
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]
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# save_cluster_boundary_image("bound", boxes, boundary_boxes)
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assert len(boundary_boxes) == 2
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def test_cluster_regions(self):
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boxes = [(100, 100, 200, 200), (202, 150, 252, 200), (900, 900, 950, 950)]
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cluster_candidates = get_cluster_candidates(
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self.frame_shape, self.min_region_size, boxes
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)
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regions = [
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get_cluster_region(self.frame_shape, self.min_region_size, candidate, boxes)
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for candidate in cluster_candidates
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]
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# save_clusters_image("regions", boxes, cluster_candidates, regions)
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assert len(regions) == 2
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def test_box_too_small_for_cluster(self):
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boxes = [(100, 100, 600, 600), (655, 100, 700, 145)]
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cluster_candidates = get_cluster_candidates(
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self.frame_shape, self.min_region_size, boxes
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)
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regions = [
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get_cluster_region(self.frame_shape, self.min_region_size, candidate, boxes)
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for candidate in cluster_candidates
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]
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save_clusters_image("too_small", boxes, cluster_candidates, regions)
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assert len(cluster_candidates) == 2
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assert len(regions) == 2
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def test_redundant_clusters(self):
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boxes = [(100, 100, 200, 200), (305, 305, 415, 415)]
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cluster_candidates = get_cluster_candidates(
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self.frame_shape, self.min_region_size, boxes
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)
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regions = [
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get_cluster_region(self.frame_shape, self.min_region_size, candidate, boxes)
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for candidate in cluster_candidates
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]
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# save_clusters_image("redundant", boxes, cluster_candidates, regions)
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assert len(cluster_candidates) == 2
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assert all([len(c) == 1 for c in cluster_candidates])
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assert len(regions) == 2
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def test_combine_boxes(self):
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boxes = [
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(460, 0, 561, 144),
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(565, 0, 586, 71),
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]
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# boundary_boxes = [get_cluster_boundary(box) for box in boxes]
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# save_cluster_boundary_image("combine_bound", boxes, boundary_boxes)
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cluster_candidates = get_cluster_candidates(
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self.frame_shape, self.min_region_size, boxes
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)
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regions = [
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get_cluster_region(self.frame_shape, self.min_region_size, candidate, boxes)
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for candidate in cluster_candidates
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]
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# save_clusters_image("combine", boxes, cluster_candidates, regions)
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assert len(regions) == 1
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def test_dont_combine_boxes(self):
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boxes = [(460, 0, 532, 129), (586, 0, 606, 46)]
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# boundary_boxes = [get_cluster_boundary(box) for box in boxes]
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# save_cluster_boundary_image("dont_combine_bound", boxes, boundary_boxes)
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cluster_candidates = get_cluster_candidates(
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self.frame_shape, self.min_region_size, boxes
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)
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regions = [
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get_cluster_region(self.frame_shape, self.min_region_size, candidate, boxes)
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for candidate in cluster_candidates
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]
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# save_clusters_image("dont_combine", boxes, cluster_candidates, regions)
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assert len(regions) == 2
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class TestObjectBoundingBoxes(unittest.TestCase):
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def setUp(self) -> None:
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pass
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def test_box_intersection(self):
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box_a = [2012, 191, 2031, 205]
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box_b = [887, 92, 985, 151]
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box_c = [899, 128, 1080, 175]
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assert intersection(box_a, box_b) == None
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assert intersection(box_b, box_c) == (899, 128, 985, 151)
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def test_overlapping_objects_reduced(self):
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"""Test that object not on edge of region is used when a higher scoring object at the edge of region is provided."""
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detections = [
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(
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"car",
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0.81,
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(1209, 73, 1437, 163),
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20520,
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2.53333333,
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(1150, 0, 1500, 200),
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),
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(
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"car",
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0.88,
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(1238, 73, 1401, 171),
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15974,
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1.663265306122449,
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(1242, 0, 1602, 360),
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),
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]
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frame_shape = (720, 2560)
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consolidated_detections = reduce_detections(frame_shape, detections)
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assert consolidated_detections == [
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(
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"car",
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0.81,
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(1209, 73, 1437, 163),
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20520,
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2.53333333,
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(1150, 0, 1500, 200),
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)
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]
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def test_non_overlapping_objects_not_reduced(self):
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"""Test that non overlapping objects are not reduced."""
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detections = [
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(
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"car",
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0.81,
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(1209, 73, 1437, 163),
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20520,
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2.53333333,
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(1150, 0, 1500, 200),
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),
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(
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"car",
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0.83203125,
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(1121, 55, 1214, 100),
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4185,
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2.066666666666667,
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(922, 0, 1242, 320),
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),
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(
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"car",
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0.85546875,
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(1414, 97, 1571, 186),
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13973,
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1.7640449438202248,
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(1248, 0, 1568, 320),
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),
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]
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frame_shape = (720, 2560)
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consolidated_detections = reduce_detections(frame_shape, detections)
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assert len(consolidated_detections) == len(detections)
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def test_overlapping_different_size_objects_not_reduced(self):
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"""Test that overlapping objects that are significantly different in size are not reduced."""
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detections = [
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(
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"car",
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0.81,
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(164, 279, 816, 719),
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286880,
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1.48,
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(90, 0, 910, 820),
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),
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(
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"car",
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0.83203125,
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(248, 340, 328, 385),
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3600,
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1.777,
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(0, 0, 460, 460),
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),
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]
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frame_shape = (720, 2560)
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consolidated_detections = reduce_detections(frame_shape, detections)
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assert len(consolidated_detections) == len(detections)
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class TestRegionGrid(unittest.TestCase):
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def setUp(self) -> None:
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pass
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def test_region_in_range(self):
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"""Test that region is kept at minimal size when within std dev."""
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frame_shape = (720, 1280)
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box = [450, 450, 550, 550]
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region_grid = [
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[],
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[],
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[],
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[{}, {}, {}, {}, {}, {"sizes": [0.25], "mean": 0.26, "std_dev": 0.01}],
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]
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region = get_region_from_grid(frame_shape, box, 320, region_grid)
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assert region[2] - region[0] == 320
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def test_region_out_of_range(self):
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"""Test that region is upsized when outside of std dev."""
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frame_shape = (720, 1280)
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box = [450, 450, 550, 550]
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region_grid = [
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[],
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[],
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[],
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[{}, {}, {}, {}, {}, {"sizes": [0.5], "mean": 0.5, "std_dev": 0.1}],
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]
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region = get_region_from_grid(frame_shape, box, 320, region_grid)
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assert region[2] - region[0] > 320
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