mirror of
https://github.com/blakeblackshear/frigate.git
synced 2024-11-21 19:07:46 +01:00
331 lines
10 KiB
Python
331 lines
10 KiB
Python
import unittest
|
|
|
|
import cv2
|
|
import numpy as np
|
|
from norfair.drawing.color import Palette
|
|
from norfair.drawing.drawer import Drawer
|
|
|
|
from frigate.util.image import intersection, transliterate_to_latin
|
|
from frigate.util.object import (
|
|
get_cluster_boundary,
|
|
get_cluster_candidates,
|
|
get_cluster_region,
|
|
get_region_from_grid,
|
|
reduce_detections,
|
|
)
|
|
|
|
|
|
def draw_box(frame, box, color=(255, 0, 0), thickness=2):
|
|
cv2.rectangle(
|
|
frame,
|
|
(box[0], box[1]),
|
|
(box[2], box[3]),
|
|
color,
|
|
thickness,
|
|
)
|
|
|
|
|
|
def save_clusters_image(name, boxes, candidates, regions=[]):
|
|
canvas = np.zeros((1000, 2000, 3), np.uint8)
|
|
for cluster in candidates:
|
|
color = Palette.choose_color(np.random.rand())
|
|
for b in cluster:
|
|
box = boxes[b]
|
|
draw_box(canvas, box, color, 2)
|
|
# bottom right
|
|
text_anchor = (
|
|
box[2],
|
|
box[3],
|
|
)
|
|
canvas = Drawer.text(
|
|
canvas,
|
|
str(b),
|
|
position=text_anchor,
|
|
size=None,
|
|
color=(255, 255, 255),
|
|
thickness=None,
|
|
)
|
|
for r in regions:
|
|
draw_box(canvas, r, (0, 255, 0), 2)
|
|
cv2.imwrite(
|
|
f"debug/frames/{name}.jpg",
|
|
canvas,
|
|
)
|
|
|
|
|
|
def save_cluster_boundary_image(name, boxes, bounding_boxes):
|
|
canvas = np.zeros((1000, 2000, 3), np.uint8)
|
|
color = Palette.choose_color(np.random.rand())
|
|
for box in boxes:
|
|
draw_box(canvas, box, color, 2)
|
|
for bound in bounding_boxes:
|
|
draw_box(canvas, bound, (0, 255, 0), 2)
|
|
cv2.imwrite(
|
|
f"debug/frames/{name}.jpg",
|
|
canvas,
|
|
)
|
|
|
|
|
|
class TestRegion(unittest.TestCase):
|
|
def setUp(self):
|
|
self.frame_shape = (1000, 2000)
|
|
self.min_region_size = 160
|
|
|
|
def test_cluster_candidates(self):
|
|
boxes = [(100, 100, 200, 200), (202, 150, 252, 200), (900, 900, 950, 950)]
|
|
|
|
cluster_candidates = get_cluster_candidates(
|
|
self.frame_shape, self.min_region_size, boxes
|
|
)
|
|
|
|
# save_clusters_image("cluster_candidates", boxes, cluster_candidates)
|
|
|
|
assert len(cluster_candidates) == 2
|
|
|
|
def test_transliterate_to_latin(self):
|
|
self.assertEqual(transliterate_to_latin("frégate"), "fregate")
|
|
self.assertEqual(transliterate_to_latin("utilité"), "utilite")
|
|
self.assertEqual(transliterate_to_latin("imágé"), "image")
|
|
|
|
def test_cluster_boundary(self):
|
|
boxes = [(100, 100, 200, 200), (215, 215, 325, 325)]
|
|
boundary_boxes = [
|
|
get_cluster_boundary(box, self.min_region_size) for box in boxes
|
|
]
|
|
|
|
# save_cluster_boundary_image("bound", boxes, boundary_boxes)
|
|
assert len(boundary_boxes) == 2
|
|
|
|
def test_cluster_regions(self):
|
|
boxes = [(100, 100, 200, 200), (202, 150, 252, 200), (900, 900, 950, 950)]
|
|
|
|
cluster_candidates = get_cluster_candidates(
|
|
self.frame_shape, self.min_region_size, boxes
|
|
)
|
|
|
|
regions = [
|
|
get_cluster_region(self.frame_shape, self.min_region_size, candidate, boxes)
|
|
for candidate in cluster_candidates
|
|
]
|
|
|
|
# save_clusters_image("regions", boxes, cluster_candidates, regions)
|
|
assert len(regions) == 2
|
|
|
|
def test_box_too_small_for_cluster(self):
|
|
boxes = [(100, 100, 600, 600), (655, 100, 700, 145)]
|
|
|
|
cluster_candidates = get_cluster_candidates(
|
|
self.frame_shape, self.min_region_size, boxes
|
|
)
|
|
|
|
regions = [
|
|
get_cluster_region(self.frame_shape, self.min_region_size, candidate, boxes)
|
|
for candidate in cluster_candidates
|
|
]
|
|
|
|
save_clusters_image("too_small", boxes, cluster_candidates, regions)
|
|
|
|
assert len(cluster_candidates) == 2
|
|
assert len(regions) == 2
|
|
|
|
def test_redundant_clusters(self):
|
|
boxes = [(100, 100, 200, 200), (305, 305, 415, 415)]
|
|
|
|
cluster_candidates = get_cluster_candidates(
|
|
self.frame_shape, self.min_region_size, boxes
|
|
)
|
|
|
|
regions = [
|
|
get_cluster_region(self.frame_shape, self.min_region_size, candidate, boxes)
|
|
for candidate in cluster_candidates
|
|
]
|
|
|
|
# save_clusters_image("redundant", boxes, cluster_candidates, regions)
|
|
|
|
assert len(cluster_candidates) == 2
|
|
assert all([len(c) == 1 for c in cluster_candidates])
|
|
assert len(regions) == 2
|
|
|
|
def test_combine_boxes(self):
|
|
boxes = [
|
|
(460, 0, 561, 144),
|
|
(565, 0, 586, 71),
|
|
]
|
|
|
|
# boundary_boxes = [get_cluster_boundary(box) for box in boxes]
|
|
# save_cluster_boundary_image("combine_bound", boxes, boundary_boxes)
|
|
|
|
cluster_candidates = get_cluster_candidates(
|
|
self.frame_shape, self.min_region_size, boxes
|
|
)
|
|
|
|
regions = [
|
|
get_cluster_region(self.frame_shape, self.min_region_size, candidate, boxes)
|
|
for candidate in cluster_candidates
|
|
]
|
|
|
|
# save_clusters_image("combine", boxes, cluster_candidates, regions)
|
|
assert len(regions) == 1
|
|
|
|
def test_dont_combine_boxes(self):
|
|
boxes = [(460, 0, 532, 129), (586, 0, 606, 46)]
|
|
|
|
# boundary_boxes = [get_cluster_boundary(box) for box in boxes]
|
|
# save_cluster_boundary_image("dont_combine_bound", boxes, boundary_boxes)
|
|
|
|
cluster_candidates = get_cluster_candidates(
|
|
self.frame_shape, self.min_region_size, boxes
|
|
)
|
|
|
|
regions = [
|
|
get_cluster_region(self.frame_shape, self.min_region_size, candidate, boxes)
|
|
for candidate in cluster_candidates
|
|
]
|
|
|
|
# save_clusters_image("dont_combine", boxes, cluster_candidates, regions)
|
|
assert len(regions) == 2
|
|
|
|
|
|
class TestObjectBoundingBoxes(unittest.TestCase):
|
|
def setUp(self) -> None:
|
|
pass
|
|
|
|
def test_box_intersection(self):
|
|
box_a = [2012, 191, 2031, 205]
|
|
box_b = [887, 92, 985, 151]
|
|
box_c = [899, 128, 1080, 175]
|
|
|
|
assert intersection(box_a, box_b) == None
|
|
assert intersection(box_b, box_c) == (899, 128, 985, 151)
|
|
|
|
def test_overlapping_objects_reduced(self):
|
|
"""Test that object not on edge of region is used when a higher scoring object at the edge of region is provided."""
|
|
detections = [
|
|
(
|
|
"car",
|
|
0.81,
|
|
(1209, 73, 1437, 163),
|
|
20520,
|
|
2.53333333,
|
|
(1150, 0, 1500, 200),
|
|
),
|
|
(
|
|
"car",
|
|
0.88,
|
|
(1238, 73, 1401, 171),
|
|
15974,
|
|
1.663265306122449,
|
|
(1242, 0, 1602, 360),
|
|
),
|
|
]
|
|
frame_shape = (720, 2560)
|
|
consolidated_detections = reduce_detections(frame_shape, detections)
|
|
assert consolidated_detections == [
|
|
(
|
|
"car",
|
|
0.81,
|
|
(1209, 73, 1437, 163),
|
|
20520,
|
|
2.53333333,
|
|
(1150, 0, 1500, 200),
|
|
)
|
|
]
|
|
|
|
def test_non_overlapping_objects_not_reduced(self):
|
|
"""Test that non overlapping objects are not reduced."""
|
|
detections = [
|
|
(
|
|
"car",
|
|
0.81,
|
|
(1209, 73, 1437, 163),
|
|
20520,
|
|
2.53333333,
|
|
(1150, 0, 1500, 200),
|
|
),
|
|
(
|
|
"car",
|
|
0.83203125,
|
|
(1121, 55, 1214, 100),
|
|
4185,
|
|
2.066666666666667,
|
|
(922, 0, 1242, 320),
|
|
),
|
|
(
|
|
"car",
|
|
0.85546875,
|
|
(1414, 97, 1571, 186),
|
|
13973,
|
|
1.7640449438202248,
|
|
(1248, 0, 1568, 320),
|
|
),
|
|
]
|
|
frame_shape = (720, 2560)
|
|
consolidated_detections = reduce_detections(frame_shape, detections)
|
|
assert len(consolidated_detections) == len(detections)
|
|
|
|
def test_overlapping_different_size_objects_not_reduced(self):
|
|
"""Test that overlapping objects that are significantly different in size are not reduced."""
|
|
detections = [
|
|
(
|
|
"car",
|
|
0.81,
|
|
(164, 279, 816, 719),
|
|
286880,
|
|
1.48,
|
|
(90, 0, 910, 820),
|
|
),
|
|
(
|
|
"car",
|
|
0.83203125,
|
|
(248, 340, 328, 385),
|
|
3600,
|
|
1.777,
|
|
(0, 0, 460, 460),
|
|
),
|
|
]
|
|
frame_shape = (720, 2560)
|
|
consolidated_detections = reduce_detections(frame_shape, detections)
|
|
assert len(consolidated_detections) == len(detections)
|
|
|
|
def test_vert_stacked_cars_not_reduced(self):
|
|
detections = [
|
|
("car", 0.8, (954, 312, 1247, 475), 498512, 1.48, (800, 200, 1400, 600)),
|
|
("car", 0.85, (970, 380, 1273, 610), 698752, 1.56, (800, 200, 1400, 700)),
|
|
]
|
|
frame_shape = (720, 1280)
|
|
consolidated_detections = reduce_detections(frame_shape, detections)
|
|
assert len(consolidated_detections) == len(detections)
|
|
|
|
|
|
class TestRegionGrid(unittest.TestCase):
|
|
def setUp(self) -> None:
|
|
pass
|
|
|
|
def test_region_in_range(self):
|
|
"""Test that region is kept at minimal size when within std dev."""
|
|
frame_shape = (720, 1280)
|
|
box = [450, 450, 550, 550]
|
|
region_grid = [
|
|
[],
|
|
[],
|
|
[],
|
|
[{}, {}, {}, {}, {}, {"sizes": [0.25], "mean": 0.26, "std_dev": 0.01}],
|
|
]
|
|
|
|
region = get_region_from_grid(frame_shape, box, 320, region_grid)
|
|
assert region[2] - region[0] == 320
|
|
|
|
def test_region_out_of_range(self):
|
|
"""Test that region is upsized when outside of std dev."""
|
|
frame_shape = (720, 1280)
|
|
box = [450, 450, 550, 550]
|
|
region_grid = [
|
|
[],
|
|
[],
|
|
[],
|
|
[{}, {}, {}, {}, {}, {"sizes": [0.5], "mean": 0.5, "std_dev": 0.1}],
|
|
]
|
|
|
|
region = get_region_from_grid(frame_shape, box, 320, region_grid)
|
|
assert region[2] - region[0] > 320
|