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Deep Learning library for Kotlin.
/*
* Copyright 2020 JetBrains s.r.o. and Kotlin Deep Learning project contributors. All Rights Reserved.
* Use of this source code is governed by the Apache 2.0 license that can be found in the LICENSE.txt file.
*/
package org.jetbrains.kotlinx.dl.dataset.handler
/**
* 80 object categories in COCO dataset.
*
* @see
* COCO dataset
*/
public val cocoCategories: Map = mapOf(
1 to "person",
2 to "bicycle",
3 to "car",
4 to "motorbike",
5 to "aeroplane",
6 to "bus",
7 to "train",
8 to "truck",
9 to "boat",
10 to "traffic light",
11 to "fire hydrant",
12 to "stop sign",
13 to "parking meter",
14 to "bench",
15 to "bird",
16 to "cat",
17 to "dog",
18 to "horse",
19 to "sheep",
20 to "cow",
21 to "elephant",
22 to "bear",
23 to "zebra",
24 to "giraffe",
25 to "backpack",
26 to "umbrella",
27 to "handbag",
28 to "tie",
29 to "suitcase",
30 to "frisbee",
31 to "skis",
32 to "snowboard",
33 to "sports ball",
34 to "kite",
35 to "baseball bat",
36 to "baseball glove",
37 to "skateboard",
38 to "surfboard",
39 to "tennis racket",
40 to "bottle",
41 to "wine glass",
42 to "cup",
43 to "fork",
44 to "knife",
45 to "spoon",
46 to "bowl",
47 to "banana",
48 to "apple",
49 to "sandwich",
50 to "orange",
51 to "broccoli",
52 to "carrot",
53 to "hot dog",
54 to "pizza",
55 to "donut",
56 to "cake",
57 to "chair",
58 to "sofa",
59 to "potted plant",
60 to "bed",
61 to "dining table",
62 to "toilet",
63 to "tvmonitor",
64 to "laptop",
65 to "mouse",
66 to "remote",
67 to "keyboard",
68 to "cell phone",
69 to "microwave",
70 to "oven",
71 to "toaster",
72 to "sink",
73 to "refrigerator",
74 to "book",
75 to "clock",
76 to "vase",
77 to "scissors",
78 to "teddy bear",
79 to "hair drier",
80 to "toothbrush"
)
/**
* 80 object categories in COCO dataset.
*
* @see
* COCO dataset
*/
public val cocoCategoriesForEfficientDet: Map = mapOf(
1 to "person",
2 to "bicycle",
3 to "car",
4 to "motorcycle",
5 to "airplane",
6 to "bus",
7 to "train",
8 to "truck",
9 to "boat",
10 to "traffic light",
11 to "fire hydrant",
13 to "stop sign",
14 to "parking meter",
15 to "bench",
16 to "bird",
17 to "cat",
18 to "dog",
19 to "horse",
20 to "sheep",
21 to "cow",
22 to "elephant",
23 to "bear",
24 to "zebra",
25 to "giraffe",
27 to "backpack",
28 to "umbrella",
31 to "handbag",
32 to "tie",
33 to "suitcase",
34 to "frisbee",
35 to "skis",
36 to "snowboard",
37 to "sports ball",
38 to "kite",
39 to "baseball bat",
40 to "baseball glove",
41 to "skateboard",
42 to "surfboard",
43 to "tennis racket",
44 to "bottle",
46 to "wine glass",
47 to "cup",
48 to "fork",
49 to "knife",
50 to "spoon",
51 to "bowl",
52 to "banana",
53 to "apple",
54 to "sandwich",
55 to "orange",
56 to "broccoli",
57 to "carrot",
58 to "hot dog",
59 to "pizza",
60 to "donut",
61 to "cake",
62 to "chair",
63 to "couch",
64 to "potted plant",
65 to "bed",
67 to "dining table",
70 to "toilet",
72 to "tv",
73 to "laptop",
74 to "mouse",
75 to "remote",
76 to "keyboard",
77 to "cell phone",
78 to "microwave",
79 to "oven",
80 to "toaster",
81 to "sink",
82 to "refrigerator",
84 to "book",
85 to "clock",
86 to "vase",
87 to "scissors",
88 to "teddy bear",
89 to "hair drier",
90 to "toothbrush"
)
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