AI sense (ML-assisted labeling)
Overview: Labels are generated automatically based on the image, this is also known as pre-labeling.
Steps for using AI Sense: 1.Go to the Editor Page and Click on the AI Sense button from the right side menu. 2.Click on Auto Detect. 3.Click on Preview to view the labels or Add All to add the labels. 4.Users can add individual labels or use Confidence Score to detect labels. 5.Make sure the category is given before using AI Sense.
Categories supported for AI Sense: Single Frame Detection categories:(2D Bounding Boxes)
  1. 1.
    person: A person walking in the scene (usually on sidewalks, crosswalks, outside driveable space
  2. 2.
    bicycle: Human or electric-powered 2-wheeled vehicle designed to travel at lower speeds either on the edge of the road surface, sidewalks, or bike paths. A driving bicycle is also considered a bicycle.
  3. 3.
    car: All Sedan, Suv, minivans, sports cars are marked as cars
  4. 4.
    motorcycle: Gasoline or electric powered 2-wheeled vehicle designed to move rapidly (at the speed of standard cars) on the road surface.
  5. 5.
    airplane
  6. 6.
    bus: A road vehicle designed to carry many passenger
  7. 7.
    train
  8. 8.
    truck: Motor vehicles designed to transport cargo, goods, merchandise, and a wide variety of objects.
  9. 9.
    boat
  10. 10.
    traffic light: A road signal for directing vehicular traffic by means of coloured lights, typically red for stop, green for go, and yellow for proceeding with caution.
  11. 11.
    fire hydrant: a fitting in a street or other public place with a nozzle by which a fire hose may be attached to the water main.
  12. 12.
    stop sign: A stop sign is a traffic sign designed to notify drivers that they must come to a complete stop
  13. 13.
    parking meter
  14. 14.
    bench
  15. 15.
    bird
  16. 16.
    cat
  17. 17.
    dog
  18. 18.
    horse
  19. 19.
    sheep
  20. 20.
    cow
  21. 21.
    elephant
  22. 22.
    bear
  23. 23.
    zebra
  24. 24.
    giraffe
  25. 25.
    backpack
  26. 26.
    umbrella
  27. 27.
    handbag
  28. 28.
    tie
  29. 29.
    suitcase
  30. 30.
    frisbee
  31. 31.
    skis
  32. 32.
    snowboard
  33. 33.
    sports ball
  34. 34.
    kite
  35. 35.
    baseball bat
  36. 36.
    baseball glove
  37. 37.
    skateboard
  38. 38.
    surfboard
  39. 39.
    tennis racket
  40. 40.
    bottle
  41. 41.
    wine glass
  42. 42.
    cup
  43. 43.
    fork
  44. 44.
    knife
  45. 45.
    spoon
  46. 46.
    bowl
  47. 47.
    banana
  48. 48.
    apple
  49. 49.
    sandwich
  50. 50.
    orange
  51. 51.
    broccoli
  52. 52.
    carrot
  53. 53.
    hot dog
  54. 54.
    pizza
  55. 55.
    donut
  56. 56.
    cake
  57. 57.
    chair
  58. 58.
    couch
  59. 59.
    potted plant
  60. 60.
    bed
  61. 61.
    dining table
  62. 62.
    toilet
  63. 63.
    tv
  64. 64.
    laptop
  65. 65.
    mouse
  66. 66.
    remote
  67. 67.
    keyboard
  68. 68.
    cell phone
  69. 69.
    microwave
  70. 70.
    oven
  71. 71.
    toaster
  72. 72.
    sink
  73. 73.
    refrigerator
  74. 74.
    book
  75. 75.
    clock
  76. 76.
    vase
  77. 77.
    scissors
  78. 78.
    teddy bear
  79. 79.
    hair drier
  80. 80.
    toothbrush
Sequence tracking model categories:(2D Bounding Boxes)
  1. 1.
    car
  2. 2.
    truck
  3. 3.
    person
  4. 4.
    bus
  5. 5.
    bike
  6. 6.
    rider: A person is driving a bicycle or motorcycle is considered as rider
  7. 7.
    motor
  8. 8.
    train
Categories for 3d Bounding box (Sequence and Single Frame):
  1. 1.
    Vehicle: All Sedan, Suv, minivans, sports cars are marked as cars
2. Pedestrian: A person walking in the scene(usually on sidewalks, crosswalks, outside driveable space)
3. Cyclist: A Person who is riding a Cycle
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