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Why so serious? Using GCP for realtime video co...

Avatar for Johann du Toit Johann du Toit
March 06, 2019
Programming
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77

Why so serious? Using GCP for realtime video context analyzation

Look into real-time video processing and how you might do this on Google Cloud
Avatar for Johann du Toit

Johann du Toit

March 06, 2019
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Transcript

  1. None

  2. [email protected] email website @signedness

  3. Technical Lead for Cloud

  4. Developer Expert (first in Africa) https://developers.google.com/experts/people/johann-du-toit

  5. Certified Architect + Data Engineer

  6. Mentor since 2016

  7. None

  8. THIS TALK Realtime processing on video Further processing using Vision

    API Training a custom model on Google Cloud

  9. THIS TALK Realtime processing on video Further processing using Vision

    API Training a custom model on Google Cloud
  10. None

  11. 14 cameras per metro station on your way out

  12. None
  13. None
  14. None
  15. None
  16. None
  17. None

  18. gocv.VideoCaptureDevice(0)

  19. gocv.VideoCaptureFile(“a.mp4”)

  20. gocv.IMRead(“test.png”)

  21. for { webcam.Read(&img) window.IMShow(img) window.WaitKey(1) }

  22. for { webcam.Read(&img) window.IMShow(img) window.WaitKey(1) }

  23. gocv.NewWindow("Raw Video Source")

  24. gocv.NewWindow("Raw Video Source") gocv.NewWindow("Raw Video Source")

  25. None

  26. for { webcam.Read(&img) // identify cars window.IMShow(img) window.WaitKey(1) }

  27. None
  28. None
  29. None

  30. 30 frames per second

  31. 1000ms

  32. 33ms

  33. None

  34. ~20ms

  35. None
  36. None
  37. None

  38. 10ms 10ms 10ms 10ms 10ms 10ms 10ms 10ms 10ms 10ms

    10ms 10ms 10ms 10ms 10ms 10ms 10ms 10ms 10ms 10m 10ms 10ms 10ms 10ms 10ms 10ms 10ms 10m 10ms 10ms 10m 10ms 10ms 10ms 10ms 10ms 10ms 10ms 10ms 10ms 10ms 10ms 10ms 10m 10m 10ms 10ms 10ms 10ms
  39. None
  40. None
  41. None
  42. None

  43. HAAR Cascades

  44. HAAR Wavelets

  45. None
  46. None
  47. None
  48. None

  49. ~20ms

  50. None

  51. frameNumber % 1 == 0

  52. frameNumber % 2 == 0

  53. frameNumber % 3 == 0

  54. None

  55. THE AGENDA Realtime processing on video Further processing using Vision

    API Training a custom model on Google Cloud
  56. None
  57. None
  58. None

  59. 2 Events

  60. None
  61. None

  62. ImageNet (14 million images)

  63. > day on

  64. < 6 minutes

  65. None
  66. None
  67. None
  68. None
  69. None
  70. None
  71. None
  72. None
  73. None
  74. None
  75. None
  76. None
  77. None
  78. None
  79. None
  80. None

  81. THE AGENDA Realtime processing on video Vision API Training a

    custom model on Google Cloud
  82. None
  83. None
  84. None
  85. None
  86. None
  87. None
  88. None
  89. None
  90. None
  91. None
  92. None
  93. None
  94. None
  95. None
  96. None
  97. None

  98. FIN

  99. FINN