Этот материал находится в платной подписке. Оформи премиум подписку и смотри или слушай Flutter Artificial Intelligence Course - Build 15+ AI Apps, а также все другие курсы, прямо сейчас!
Премиум
  1. Урок 1. 00:07:28
    Course Introduction
  2. Урок 2. 00:20:08
    For Windows users - Flutter 2.2 Setup
  3. Урок 3. 00:26:16
    For MAC Users - Flutter 2.2 Setup
  4. Урок 4. 00:03:51
    Creating Project and Installing Dependences
  5. Урок 5. 00:10:20
    Adding SplashScreen
  6. Урок 6. 00:04:11
    Creating Home Page
  7. Урок 7. 00:13:35
    Home Page Design - Completed
  8. Урок 8. 00:06:59
    Downloading Dataset and Perform Training on Dataset - Get Trained Model
  9. Урок 9. 00:06:53
    Adding TFlite Functions
  10. Урок 10. 00:02:10
    Creating Functions for Capturing Image and Pick Image from Gallery
  11. Урок 11. 00:04:38
    Completing App and Texting the App
  12. Урок 12. 00:02:08
    create new project
  13. Урок 13. 00:06:09
    Add Splash Screen
  14. Урок 14. 00:14:40
    Implement Live Camera Feature
  15. Урок 15. 00:03:09
    Add and Load TfLite Model for Face Mask Detection
  16. Урок 16. 00:04:25
    Run Model on Camera Stream Frames
  17. Урок 17. 00:01:50
    Finishing the App and Testing the App
  18. Урок 18. 00:03:54
    Ceating and Setting up the project
  19. Урок 19. 00:09:35
    Completing the SplashScreen
  20. Урок 20. 00:13:24
    Completing the Home Page Design
  21. Урок 21. 00:05:00
    Creating Funtions for Uploading and Capturing Photos
  22. Урок 22. 00:09:42
    Download Model and Training it
  23. Урок 23. 00:04:35
    Installing Tflite and ImagePicker
  24. Урок 24. 00:06:17
    Adding Image Recognition Funtions and Testing our App
  25. Урок 25. 00:03:33
    Setup the Project & Everything
  26. Урок 26. 00:02:11
    Installing TfLite in our App
  27. Урок 27. 00:06:00
    Downloading our Dataset and Training our Model
  28. Урок 28. 00:02:48
    Creating Funtions and Testing our app
  29. Урок 29. 00:06:01
    Setup the Project || Ui & Everything
  30. Урок 30. 00:07:34
    Download Dataset and Training our Model
  31. Урок 31. 00:02:18
    Installing TfLite in our application
  32. Урок 32. 00:03:49
    Creating Funtions and Testing our App
  33. Урок 33. 00:01:58
    Create and Setting up Project
  34. Урок 34. 00:06:46
    Add Splash Screen
  35. Урок 35. 00:08:05
    HomeScreen part 1
  36. Урок 36. 00:08:22
    HomeScreen part 2
  37. Урок 37. 00:08:34
    HomeScreen part 3
  38. Урок 38. 00:05:03
    Implement Capture Image and Pick image from Gallery Functions
  39. Урок 39. 00:07:04
    Create API Service
  40. Урок 40. 00:14:40
    Get Image Caption Predictions Response from API
  41. Урок 41. 00:00:53
    Calling the getResponse Function
  42. Урок 42. 00:16:54
    Implement Live Camera Stream Function
  43. Урок 43. 00:22:45
    Finalising the App and Testing the App
  44. Урок 44. 00:02:48
    Create and Setup New Project
  45. Урок 45. 00:03:38
    Install Required Packages
  46. Урок 46. 00:10:50
    Implement Live Camera Function
  47. Урок 47. 00:01:20
    Add Object Detection Model to our Project
  48. Урок 48. 00:04:28
    Load Model into our Flutter Project
  49. Урок 49. 00:05:29
    Run Model on Stream Frame
  50. Урок 50. 00:10:11
    Implement Boxes Around Detected Objects Function
  51. Урок 51. 00:03:51
    Finishing the App and Testing the App
  52. Урок 52. 00:03:12
    Create and Setup Project
  53. Урок 53. 00:05:31
    Add Splash Screen
  54. Урок 54. 00:01:17
    Create Home Page
  55. Урок 55. 00:07:06
    Implement Live Camera Function
  56. Урок 56. 00:05:04
    Add Model and Load Model
  57. Урок 57. 00:02:27
    Run Model on Stream Frame
  58. Урок 58. 00:08:01
    Finish the App and Testing the App
  59. Урок 59. 00:02:25
    Create Project & Setup Everything
  60. Урок 60. 00:07:16
    Add Splash Screen
  61. Урок 61. 00:01:06
    Create Home Page
  62. Урок 62. 00:06:12
    Initialise Live Camera
  63. Урок 63. 00:09:56
    Implement Live Camera Function
  64. Урок 64. 00:05:27
    Add Model in our Project and Load Model
  65. Урок 65. 00:06:43
    Run Model on Camera Stream Frames
  66. Урок 66. 00:03:49
    Finish the App and Testing the App
  67. Урок 67. 00:02:09
    Create and Setup New Project
  68. Урок 68. 00:04:49
    Splash Screen
  69. Урок 69. 00:06:57
    Implement Live Camera Feature for Dogs Breed Recognition
  70. Урок 70. 00:04:30
    Load Model and Run Model for Dog's Breed Live Identification
  71. Урок 71. 00:02:30
    Finishing the App and Testing the App
  72. Урок 72. 00:03:01
    Create New Project and Installing Dependencies
  73. Урок 73. 00:03:31
    Splash Screen
  74. Урок 74. 00:04:13
    Implement Live Camera Feature
  75. Урок 75. 00:03:02
    Load Model and Run Model
  76. Урок 76. 00:01:25
    Finishing the App and Testing the App
  77. Урок 77. 00:04:01
    Create and Setup Project
  78. Урок 78. 00:03:22
    Add Splash Screen
  79. Урок 79. 00:07:26
    Google ML Vision Setup
  80. Урок 80. 00:08:47
    Home Page
  81. Урок 81. 00:05:10
    Implement Pick Image and Capture Image Function
  82. Урок 82. 00:05:32
    Finishing the App and Testing the App
  83. Урок 83. 00:02:10
    Create and Setup Project
  84. Урок 84. 00:03:25
    Add Splash Screen and Installing Dependencies
  85. Урок 85. 00:07:52
    Setup the Google Machine Learning Vision
  86. Урок 86. 00:11:59
    Image Stream Frame Scanner Utils
  87. Урок 87. 00:11:39
    Implement Live Camera Stream Feature
  88. Урок 88. 00:05:17
    Toggle between Front Camera and Back Camera
  89. Урок 89. 00:03:19
    Perform Face Detection on Camera Stream Frame
  90. Урок 90. 00:10:38
    Draw Rectangles around All Detected Faces in Live Camera Stream Frame
  91. Урок 91. 00:02:00
    Finishing the app and Testing the app