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I'm trying to implement Tensorflow object detection API sample. I am following sentdex videos for getting started. The sample code runs perfectly, it also shows the images which are used for testing the results, but no boundaries around detected objects are shown. Just the plane image is displayed without any errors.
I'm using this code: This Github link.
This is my result after running the sample code.
another image without any detection.
What I'm missing here? The code is included in above link and there is no error logs.
Results of box, score, classes, num in that order.
[[[ 0.74907303 0.14624023 1. 1. ]
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[ 0.74907303 0.14624023 1. 1. ]
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[ 0.74907303 0.14624023 1. 1. ]
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[ 0.74907303 0.14624023 1. 1. ]
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[ 0.74907303 0.14624023 1. 1. ]
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[ 0.74907303 0.14624023 1. 1. ]
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[ 0.74907303 0.14624023 1. 1. ]
[ 0.74907303 0.14624023 1. 1. ]
[ 0.74907303 0.14624023 1. 1. ]
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[ 0.74907303 0.14624023 1. 1. ]
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[ 0.74907303 0.14624023 1. 1. ]
[ 0.74907303 0.14624023 1. 1. ]
[ 0. 0. 1. 1. ]
[ 0. 0. 1. 1. ]
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[ 0.74907303 0.14624023 1. 1. ]
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[[ 0.03587547 0.02224986 0.0186467 0.01096812 0.01003207 0.00654409
0.00633549 0.00534311 0.0049596 0.00410213 0.00362371 0.00339186
0.00308251 0.00303347 0.00293389 0.00277099 0.00269575 0.00266825
0.00263925 0.00263331 0.00258657 0.00240822 0.0022581 0.00186967
0.00184311 0.00180467 0.00177475 0.00173655 0.00172811 0.00171935
0.00171891 0.00170288 0.00163755 0.00162967 0.00160273 0.00156545
0.00153615 0.00140941 0.00132407 0.00131524 0.0013105 0.00129431
0.0012582 0.0012553 0.00122365 0.00119186 0.00115651 0.00115186
0.00112369 0.00107097 0.00105805 0.00104338 0.00102719 0.00102337
0.00100349 0.00097762 0.00096851 0.00092741 0.00088506 0.00087696
0.0008734 0.00084826 0.00084135 0.00083513 0.00083398 0.00082068
0.00080583 0.00078979 0.00078059 0.00077476 0.00075448 0.00074426
0.00074421 0.00070195 0.00068741 0.00068138 0.00067262 0.00067125
0.00067033 0.00066035 0.00064729 0.00064205 0.00061964 0.00061794
0.00060835 0.00060465 0.00059548 0.00059479 0.00059461 0.00059436
0.00059426 0.00059411 0.00059406 0.00059392 0.00059365 0.00059351
0.00059191 0.00058798 0.00058682 0.00058148]]
[[ 1. 1. 18. 32. 62. 60. 63. 67. 61. 49. 31. 84. 50. 54.
15. 44. 44. 49. 31. 56. 88. 28. 88. 52. 17. 32. 38. 75.
3. 33. 48. 59. 35. 57. 47. 51. 19. 27. 72. 4. 84. 6.
55. 20. 58. 65. 61. 82. 42. 34. 40. 21. 43. 64. 39. 62.
36. 22. 79. 46. 16. 40. 41. 77. 16. 48. 78. 77. 89. 86.
27. 8. 87. 5. 25. 70. 80. 76. 75. 67. 65. 37. 2. 9.
73. 63. 29. 30. 69. 66. 68. 26. 71. 12. 45. 83. 13. 85.
74. 23.]]
[ 100.]
[[[ 0. 0. 1. 1. ]
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[ 0. 0. 1. 1. ]
[ 0. 0. 1. 1. ]
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[ 0. 0.68494415 1. 1. ]
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[[ 0.01044297 0.0098214 0.00942165 0.00846471 0.00613666 0.00398615
0.00357754 0.0030054 0.00255861 0.00236574 0.00232631 0.00220291
0.00185227 0.0016354 0.0015979 0.00145072 0.00143661 0.00141369
0.00122685 0.00118978 0.00108457 0.00104251 0.00099215 0.00096401
0.0008708 0.00084773 0.00080484 0.00078507 0.00078378 0.00076876
0.00072774 0.00071732 0.00071348 0.00070812 0.00069253 0.0006762
0.00067269 0.00059905 0.00059367 0.000588 0.00056114 0.0005504
0.00051472 0.00051057 0.00050973 0.00048486 0.00047297 0.00046204
0.00044787 0.00043259 0.00042987 0.00042673 0.00041978 0.00040494
0.00040087 0.00039576 0.00039059 0.00037274 0.00036831 0.00036417
0.00036119 0.00034645 0.00034479 0.00034078 0.00033771 0.00033605
0.0003333 0.0003304 0.0003294 0.00032326 0.00031787 0.00031773
0.00031748 0.00031741 0.00031732 0.00031729 0.00031724 0.00031722
0.00031717 0.00031708 0.00031702 0.00031579 0.00030416 0.00030222
0.00029739 0.00029726 0.00028289 0.0002653 0.00026325 0.00024584
0.00024221 0.00024156 0.00023911 0.00023335 0.00021619 0.0002001
0.00019127 0.00018342 0.00017273 0.00015509]]
[[ 38. 1. 1. 16. 25. 38. 64. 24. 49. 56. 20. 3. 28. 2.
48. 19. 21. 62. 50. 6. 8. 7. 67. 18. 35. 53. 39. 55.
15. 57. 72. 52. 10. 5. 42. 43. 76. 22. 82. 4. 61. 23.
17. 16. 87. 62. 51. 60. 36. 58. 59. 33. 31. 54. 70. 11.
40. 79. 31. 9. 41. 77. 80. 34. 90. 89. 73. 13. 84. 32.
63. 29. 30. 69. 66. 68. 26. 71. 12. 45. 83. 14. 44. 78.
85. 46. 47. 19. 65. 74. 37. 27. 63. 88. 28. 81. 86. 75.
27. 18.]]
[ 100.]
EDIT: As per suggested answers, it is working when we use faster_rcnn_resnet101_coco_2017_11_08 model. But it is more accurate and that's why slower. I want this application with high speed because I'm going to use it in real time (on webcam) object detection. So I need to use faster model (ssd_mobilenet_v1_coco_2017_11_08)
694
The TensorFlow Object Detection API is an open-source framework built on top of TensorFlow that makes it easy to construct, train and deploy object detection models. There are already pre-trained models in their framework which are referred to as Model Zoo.
The TensorFlow Object Detection API is an open-source computer vision framework for building object detection and image segmentation models that can localize multiple objects in the same image. The framework works for both TensorFlow 1 and 2.
The problem is from the model: 'ssd_mobilenet_v1_coco_2017_11_08'
Solution: change to an differrent version 'ssd_mobilenet_v1_coco_11_06_2017' (this model type is the fastest one, change to other model types will make it slower and not the thing that you want)
Just change 1 line of code:
# What model to download.
MODEL_NAME = 'ssd_mobilenet_v1_coco_11_06_2017'
When I use your code, nothing is shown but when I replace it with my previous experiment model 'ssd_mobilenet_v1_coco_11_06_2017' it works fine
87
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