Tensorflow对象检测API中没有检测到什么
我试图实现Tensorflow对象检测API示例。我正在关注sentdex视频。示例代码运行良好,它还显示用于测试结果的图像,但未显示检测到的对象周围的边界。只是平面图像显示没有任何错误。Tensorflow对象检测API中没有检测到什么
我使用此代码:This Github link。
这是运行示例代码后的结果。
没有任何检测的另一图像。
什么我错过这里?代码包含在上面的链接中,并且没有错误日志。
按照该顺序的框,分数,类别,数量的结果。
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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.]
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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.]
编辑:按参考答案,这是工作,当我们使用faster_rcnn_resnet101_coco_2017_11_08
模型。但它更准确,这就是为什么要慢。我希望高速应用这个应用程序,因为我将实时(在网络摄像头上)对象检测中使用它。所以,我需要使用更快的模型(ssd_mobilenet_v1_coco_2017_11_08
)
功能visualize_boxes_and_labels_on_image_array具有下面的代码:
for i in range(min(max_boxes_to_draw, boxes.shape[0])):
if scores is None or scores[i] > min_score_thresh:
如此,得分必须比min_score_thresh(默认值0.5)更大,你可以检查是否有一些分数比它大。
解决方法将#MODEL_NAME ='ssd_mobilenet_v1_coco_2017_11_08'更改为MODEL_NAME ='faster_rcnn_resnet101_coco_2017_11_08'。
的问题是从模型:'ssd_mobilenet_v1_coco_2017_11_08'
解决方法:更改为differrent版本'ssd_mobilenet_v1_coco_11_06_2017'
(这种模式类型为最快的国家之一,更改为其他模型类型将使其更慢,而不是东西你想要的)
只要改变1行代码:
# What model to download.
MODEL_NAME = 'ssd_mobilenet_v1_coco_11_06_2017'
当我用你的鳕鱼e,什么都没有显示,但当我用我以前的实验模型替换它'ssd_mobilenet_v1_coco_11_06_2017'
它工作正常
我曾经有同样的问题。
但一种新的模式最近已被上传“ssd_mobilenet_v1_coco_2017_11_17”
我尝试过了,就像魅力:)
你能告诉我们的价值观(盒,分数,等级,NUM) ;我想了解是否有任何物体被检测到。 – Zephro
我该怎么做? @Zephro – Kaushal28
好吗通过打印框的坐标? – Kaushal28