I am following this tutorial: https://tensorflow-object-detection-api-...ining.html And after training I use code for object detection. What I get are rectangles with percentage and labels
1) Why does this happen? How can I fix that?
Also, I have 10 images. From each image I get 100 objects that depict the same object differently. For instance: from
2) Does the rationale behind
Update: I also use this command
"n/a"
. 1) Why does this happen? How can I fix that?
Also, I have 10 images. From each image I get 100 objects that depict the same object differently. For instance: from
"image_1"
I get "cat"
100 different images (from "image_1"
). From "image_2"
I get 100 different depicted "dog"
images. From "image_3"
I get 100 different depicted "mouse"
images and things go like that. As you can understand every main
image is a different class. So, in the label_map.pbtxt
things are like that:1 2 3 4 5 6 7 8 9 10 11 12 13 14 |
item { id : 1 name: 'cat' } item { id : 2 name: 'dog' } item { id : 3 name: 'mouse' } ... |
label_map.pbtxt
make sense? I am asking that in addition/auxiliary to my 1st question to identify if that is the problem...Update: I also use this command
category_index ={'name':'dummyname','id':1}
in order to overcome some errors/warnings. Could this be the problem? But, if I remove it the object detection code does not run... (source: https://stackoverflow.com/questions/7148...how-to-fix)