CODEWITHSUNDEEP
tensorflowobject-detection
nimop
nimop

Reputation: 1

Understanding exactly what the pretrained model does on the Tensorflow object detection API

I am trying to understand what I need from any pre-trained model used in the API regardless of any additional code found on the Tensorflow object detection API. For example: ssd_mobilenet_v1_coco_2017_11_17, depending on what I have understood: it is a model that is already trained to detect objects (there is a classification to know the category of the object + Regression to bound the objects with rectangles and those rectangles are actually the x,y,w,h coordinates on the object).

How do we benefit from the regression output of that model (x,y,w,h coordinates) to use them in another model?

Let's assume we want to print out just the coordinates x,y,w,h of a detected object on an image without any need of the code of Tensorflow object detection API, how can we do that?

Upvotes: 0

Views: 194

Answers (1)

Danny Fang
Danny Fang

Reputation: 4071

Certainly you can use the pretrained model provided in tensorflow object detection model zoo without installing object detection api. The alternative solution is to use opencv.

Opencv has provided both c++ and python api to call .pb models generated by tensorflow. Here is a nice tutorial.

Upvotes: 0

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