How can i detect and localize object using tensorflow and convolutional neural network?

Question

My problem statement is as follows :

\" Object Detection and Localization using Tensorflow and convolutional neural network \"

What i di

Answer 1

You have several ways to go about it.

The most straight forward way is to get some suggested bounding boxes using some bounding box suggestion algorithm like selective search and run on each on of the suggestion the classification net that you already trained. This approach is the approach taken by R-CNN.

For more advanced algorithm based on the above approach i suggest you read about Fast-R-CNN and Faster R-CNN.

Look at Object detection with R-CNN? for some basic explanation.

Darknet and SSD are based on a different approach if you want to undestand them you can read about them on

http://www.cs.unc.edu/~wliu/papers/ssd.pdf https://pjreddie.com/media/files/papers/yolo.pdf

Answer 2

Image localization is a complex problem with many different implementations achieving the same result with different efficiency.

There are 2 main types of implementation

-Localize objects with regression

-Single Shot Detectors

Read this https://leonardoaraujosantos.gitbooks.io/artificial-inteligence/content/object_localization_and_detection.html to get a better idea.

Cheers

Answer 3

I have done a similar project (detection + localization) on Indian Currencies using PyTorch and ResNet34. Following is the link of my kaggle notebook, hope you find it helpful. I have manually collected images from the internet and made bounding box around them and saved their annotation file (Pascal VOC) using "LabelImg" annotation tool.

https://www.kaggle.com/shweta2407/objectdetection-on-custom-dataset-resnet34