Label issue of training a faster R-CNN deep learning object detector

2 次查看(过去 30 天)
Hi all! I met an issue of labeling the ROI region for training data. As different network requires different input size, once we resize the input image, the size of bouncing boxes will also change. I used the Image Labler to label the bouncing boxes for each traning image. The initial image size is 224*224 for Resnet50. If I want to use other networks such as AlexNet which requires 227*227 input size, does it mean that I have to relabel all the training images once again? Or is there any other method to adjust the size of bouncing boxes for the new input size?

回答(2 个)

Kritika Bansal
Kritika Bansal 2019-8-2
Hi,
You can move the labels to the workspace and manipulate them according to your required size instead of labeling the whole data again.

hameed asmath
hameed asmath 2020-4-2
Hi,iam using matlabR2013 I need training image labler app to lable ROI region.Is there any options to import that app or else any other app to label ROI region.

类别

Help CenterFile Exchange 中查找有关 Recognition, Object Detection, and Semantic Segmentation 的更多信息

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by