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I have red the part where it's explained how to train the model using your own dataset. However, it doesn't tell how and where to put the training images.
There is a mention of the dataset here: flow --model cfg/tiny-yolo-voc-3c.cfg --load bin/tiny-yolo-voc.weights --train --annotation train/Annotations --dataset train/Images
but I don't know how the images should be organized with labels.
My training dataset is organized in folders each folder is named after the class of the images that it contains. Is there anyway I can use this code on such training dataset?
Thank you!
The text was updated successfully, but these errors were encountered:
You are referring to weakly supervised object detection, where you localize objects in your image based on only image level labels. I suggest you look into that. This repo is useful if you are willing to hand-annotate your data with bounding boxes.
I have red the part where it's explained how to train the model using your own dataset. However, it doesn't tell how and where to put the training images.
There is a mention of the dataset here: flow --model cfg/tiny-yolo-voc-3c.cfg --load bin/tiny-yolo-voc.weights --train --annotation train/Annotations --dataset train/Images
but I don't know how the images should be organized with labels.
My training dataset is organized in folders each folder is named after the class of the images that it contains. Is there anyway I can use this code on such training dataset?
Thank you!
The text was updated successfully, but these errors were encountered: