Training with custom data

[Amit12690]

I have few images where I have to segment 2 kinds of flowers . I wish to achieve it using Yoloact. However I am very confused with how to prepare my dataset suitable for training . Can anyone please help me with the following :

• Any annotation tool for labelling and getting the annotations in coco format

• How to proceed once I have the annotated data ?

Sorry if this is a very basic question . I have just started looking in to instance segmentation , so confused

[dbolya]

I'm not very familiar with preparing instance segmentation data as I've just been using COCO this whole time, but I've heard good things about LabelMe. Once you have the LabelMe annotations then you can use labelme2coco to convert it to coco annotations and then proceed with the custom dataset instructions in my readme.

I haven't use either of those tools though--I've just heard about others using them.

[Amit12690]

Thanks a lot @dbolya . I will try labelme.

[abhigoku10]

@Amit12690 as dbolya suggested , you can use that it will work since i have used the same approach for annotation and training

[Amit12690]

@abhigoku10 @dbolya Thanks for the advice. Labelme is so easy to use. I am trying it on a sample dataset. Will update once I get training to work

[Amit12690]

@dbolya @abhigoku10 I think my training has made progress , thanks a lot for your valuable suggestions. Labelme and labelme2coco.py work perfectly to create the dataset. For anyone who is planning to finetune/train the model on a custom dataset , please follow following steps :

• Download and install Labelme (https://github.com/wkentaro/labelme)
• Label using polygon labelling option provided (The repo has nice tutorials)
• A json file will be created for each image labelled
• Now use create a label.txt (Example : https://github.com/wkentaro/labelme/blob/master/examples/instance_segmentation/labels.txt)
• To generate coco style json : ./labelme2coco.py <labelled_data_folder> <out_folder> --labels labels.txt
  More details : https://github.com/wkentaro/labelme/tree/master/examples/instance_segmentation

Done! The dataset is created. Now proceed with the instruction in the yolact repo on custom training

[abhigoku10]

@Amit12690 nice work in sharing the steps .!!!

[dbolya]

Thanks @Amit12690 for the steps! I've added a link to your post in the readme for future reference, and I'll close the issue for now.

[imvisibleman]

hi， @Amit12690 Can you train the source code?

[imvisibleman]

I have encountered some problems and hope to get your help.

[abhigoku10]

@imvisibleman what is the problem ur facing pls share the errors

[imvisibleman]

I am a high school student, so my code understanding ability is not very strong, but I am very interested in yolact. Just like yoloV3, after I finished the data annotation, I don't know how to train my data.

[imvisibleman]

@abhigoku10 Can you help me?

[imvisibleman]

Is the Train.py code running directly?

[imvisibleman]

I don't know how to set the parameters.