In this article, I will teach you a few things about how to add and customize the tags for your dataset to go directly into online training on TensorArt. But why? Well, because the online training in TensorArt is somewhat limited when it comes to handling tags.

REQUIREMENTS:

The images for which you will generate tags.
Download the program Dataset Processor - All-in-one Tools.
We will also use BooruDatasetTagManager since it is more intuitive for managing tags.
Patience.
Need GPU?, No. (I have only ryzen CPU)

PROCEEDING:

First, it is necessary that you have read your images and stored them in a folder, which we will use later. (This time, I will use sample images.)

Having downloaded the Dataset Processor - All-in-one Tools, we open it and navigate to the "Generate Tags" section.

In this section, where it says "Select input folder," we click there and specify the path to our images. In the "Select output folder" field, we specify the same path.

In the "Select the auto tagger mode" section, we select the WD14v2 or WDv3 model and adjust the "Threshold for predictions" to between 0.25 and 0.50.
5. Then, scroll down and click on "GENERATE TAGS." (The first time, it will take some time because it will download the necessary models; afterwards, it will be immediate.)
When it has finished generating the tags, it will mark as "FINISHED."
So far the process of generating tags
To verify that everything has been done correctly, we will go to our image folder, where each image is accompanied by a TXT file that contains the generated tags. If we open it, we will be able to see the generated TAGS.
PERFECT! NOW YOU HAVE ALL THE TAGS FOR EACH IMAGE! But what if you want to edit them? Well, you won’t open each TXT file one by one; instead, you can use the following tool for quick management.
To do this, we will open the BooruDatasetTagManager, which I assume you have already downloaded. Here, we simply load our dataset (the folder with the image paths and the TXT files), and it loads all the tags associated with the images, allowing us to edit them in bulk or individually. We can add, delete, or replace tags; you can even generate tags (the generator doesn’t work for me).
Now it’s just a matter of having patience and trimming the tags that you don’t need or that affect the quality of the dataset.
When you have finished, simply save the changes or press CTRL + S and close the program.
Next, go to your dataset folder and prepare it to be compressed into a ZIP file.
Now we open the online training in TensorArt and upload our ZIP file.
If you don’t know how to upload a ZIP file, simply click where it says "or upload dataset" and select your ZIP file.
Finally, when your dataset finishes uploading, your images with your customized tags will be loaded. From here on, you only need to adjust the parameters and train! You can also review the tags using TensorArt's function.
DONE! That’s it. It’s a longer process, but it allows you to modify the tags in a more personalized way, which ultimately benefits you by improving the quality of your LoRA training.

I HOPE THIS GUIDE IS VERY HELPFUL FOR YOU IN CREATING TAGS LOCALLY. ADDITIONALLY, IT’S NOT THAT COMPLEX IF YOU FOLLOW IT STEP BY STEP. I apologize for my poor command of the English language, as I am Japanese.

HAPPY HALLOWEEN!

AIIKO

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