This repository contains the code for the segmentation tool that is used to segment images manually or with the help of the Segment Anything Model (SAM).
First of all, you need to download the SAM checkpoints from here and put it in the folder sam-server.
Next, if you don't have Docker installed, you need to install it and Docker Compose. You can find the instructions here.
Finally, all you need to do is run the following command:
docker-compose up -dIf everything goes well, you can access the application on localhost:4002.
To use the application, you need to create a folder called images inside the folder sam-server. Then, inside this folder, you may create your image groups to segment. An example of path is sam-server/images/group_1.
Inside the group folder, you need to put the images you want to segment.
After that, you can access the application on localhost:4002. Here, you have 3 options:
-
Manual segmentation: use it to segment the images manually. -
Box with SAM segmentation: use it to segment the images with the help of the SAM model using a box as prompt. -
Folder Pre-Processing: indicate a group folder inside thesam-server/imagesfolder to pre-process the images before segmenting them (more info below).
If your API server is not running on localhost at port 5000, make sure to create and update the API_URL in the .env file.
If you want to segment the images manually, click on the Manual segmentation button. You will see the following screen:
Here, indicate the name of the group folder to segment (the folder must be inside the sam-server/images folder) and click on Select Images Folder.
The images will be loaded one by one and you can segment them by drawing on the original image. You'll see the mask on the right side of the screen. When you finish, click on Next to go to the next image. If you did something wrong in the mask, click on Reset to start over.
To annotate the images with SAM's help, the first step is to preprocess the images. This step is necessary because SAM may take a long time to generate the data required for segmentation. Preprocessing the images improves the user experience by generating the necessary data beforehand.
To pre-process the images, set the group folder (inside the sam-server/images folder) and click on Folder Pre-Processing.
After preprocessing, a .pkl file is created for each image in the folder. This file contains the data that SAM needs to segment the image along with the prompt (in this case, a box).
Note that preprocessing may take a while (5-10 minutes for 50 images), but it is a one-time process. Once complete, you can segment the images without waiting again.
Now, choose Box with SAM segmentation. The process is similar to the manual segmentation, but now you will see the mask generated by SAM based on the box prompt you draw.
Example of box segmentation:
After completing the annotations, you can download the results by clicking on the Download button. The results will be downloaded in a .zip file.
If you encounter any issues during this step, all results are saved in the folder sam-server/sessions.