问题
I'm trying to train a CNN model that perform image segmentation, but I'm confused how to create the ground truth if I have several image samples?
Image segmentation can classify each pixel in input image to a pre-defined class, such as cars, buildings, people, or any else.
Is there any tools or some good idea to create the ground truth for image segmentation?
Thanks!
回答1:
Try out https://www.labelbox.io/. Here is what their image segmentation template looks like...
A lot of the code is open source and they have a hosted service to manage labeling end to end.
回答2:
One tool that pops to mind is MIT's LabelMe toolbox: this toolbox is mainly for browsing the existing labeled images of the dataset, but it has an option to annotated new images as well.
There's alos this github repository for COCO UI you might find useful.
回答3:
you can use averaging and normalization techniques all over your dataset so create your ground truth and then label different structures. for this purpose, you can think about creating a so called |template|. make sure all your data are co registered initially.
回答4:
For semantic segmentation every pixel of an image should be labeled. There are three following ways to address the task:
Vector based - polygons, polylines
Pixel based - brush, eraser
AI-powered tools
In Supervisely, tools to perform 1,2,3 are available.
Below are two videos that compare polygon vs AI-powered tools: cars segmentation and food segmentation.
More details about annotation features of Supervisely can be found here.
回答5:
I created an open source tool called COCO Annotator: It provide any features where other tools fall short:
- Directly export to COCO format
- Segmentation of objects
- Useful API endpoints to analyze data
- Import datasets already annotated in COCO format
- Annotated disconnected objects as a single instance
- Labeling image segments with any number of labels simultaneously
- Allow custom metadata for each instance or object
- Magic wand/select tool
- Generate datasets using google images
- User authentication system
来源：https://stackoverflow.com/questions/40600936/how-to-annotate-the-ground-truth-for-image-segmentation