Instance segmentation failing even on the training images

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Worked on this project I was testing the segmentation using some of the annotated images used as training set (i.e. this one) and it totally fails, detecting with ultralow confidence just one of the categories. Testing other images get the same result, or even worse find a totally wrong category.

Due the original dataset was 41 images with 18 classes, with around 800 images in the dataset after augmentation, I was expecting a low confidence, but not a totally unusable result.

Wanted to ask if there might be something wrong in the training setup, or my expectations was just wrong and I will need a more balanced dataset (this is the health check result)

I’m sorry, but your question seems to be incomplete. Could you please provide more details about your issue or question related to the Instance Segmentation project on Roboflow? Also, please specify your operating system and browser for better assistance.

In the meantime, here are some resources that might be helpful:

  • To start an Instance Segmentation project, you can log in to your Roboflow account, create a new project, and choose the Instance Segmentation project type. You can share your project with the community on Roboflow Discuss (source).

  • If you need to upload data for your project, you can create a project and upload images via the web interface. If you already have a project, click “Upload” in the project sidebar to upload images (source).

  • You can also use the Roboflow Universe to find datasets for your project. To download data from Universe, search for a dataset that meets your needs, click the “Download this Dataset” button to export the dataset, unzip the folder downloaded from Universe, and upload it into Roboflow (source).

  • If you need to clone images from Roboflow Universe to your project, you can use the “Clone Images” feature. Search Roboflow Universe for a dataset, enter the project’s “Images” page, select the images you wish to copy, and choose the target destination workspace and project (source).

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This is the segmentation coming from the v1 version of the model on the linked image

So just two classes, no segmentation, accuracy 6%

This are the very same image annotations
Brenner-base-tunnel-Mules.jpg > Tunneling (

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