PlantSeg Agglomeration Issue: Troubleshooting Guide

Hey everyone,

We've got a situation here where a user, Ioannis, encountered some trouble with PlantSeg after updating to the latest version on conda-forge. It seems like the agglomeration process, which usually works smoothly after the watershed step, is acting up. Specifically, Ioannis is getting a warning message in the console that says:

"WARNING: P [Dummy-3] 2025-08-04 17:00:21,112 plantseg.tasks.segmentation_tasks - The input image is not a boundary probability map. The task will still attempt to run, but the results may not be as expected.
The input image is not a boundary probability map. The task will still attempt to run, but the results may not be as expected."

This is definitely not what we want to see, especially when things were working fine before the update. Ioannis mentioned that the parameters used are the same as before, so the version of PlantSeg seems to be the culprit. Let's dive into the possible causes and solutions for this issue.

Understanding the Problem: Boundary Probability Maps

First off, let's break down the warning message. Boundary probability maps are crucial for the agglomeration process in PlantSeg. Think of them as images that highlight the likelihood of a boundary existing between different segments. The agglomeration algorithm uses this information to decide which segments should be merged together. If the input isn't a proper boundary probability map, the algorithm might make incorrect decisions, leading to poor segmentation results.

So, why is PlantSeg suddenly complaining about the input image not being a boundary probability map? There could be several reasons, and we need to investigate each one. One potential issue could be related to changes in how PlantSeg expects the input data to be formatted or scaled. Maybe the new version requires the boundary probability map to be within a specific range (e.g., 0 to 1) or in a particular data type (e.g., float32). Another possibility is that there's a bug in the new version that's causing it to misinterpret the input data. It’s also possible that a default setting or parameter has changed which is resulting in an unexpected output, so this is something to consider during troubleshooting.

Possible Causes and Troubleshooting Steps

Here’s a structured way to troubleshoot this issue. Let's walk through each of the following steps in detail.

• Data Type and Range: Ensure that the input image's data type and range are compatible with the latest PlantSeg version. Convert or rescale the image if necessary.
• Parameter Check: Verify that the parameters used for the watershed and agglomeration steps are correct and haven't been inadvertently changed.
• Version Compatibility: If the issue persists, consider downgrading to the previous PlantSeg version to see if that resolves the problem. If it does, it suggests a bug in the new version.
• Example Data: Test the workflow with PlantSeg's example data to rule out issues with your specific dataset.
• Community Support: Seek help from the PlantSeg community or developers, providing detailed information about your setup and the error message.

Diving Deep into Data Type and Range

The first thing to check is whether the data type and range of the input image are what PlantSeg expects. The data type refers to the kind of numbers used to represent the image pixels (e.g., 8-bit integers, 32-bit floats), and the range is the minimum and maximum values the pixels can have. If these don't match PlantSeg's expectations, it can lead to misinterpretations and errors. To do this, we should first inspect the image to see the current data type. We can then check PlantSeg's documentation or release notes to find details regarding the expected data type. If they do not match, the image will have to be converted to the correct data type using an appropriate function that maintains data integrity. Additionally, if the data range does not align with PlantSeg's expectations, normalization techniques may need to be applied to scale the values into the expected range. This might involve subtracting the minimum value and dividing by the maximum value or other similar operations.

Parameter Verification: Are the Settings Correct?

Next up, we need to double-check the parameters used for the watershed and agglomeration steps. It's easy to overlook a small change in a parameter that can have a big impact on the results. So, let’s open up your PlantSeg configuration and carefully compare the settings with what you used before the update. Pay close attention to parameters related to the watershed threshold, the agglomeration threshold, and any other parameters that control how segments are merged. If you spot any discrepancies, correct them and try running the workflow again. This step also involves reviewing any custom scripts or configurations you might be using, to ensure they are compatible with the new version of PlantSeg. Sometimes, parameters might have been deprecated or replaced with new ones in the update, so it’s a good idea to cross-reference your configurations with the updated documentation.

Version Rollback: A Test for Bugs

If you’ve gone through the data type, range, and parameter checks, and the issue is still persisting, it might be a bug in the new PlantSeg version. To test this, we can perform what is called a version rollback. That simply means going back to the previous version of PlantSeg that you were using before the update. You can usually do this using conda, which is a package and environment management system. Rolling back can be a swift way to identify if the new update is the problem, and it helps narrow down whether the issues lie within the new version's code. If the process functions correctly after a rollback, it strongly suggests that there's a version-specific issue to address. This information becomes crucial feedback for the PlantSeg developers and can help in their debugging and future releases.

Example Data: Can PlantSeg Handle It?

Another useful troubleshooting step is to test the PlantSeg workflow with its example data. The goal here is to rule out any issues specific to your dataset. If PlantSeg works fine with its example data but fails with yours, it suggests that the problem might lie in your data's format, scale, or some other characteristic. On the other hand, if PlantSeg fails even with its example data, it further points to a more general issue with the installation or the new version itself. Testing with known data is a crucial step in diagnosing the root cause of the problem.

Seeking Community Support

If you've tried all the above steps and are still scratching your head, it's time to tap into the collective brainpower of the PlantSeg community or developers. These people are PlantSeg experts and can provide insights and solutions you might not have thought of. When seeking help, be sure to provide as much detail as possible. Include information about your operating system (Windows 11, in this case), the versions of PlantSeg and its dependencies, the exact error message you're seeing, and any steps you've already taken to troubleshoot the issue. The more information you provide, the easier it will be for others to understand the problem and offer assistance. This step might involve posting on a forum, reaching out on a mailing list, or opening an issue on the PlantSeg's GitHub repository. The key is to make your problem visible to the wider community so that expertise can be shared and solutions can be found collaboratively.

Specific Steps for Ioannis

Okay, Ioannis, let's focus on your specific situation. Based on the information you've provided, here's a step-by-step plan:

1. Verify Data Type and Range: Check the data type and range of your image after the watershed step. Make sure it aligns with what PlantSeg expects for the agglomeration input. If needed, convert or rescale the image.
2. Double-Check Parameters: Go through your watershed and agglomeration parameters. Ensure they are the same as when things were working correctly.
3. Rollback PlantSeg: Try downgrading to the previous PlantSeg version you were using. See if the agglomeration works as expected.
4. Test with Example Data: If the rollback doesn't help, try running PlantSeg with its example data to rule out data-specific issues.
5. Community Help: If all else fails, reach out to the PlantSeg community or developers. Provide them with the error message, your OS info, PlantSeg version, and the troubleshooting steps you've taken.

Wrapping Up

Dealing with software updates can sometimes throw unexpected curveballs. But by systematically troubleshooting and leveraging the community's expertise, we can usually get things back on track. Remember, the key is to break down the problem, gather as much information as possible, and try different solutions one by one. Good luck, and let us know how it goes!