EXAMPLE/robot/lifelong_learning_bench/semantic-segmentation verified and updated. #242

RONAK-AI647 · 2025-08-12T05:26:06Z

I was trying to run examples/robot/lifelong_learning_bench/semantic-segmentation to learn the use of Ianvs. However, the entire process of running this example was not so easy. So after many iterations and checks I have verified the example and updated the README.md so could any user can understand it well.

What type of PR is this?

/kind bug
/kind cleanup
/kind documentation

What this PR does / why we need it:
This PR verifies the example and well documents it. This PR involves :

1)Updating the README.md and seperating the parts of simple and sam model.
Verifying the exmpale by running it
2)Removing hard-coded paths
3)Sort out project dependencies and complete the documentation, especially 4)the missing packages and configuration of dataset path.
5)replace print with logger.info for better monitoring.

Which issue(s) this PR fixes:

Fixes #106

1)the print is replaced with logger.in 2) hardcoded paths are removed with relative path 3) the readme made more detaled and clear Signed-off-by: RONAK <codeitronak226277@gmail.com>

kubeedge-bot · 2025-08-12T05:26:14Z

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gemini-code-assist

Summary of Changes

Hello @RONAK-AI647, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request significantly enhances the usability and clarity of the semantic-segmentation example within the ianvs project. It addresses difficulties encountered during the example's execution by providing comprehensive documentation, streamlining setup processes, and improving code logging. The changes aim to make the example more accessible and understandable for new users, ensuring a smoother experience for anyone trying to learn or utilize Ianvs through this example.

Highlights

Improved Documentation: The README.md for the semantic segmentation example has been completely overhauled, featuring a detailed table of contents, clear prerequisites, and separate, step-by-step guides for both simple and large vision model (SAM) benchmarking.
Streamlined Setup: Instructions for Ianvs setup, virtual environment creation, and dataset preparation have been made more explicit, including direct Kaggle download links and expected dataset directory structures.
Dependency Management: A new requirements.txt file has been added specifically for the semantic segmentation example, ensuring all necessary Python packages are easily installable.
Path Standardization: Hard-coded absolute paths in various configuration (.yaml) files have been replaced with relative paths, improving portability and consistency across different environments.
Enhanced Logging: Numerous print statements across the Python codebase have been replaced with logger.info calls, providing more structured and monitorable output during execution.
Git Ignore Updates: Added datasets/ and workspace/ to .gitignore to prevent unnecessary large files from being committed to the repository.

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Signed-off-by: RONAK <codeitronak226277@gmail.com>

gemini-code-assist

Code Review

This pull request significantly improves the documentation and usability of the semantic segmentation example by updating the README, removing some hardcoded paths, and replacing print statements with a structured logger. These are all valuable changes. However, the review identified several critical issues that need to be addressed. There are still hardcoded paths in the source code, which contradicts one of the main goals of this PR. The new requirements.txt uses latest for dependencies, which harms reproducibility. There's also a critical bug in eval.py due to an incorrect import update, and several configuration files contain invalid values. Addressing these points will greatly improve the quality and reliability of the example.

examples/robot/lifelong_learning_bench/semantic-segmentation/testalgorithms/rfnet/RFNet/eval.py

examples/robot/lifelong_learning_bench/semantic-segmentation/requirements.txt

examples/robot/lifelong_learning_bench/semantic-segmentation/testalgorithms/rfnet/RFNet/eval.py

examples/robot/lifelong_learning_bench/semantic-segmentation/testenv/testenv-all.yaml

examples/robot/lifelong_learning_bench/semantic-segmentation/testenv/testenv-city.yaml

examples/robot/lifelong_learning_bench/semantic-segmentation/testenv/testenv.yaml

gemini-code-assist · 2025-08-12T05:28:35Z

.../robot/lifelong_learning_bench/semantic-segmentation/testalgorithms/rfnet/RFNet/basemodel.py

    def train(self, train_data, valid_data=None, **kwargs):        
        self.trainer = Trainer(self.train_args, train_data=train_data)
-        print("Total epoches:", self.trainer.args.epochs)
+        logger.info("Total epoches:", self.trainer.args.epochs)


The logger's info method expects a single string argument for the message. Passing multiple arguments like this will result in a tuple being logged, which is likely not the intended format. Please use string formatting to combine the message and variables into a single string, for example: logger.info(f"Total epoches: {self.trainer.args.epochs}"). This issue is present in multiple files across this PR.

Suggested change

logger.info("Total epoches:", self.trainer.args.epochs)

logger.info(f"Total epoches: {self.trainer.args.epochs}")

RONAK-AI647 · 2025-08-12T05:31:19Z

I checked my fork had some mistakes and some wrong files which wee creating confusions. So , I renewed my fork with proper cloning this time , hence the prs are renewed. Thank You.

hsj576 · 2025-08-21T01:57:47Z

...g_learning_bench/semantic-segmentation/testalgorithms/rfnet/RFNet/dataloaders/datasets/e1.py

        img_path = self.images[self.split][index].rstrip()
        disp_path = self.disparities[self.split][index].rstrip()
-        #print(index)
+        #logger.info(index)


Commented-out code can be deleted directly.

hsj576 · 2025-08-21T02:02:26Z

examples/robot/lifelong_learning_bench/semantic-segmentation/testalgorithms/rfnet/RFNet/eval.py

 import mmcv
 import pycocotools.mask as maskUtils
-from mmdet.visualization.image import imshow_det_bboxes
+from mmdet.visualization import DetLocalVisualizer


We need the module "imshow_det_bboxes" to visualize the results.

hsj576 · 2025-08-21T02:06:31Z

Could you show the results of running this example as expected?

semantic-segmentation-README.md file updated

8cbac0c

1)the print is replaced with logger.in 2) hardcoded paths are removed with relative path 3) the readme made more detaled and clear Signed-off-by: RONAK <codeitronak226277@gmail.com>

kubeedge-bot added kind/bug Categorizes issue or PR as related to a bug. kind/cleanup Categorizes issue or PR as related to cleaning up code, process, or technical debt. kind/documentation Categorizes issue or PR as related to documentation. labels Aug 12, 2025

kubeedge-bot requested review from MooreZheng and Poorunga August 12, 2025 05:26

kubeedge-bot added the size/XL Denotes a PR that changes 500-999 lines, ignoring generated files. label Aug 12, 2025

RONAK-AI647 changed the title ~~Ronak a1647/ guide for running the example of robot/lifelong learning bench/semantic segmentation #106 open~~ EXAMPLE/robot/lifelong_learning_bench/semantic-segmentation verified and updated. #238 Aug 12, 2025

gemini-code-assist bot reviewed Aug 12, 2025

View reviewed changes

Update rfnet.py

abbd66a

Signed-off-by: RONAK <codeitronak226277@gmail.com>

gemini-code-assist bot reviewed Aug 12, 2025

View reviewed changes

RONAK-AI647 force-pushed the RONAK-A1647/-Guide-for-running-the-example-of-robot/lifelong_learning_bench/semantic-segmentation-#106-Open branch from b3c83a1 to abbd66a Compare August 12, 2025 05:28

RONAK-AI647 changed the title ~~EXAMPLE/robot/lifelong_learning_bench/semantic-segmentation verified and updated. #238~~ EXAMPLE/robot/lifelong_learning_bench/semantic-segmentation verified and updated. Aug 12, 2025

hsj576 requested changes Aug 21, 2025

View reviewed changes

kubeedge-bot assigned hsj576 Aug 21, 2025

RONAK-AI647 mentioned this pull request Aug 24, 2025

PRE-TASK: example/robot/lifelong_learning_bench/semantic-segmentation Comprehensive (Example Restoration for KubeEdge Ianvs (2025 Term 3)) #248

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RONAK-AI647 mentioned this pull request Dec 2, 2025

REQUEST: New membership for Ronak Raj kubeedge/community#245

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EXAMPLE/robot/lifelong_learning_bench/semantic-segmentation verified and updated. #242

EXAMPLE/robot/lifelong_learning_bench/semantic-segmentation verified and updated. #242

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	logger.info("Total epoches:", self.trainer.args.epochs)
	logger.info(f"Total epoches: {self.trainer.args.epochs}")

EXAMPLE/robot/lifelong_learning_bench/semantic-segmentation verified and updated. #242

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EXAMPLE/robot/lifelong_learning_bench/semantic-segmentation verified and updated. #242

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