Comments (3)
jakubczakon
commented on June 3, 2024
Hi @Ahsanr312 thank you for the suggestion.
Actually, you can do any of the options right now.
This repository is more about how to train it (how we trained it) than "generalizable" results.
We wanted to share our work on this competition with the world.
One thing to keep in mind is that this was built for buildings so perhaps you should use a different dataset than MS COCO (cityscape is a good one I believe).
Good luck with fine-tuning!
from open-solution-mapping-challenge.
Ahsanr312
commented on June 3, 2024
I have looked for steps to fine-tune the model but couldn't fine anything.
Can you help me with it? @jakubczakon
from open-solution-mapping-challenge.
data-overload
commented on June 3, 2024
@Ahsanr312 Were you able to figure out how to tune the model?
I prepared the training directory as per the Readme with my own images+annotations but get a DecodeError running the train command.
Edit: that error is fixed by upgrading neptune client, however I still struggle to produce new tuned weights (no errors but I don't see the output from training).
from open-solution-mapping-challenge.
Related Issues (20)
- File b'data/meta/metadata.csv' does not exist: b'data/meta/metadata.csv' HOT 1
- AttributeError: 'StdOutWithUpload' object has no attribute 'fileno' HOT 1
- where to get Original Dataset? CrowdAi had been shut down HOT 3
- transformer aren't generate HOT 2
- Why droping small masks on the edge works HOT 1
- Dataset cant' be reachable anymore HOT 4
- Using model weights on own dataset HOT 26
- evaluate：valid data is none？
- Confused about generating target masks HOT 5
- Error when running Evaluate : axis 1 is out of bounds for array of dimension 0 HOT 21
- Use the Mapping-Challenge-weights to predict on my own data HOT 17
- KeyError: 'inference' when applying solution weight to my data HOT 11
- Transfer learning using the available weights
- FileNotFoundError: [Errno 2] No such file or directory: 'data/meta\\masks_overlayed_eroded_0_dilated_0\\train\\masks\\000000150992 HOT 3
- Pip subprocess error related to pycocotools when running 'source Makefile' HOT 2
- Adjusting 'Confidence' when Predicting on New Data
- The runtime encountered a problem HOT 1
- Segment Mask not visible on custom data
- Model weights for the winning solution is not available!
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