poor prediction in satellite images
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Description
Hi All,
I am able to get 0.83 of IOU using the Tanzania dataset using your code and able to generate vector files after predictions.
Now, I have a 50cm VHR image over an urban area and corresponding building shape files in geojson format. I applied the same techniques as in the Tanzania dataset and trained the model with an IOU of .67
But, generated segmentation probabilities do not look good, what can be the reason ?
I have used batch_size of 16, image_size of 512, lr= 0.00005 and loss function of Lovasz.
I will be happy to hear from you.
regards,
Jai
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Research direction
The issue mentions the Tanzania dataset, a 50cm VHR urban image, GeoJSON building shapes, and training parameters, but no repository file, test, or entry point. Start by comparing the dataset and training configuration with the project’s documented workflow; done would require identifying and reproducing the cause of the poor segmentation probabilities.
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Assessment
- Tech stack
- python
- Domain
- computer-vision, machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100