Comments (4)
I do not think that it will work. You may just retrain the model, it would be much faster. Data is available at the Kaggle website.
We worked on this problem more than a year ago. Everything is changing so fast. There are much better ways to perform segmentation for satellite images.
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I want to implement your pre-trained model of DSTL competition only on RGB images. I don't have data set of other band images for my satellite imagery application. Is it possible to test only RGB images using your pre-trained model?
Hello! Do you have solve your problem ?
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Bonjour! Do you have solve your problem ?
Thanks for your time sir. If possible, kindly share some links where we can get pre-trained models or any other usefull help regarding segmentation for satellite images. I will be very thankful to you. Regards Zain ul Abideen Software Developer
…
On Mon, May 21, 2018 at 9:56 PM, Vladimir Iglovikov < @.***> wrote: I do not think that it will work. You may just retrain the model, it would be much faster. Data is available at the Kaggle website. We worked on this problem more than a year ago. Everything is changing so fast. There are much better ways to perform segmentation for satellite images. — You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub <#15 (comment)>, or mute the thread https://github.com/notifications/unsubscribe-auth/Ak5cIjC4UUNqGsOUeE3BrzEXtSwJgyq0ks5t0vHagaJpZM4ThfOX .
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Related Issues (20)
- Using real coordinates
- h5py.File doesn't have compression as argument? HOT 1
- Training at once for all classes HOT 1
- output of generator should be a tuple (x, y, sample_weight) or (x, y). Found: None HOT 3
- ValueError: "concat" mode can only merge layers with matching output shapes except for the concat axis. Layer shapes: [(None, 1024, 14, 7), (None, 256, 14, 14)] HOT 2
- Object detection question HOT 1
- TypeError: 'compression_opts' is an invalid keyword argument for this function(cache_train.py) HOT 1
- Running visualize error HOT 1
- How can I label my own images? HOT 1
- Thanks so much HOT 1
- How can I make this code work with images of 3 bands only? HOT 3
- why loss go up?
- model issue
- TypeError: 'compression' is an invalid keyword argument for this function HOT 2
- ValueError: "concat" mode can only merge layers with matching output shapes except for the concat axis. Layer shapes: [(None, 2, 14, 512), (None, 2, 14, 256)] HOT 7
- Reproducing Results Problem HOT 1
- make prediction on buildings is failing HOT 5
- Running code only with RGB images HOT 3
- Dimension of the traning set images HOT 1
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