Comments (7)
Hi @tiusty,
I am also just figuring out how to use this tool, but figured I would chime in with what I have found out.
I am fairly sure by using 'convert' you are not providing the crs or any location information. The tif file should actually be a geotiff. Take a look at osgeo gdal translate, you'll need to provide the output bounds and the crs.
https://gdal.org/python/osgeo.gdal-module.html#Translate
You can check if your tiff is referenced correctly by importing it into QGIS and using it as a layer. The image should line up with another map.
Hope that helps.
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Hi @tiusty,
If your single .tif image is small enough to run in a reasonable amount of time on the front end, then you can define a polygon layer that simply contains the extent of the tif and run "Download" on it through the web interface.
If it is much larger, or you want to interact with your model programmatically, then you can save a checkpoint, and use that ModelSession object as a normal class in a jupyter notebook.
Happy to explain more in-depth if these don't make sense!
Best,
Caleb
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Thanks for the response!
I will give that a try tomorrow and let you know how it goes.
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Hi @calebrob6,
I am taking approach 1 for now.
Let me know if I am taking the right approach or not.
Lets say I have the following png file.
I converted it to a tif file on Ubuntu by running
convert image2.png image2.tif
Then I update the dataset of the HCMC dataset with:
Now the image shown by the localhost still appears like HCMC
But when I shift click to apply segmentation it seems to load the new image underneath when actual computing the segmentation but it fails.
The first issue was when the .tif file was loaded, the f.crs was not populated. To see if that was the only issue, I hardcoded to the value from the HCMC tif file.
Then after that I tried again but now run into the next issue:
Therefore maybe the format of my tif file is not proper since I just converted it from a png directly?
Wonder if you have any thoughts.
Thanks!
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Hi @richard-mackie,
Thanks for the info.
I downloaded QGIS and used the georeferencer to convert to the png into to a geotiff. I was able to get segmentation results from the image after that.
This may not exist but wondering if @calebrob6 has a comment on this:
Not sure if this functionality exists but the reason why just being able to pass a single png image to the frontend without needing to convert to geotiff and also loading a basemap with the associated layers is because my use case involves integrating with Airsim.
Therefore generating a basemap with the associated layers and also producing a geotiff is not super relevant. My understanding is that the geotiff is needed to be able to produce predictions for the inference window so you are not producing a prediction of the whole image.
@calebrob6 mentioned a way to define a single image as a polygon layer and then perhaps if then image can be interacted, i.e set sample points to retrain and then do a prediction on the extent of the image, that would be great. Otherwise this would probably be a feature request which would probably be outside of the use case of the Microsoft Land Cover.
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from landcover.
Hi @calebrob6,
No worries at all. Hope you had a good vacation.
That would be super useful if possible.
If you want feel free to ping me here if you decide to go forward with this/when you are able to complete it. Otherwise I will check back in periodically.
Thanks!
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Related Issues (14)
- Error when loading the model naip_demo HOT 1
- Map shows, but can't select a region. HOT 7
- Question: Custom NAIP Datasets HOT 3
- Is there a tutorial available for the demo? HOT 1
- Session Handler- Tried to get a non-existing Session HOT 7
- Problem with Exporting Geotiff files when using ESRI maps HOT 2
- Problem with running inference on demo data HOT 10
- Missing segmentation_models_pytorch HOT 2
- This repo is missing a LICENSE file
- Demo model file? HOT 1
- This repo is missing important files
- Errors when running all datasets except the ESRI World Imagery HOT 7
- Cannot complete the installation HOT 2
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