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[Lecture 3_Autoencoder]
Q - The concept of superpixels has been introduced as an example of blobs. Superpixels are the most advanced version of blobs, but I want to know about the difference between …
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Does the file named compute_spixels.py generate superpixels and the file named compute_segment.py generate segmentation?
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Instead of implementing k-means clustering on the pixels of an image itself, it is **far more efficient** to cluster the image in superpixels first and operate on those in further steps.
I found a …
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When I use your code to generate superpixels, I meet the following problem:
I use …
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I have tried it for some medical images which are a bit larger than standard computer vision images and then the processing takes significantly longer time and on the other hand, setting larger step m…
Borda updated
5 years ago
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I could not train properly. I used opencv-python3.4.0.14 to Extract the superpixels and line segments, but the problem still occurred.
Training model named:
mdp
Models and tensorboard events f…
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Add an imputer that works for images. This imputer should automatically detect superpixels in the image and use these as players for the approximators.
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Thank you for sharing your work. I have a question about the overlap folder. How do you generate the overlaps between superpixels and save it in the coverage_superpixel folder? Thanks.
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Hello,
When running the code, I find there is a bug from main_superpixels_contrastive.py.
It reports as follows:
![image](https://user-images.githubusercontent.com/15103490/113104134-c2411f80-9232-…
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Thanks for sharing. Recently, using your code, I generated the superpixels with SEEM. Then I pre-trained the 3D backbone with SLidR with the new superpixels. However, the performance is not as good as…