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Hello there:)
First of all, thank you for sharing this research.
I finished demo Train and Test using your DEL algorithm.
I have some few question.
1. What is role of the images in folder 'supe…
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The purpose of this tool is to make labeling as easy and fast as possible.
Initial ideas:
- Use pre-labeled images from Yolo v2;
- Video Object Tracking;
- Feature Matching + Homography;
- Sup…
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Hi,
I try to train my model without superpixel planar regularization. But it's likely that the training collapses and the output is all-zero. Have you faced and managed to solve this problem?
Th…
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An agglomeration can be represented as a forest structure (single tree if the agglomeration proceeds to completion) in which each leaf is a superpixel, and inner nodes are the products of agglomeratin…
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When we specify 100 superpixels, this code cannot run for many images in BSDS500:
e.g.
100039.jpg, 101027.jpg, 107045.jpg, .....
ahban updated
5 years ago
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Hi, thanks for your work.
if no boundary perceiving loss is used, will the result keep the clear edge and show superpixel clustering in semantic segmentaion task?
do you think this method work well …
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I used to use scanpy python package for down-stream analysis.
I wonder how the predicted gene expressions can be analyzed in Anndata (Scanpy).
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Object tracking based on a point annotation uses a fixed radius for the initial box that is used for tracking. This is not ideal for most cases. Maybe we should remove object tracking for point annota…
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**Time estimate:** 10 hours
**Deadline:** N/A
**Description of task:**
It would be beneficial to apply a type of segmentation on the RGB data for easier HSV filtering afterwards. Clustering me…
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## Describe the bug
Right now one has to supply a boundary probability map even if one does not plan to use it for superpixel generation (superpixels generated outside ilastik) and calculating …