connected-components

I think the tags explain quite well my problem :) I've been trying to write a Gremlin traversal to compute the connected components of the simple graph described at the end of the post. I tried with g.V().repeat(both('e')).until(cyclicPath()).dedup().tree().by('name').next() obtaining ==>a={b={a={}, c={b={}}, d={c={d={}}}}, c={d={c={}}}} ==>e={f={e={}, g={f={}}}, h={f={h={}}}} ==>g={f={g={}}} which is bad, since the cyclicPath filter terminated the traversal starting from e before reaching g . Obviously, if I remove the until clause I get an infinite loop. Moreover, if I use simplePath the

I tried to run the following command in Neo4j however it gives the error Unknown function 'algo.getNodeById'. I am using Neo4j desktop (3.4.0) and I am running this command in Neo4j browser: CALL algo.unionFind.stream('', ':REL', {}) YIELD nodeId,setId RETURN algo.getNodeById(nodeId).id AS user, setId I want to find connected components (top10 maximum connected) in my graph. Any other solution which can help me visualize the connected component in the graph will also work Some of the older versions of algorithms don't have algo.getNodeById() included. If you can try to use the latest graph

So I have a single channel image that is mostly 0s (background), and some values for foreground pixels like 20, 21, 22. The nonzero foreground pixels are mostly clustered together with other foreground pixels with the same value. However, there is some noise in the image. To get rid of the noise, I want to use connected components analysis, and for each value (in this case 20, 21, 22), zero out everything but the largest connected component. So in the end, I will have 3 large connected components and no noise. How would I use cv2.connectedComponentsWithStats to accomplish this? It seems poorly

My table has account_id and device_id . One account_id could have multiple device_id s and vice versa. I am trying to count the depth of each connected many-to-many relationship. Ex: account_id | device_id 1 | 10 1 | 11 1 | 12 2 | 10 3 | 11 3 | 13 3 | 14 4 | 15 5 | 15 6 | 16 How do I construct a query that knows to combine accounts 1-3 together, 4-5 together, and leave 6 by itself? All 7 entries of accounts 1-3 should be grouped together because they all touched the same account_id or device_id at some point. I am trying to group them together and output the count. Account 1 was used on device

In OpenCV 3.0 there is a function called connectedComponent . I know that it takes as input a binary image and returns the labels and the number of connected components, but what algorithm is used internally? OpenCV is open source. You can look at the documentation and the source code . You can choose 2 algorithms to perform connected component lablelling : CCL_WU : Based on "Two Strategies to Speed up Connected Components Algorithms", the SAUF (Scan array union find) variant using decision trees, Kesheng Wu, et al . CCL_GRANA : Based on "Optimized Block-based Connected Components Labeling