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I'm successfully posting high scores to apple game center but when I view the game center leaderboard UI the data is odd and doesn't match. I am testing with 5 different game center accounts on 5 different devices, but the "All xxx Players" section of the leader board shows only two or three players per device instead of the expected 5. Other weird behaviour:
I see myself and one friend's score in the "Friends" area, but only myself and one other person (not my friend) in the "All 2 Players" area. Why don't I see my friend?
On another device, i correctly see myself and a (different) friend in the "Friends" area, but my friend has a different score (smaller) score when listed in the 'All 3 Players" area below.
I am in sandbox environment, if that matters, but I don't want to wait until prod to find there is something wrong. If it is simply stale data, is there any API call I should be doing to refresh this data?
EDIT: The above was the behaviour seen with Apple's reportScoreWithCompletionHandler() api.
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i am building a game tournament app in react js where each tournament having 4 players.
one player will create the game tournament and remaining three player will join the game.
In any condition game creator left the game then creator status should be assign to another three player.
How to build this login in mern stack
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Here I have an image of two objects/stars:
I have hundreds of images like this one, from NASA MAST Archive. (The corners are not stars, just errors, one star is on the top, the other one is on the bottom).
What algorithm should I use to determine the number of objects (in this case stars) in one picture? For a human, it is pretty obvious that there are two objects, but I want to implement this detection in Python.
For reference, here is a picture with one star only:
(The pictures are produced from FITS files with PyKE.)
You can apply a threshold and use open cv to analyze the number of connected components (groups).
For example :
import cv2
src = cv2.imread('/path/to/your/image')
ret, thresh = cv2.threshold(src,0,255,cv2.THRESH_BINARY+cv2.THRESH_OTSU)
connectivity = 8 #also diagonal neighbors, choose 4 if you want just horizontal and vertical neighbors.
# Analysis of the binary image
output = cv2.connectedComponentsWithStats(thresh, connectivity, cv2.CV_32S)
n_groups=output[2].max()
To get rid of the noises you can decide that you don't take into account groups with less than TH number of connected pixels (from the images you uploaded as an example I would choose something like TH=4).
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I am working on a project to pull out data from rally and create a velocity chart.
I understand the REST Web Service APIs to use are Defects, Iteration, Hierarchical requirement and Iteration cumulative flow data.
How are the calculations are done to calculate the velocity per iteration for a particular project?
What data is required and how can it be achieved? Right now I'm able to pull plan estimate of all accepted user stories and total plan estimate.
I wrote an app recently to calculate velocity. I used the story points of all accepted stories/defects in a time period (iteration/release). My numbers ended up matching what Rally had for my velocity, so I believe that is all it takes.
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I'm hoping to find a corpus of play-by-play style commentary* for an NLP project that involves predicting game outcomes from such commentary.
I can't shake the feeling that with the huge interest in chess within the A.I. community, there must've been some previous project involving using chess commentary for some similar purpose, but for I can't find one for the life of me.
I have found a few sites like Chess Games that claim to have written commentary for some of their games, but most don't and there appears to be no way to sort them by this property.
*By 'play-by-play style commentary' I mean anything involving the game at hand and nothing more. E.g. everything from "Kasparov moved his queen to b3, taking Deep Blue's pawn" to "Kasparov's poor opening has left his Knight vulnerable" but not things like "Kasparov played a similar move back in his 1996 game" or "Kasparov's hair looks particularly pretty today".
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I've bought an 11" and a 13" macbook air and borrowing a spyder3pro from my friend to calibrate the screens. I am trying out the macbook air's and returning one.
I'd like to calibrate both the screens and then also my home external lcd screen and my work external lcd screen.
Can i calibrate these external screens using 1 laptop and the spyder3pro and then copy over the profiles to the other macbook air? Does this work?
I don't really want to calibrate 1 day at work when i have the 13" and then again when i have the 11" with me.
It should be ok since the 11" and 13" have the same gpu... and probably the same display circuitry. It would still be optimal to calibrate each combination of pc/laptop/lcd to get the best possible results. Just copy the icc profile from the correct folder, and copy to the correct destination on the target pc : ICC Profile Locations
You're going to want to use the calibration on both machines, since there can be differences from chip to chip. Also remember that you're going to want to calibrate both machines on both screens, so you'll need four calibrations total. Unless, that is, you're going to try to calibrate your macbook screens as well, for some reason...