Lately, I was understanding what exactly buffering is. And I read that cout is buffered. So I got confused. What does it mean that cout is buffered? In general, what does it mean when someone says that something is buffered? And what does flushing the streams(cout/buffer) mean?
Any example tagged with the answer would be appreciated :)
Here's a related post:
Is std::cout buffered?
And here's an article that talks about it in more detail:
https://www.programmingincpp.com/flush-the-output-stream-buffer.html
Related
In this twitter thread https://twitter.com/jlowin/status/1061085224862433280, Jeremiah says that the author makes the error of echoing in this article https://heartbeat.fritz.ai/using-a-keras-long-shortterm-memory-lstm-model-to-predict-stock-prices-a08c9f69aa74
"3/6 The echo is the result of a model collapsing in a fit of maximum worthlessness. The model is saying, "My best guess is that tomorrow is pretty much going to be like today," or x_t+1 ≈ x_t. You don't need an AI for that. You barely need a calculator."
Whats wrong with the author model? how should he have done to avoid echo?
Thanks
Basically organizes the content based on the speaker?
Excerpt From: Robert Louis Stevenson. “The Strange Case of Dr. Jekyll and Mr. Hyde.”
Example Input:
But Lanyon's face changed, and he held up a trembling hand. "I wish to see or hear no more of Dr. Jekyll," he said in a loud, unsteady voice. "I am quite done with that person; and I beg that you will spare me any allusion to one whom I regard as dead.
Example Output:
[
“Narrator”: “But Lanyon's face changed, and he held up a trembling hand.”,
“Lanyon”: “I wish to see or hear no more of Dr. Jekyll”,
“Narrator”: “he said in a loud, unsteady voice.”,
“Lanyon”: “I am quite done with that person; and I beg that you will spare me any allusion to one whom I regard as dead.”
]
I have not heard of the algorithm that does exactly this. But there are two well known problem that could be useful: named entity recognition (to find all potential speakers) and anaphora resolution (to decide who "he" or "she" is in each case).
You would also need to train a classifier that for each quoted chunk of text to decide whether it is a direct speech. And you would probably need another classifier to decide for each identified piece of speech and for each identified speaker in the context, how likely is that this speech actually belongs to this speaker.
I am working on post processing of disparity map.
My disparity image, even though it is WLS filtered, has too many 'holes'.
This is what i get for now. Rectified, but in fish eye way. Anyway rectified for sure, but have many holes. Disparity matching algorithm is SGBM. WLS filter sigma is 2.1, lambda is 30000. Black regions are holes.
I am referring official opencv site which says Disparity map post-filtering and it is using DisparityWLSFilter extensively. But I wonder how it works internally and want to read theoretical paper regarding this implementation. I want to know what Sigma and Lambda does, and how it will filter my image.
And, is there any other good disparity filter that i can use? WLS filter cannot fill the 'holes' effectively. Or, any algorithm that is easy to use or easy to implement, or library that is not GPL?
Self reply.
Got answer from Opencv.
Orig question is HERE.
Reply says
References have been added here, documentation reference
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Check out the comments here, and the code here. That should answer some of your questions. To see how the code author has come up with this method perhaps should contact him directly as there is no reference for that in the code comments.
I'm having some issues regarding a conjoint analysis. Excuse me if some of the terms I use are wrong, but it has been some time since I last worked with SPSS - and my teacher was Danish.
Task object
I am to make a series of concept travelpackages (attributes and attribute notes/levels).
This far I've got things under control - I've reduced the number of packages from 81 to 9, with the help of 'orthogonal' design.
These 9 packages have been rated by some people (1-10), on a questionnaire.
Then I've been asked to write a syntax which evaluates my conjoint plan:
CONJOINT PLAN= 'C:\Users\MYNAME\DROBBOXFOLDER\Conjoint_cards.SAV'
/DATA='C:\Users\MYNAME\DROBBOXFOLDER\Respondents.SAV'
/SCORE=Card_1 TO Card_9
/SUBJECT=ID
/FACTORS= SMS Minutter Data Tryghed
/PRINT=ALL
/PLOT=ALL.
However I keep getting this error:
SUBJECT SUBCOMMAND -- Subject variable is not on data file.
Execution of this command stops.
At this point I've been to the dark pages of Google and back for an answer to what I am doing wrong, but nothing so far. The answer is probably staring me in the face. But I will appreciate any help or pointers as to what I'm doing wrong.
Problem solved:
So apparently one shouldn't follow a guide to the letter. My datafile didn't contain a ID, so removing this from my syntax solved the problem.
How can I define (statistically) quality of image matching (area-based, feature-based ) between two images.
'If its wrong forum to ask such conceptual questions , please guide me to other forum'.
Thanx and regards,
You should probably look at the cross-correlation between the images.