Hi Paul,
If the background is relatively uniform:
Then a simple algorithm could be used, to distinguish foreground from
background points.
Essentially, returning a logical matrix.
Otherwise, I'm assuming that suitable pooling/convolution operations
could be used for this purpose.
Then you could
Rui
Actually yes. I was able to work this into my shiny app this afternoon.
Thank you
Jeff
-Original Message-
From: Rui Barradas
Sent: Sunday, February 28, 2021 5:26 AM
To: reichm...@sbcglobal.net; R-help@r-project.org
Subject: Re: [R] Making model predictions
Hello,
Are you looki
Hello Paul Bernal,
(sorry, forgot to CC)
Re:
> Does anyone know about any package for image processing, for example, to
> calculate body mass index pased on a picture, silouette or image.
This sounds more like a job for the image analysis program NIH Image (the
Java-version "ImageJ" being a
I am sure you can get more done with a caret than a stick. I need a stick for
another problem, though.
A serious question. I somehow upset my R/RSTUDIO setup while trying to see why
a markdown only allowed me to save an HTML version, not PDF and DOC as it used
to. It now fails on any such docum
Hi Paul,
The paper doesn't seem to mention R and the journal doesn't inspire
confidence, but the formulas provided give you a start:
https://www.researchgate.net/publication/280133090_Calculation_of_Body_Mass_Index_using_Image_Processing_Techniques
Jim
On Mon, Mar 1, 2021 at 3:39 AM Paul Bernal
On Sun, Feb 28, 2021, 17:49 Paul Bernal wrote:
> Hello everyone,
>
> Is there a way to calculate volume and area of an image with R?
How can an image have a volume or an area?
I think you need to be more specific.
Regards
Martin
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__
Thanks, I'll check it out.
On Sun, 28 Feb, 2021, 1:37 AM John Kane, wrote:
> The "confusionMatrix" function appears to be from the 'caret' package.
> Have you loaded 'caret' with the library(caret) command?
>
> On Sat, 27 Feb 2021 at 14:20, Kishor raut wrote:
>
>> Respected Sir,
>>
>> I Mr Kish
1) doing a web search on:
"R package to calculate body mass index based on a picture, silhouette or
image"
did *not* bring up any R packages, but did provide what looked like
relevant links to other software and research/discussions. You can decide
whether or not this is useful "guidance" (if you
Hello everyone,
Is there a way to calculate volume and area of an image with R?
Any guidance will be greatly appreciated.
Best regards,
Paul
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Hello everyone,
Does anyone know about any package for image processing, for example, to
calculate body mass index pased on a picture, silouette or image.
Any guidance will be greatly appreciated.
Best regards,
Paul
[[alternative HTML version deleted]]
Oh
find ~ -name .Rhistory 2>/dev/null
shows 12 file :-)-O
vriendelijke groeten/sincères amitiés,
el
On 2021-02-28 17:17 , Mahmood Naderan-Tahan wrote:
> OK. It seems that it depends on where R is launched.
>
> In my case, I found .Rhistory file in ~/Documents.
>
>
> Regards,
> Mahm
OK. It seems that it depends on where R is launched.
In my case, I found .Rhistory file in ~/Documents.
Regards,
Mahmood
From: R-help on behalf of Dr Eberhard W Lisse
Sent: Sunday, February 28, 2021 4:06:26 PM
To: r-help@r-project.org
Subject: Re: [R] Command
On the Mac it is ~/.Rhistory
el
On 2021-02-28 15:39 , Mahmood Naderan-Tahan wrote:
> Hi
>
> May I know where is the location of commands we used in R in the history?
>
>
> Regards,
> Mahmood--
Dr. Eberhard W. Lisse \ / Obstetrician & Gynaecologist
e...@lisse.na / *
I think it may depend on your operating system. In my case, Ubuntu 20.10,
it is a hidden file at /home level.
On Sun, 28 Feb 2021 at 08:40, Mahmood Naderan-Tahan <
mahmood.nade...@ugent.be> wrote:
> Hi
>
> May I know where is the location of commands we used in R in the history?
>
>
> Regards,
>
Hi
May I know where is the location of commands we used in R in the history?
Regards,
Mahmood
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Hello,
Are you looking for this?
newd <- data.frame(
Class = '1st',
Sex = 'Male',
Age = 'Child'
)
predict(m, newdata = newd, type = 'raw')
#No Yes
#[1,] 0.3169345 0.6830655
With the default type = 'class' the result is
predict(m, newdata = newd)
#[1] Yes
#Levels: No Y
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