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Error! The command "tesseract" was not found. (PHP thiagoalessio)


Error! The command "tesseract" was not found. (PHP thiagoalessio)

By : Eamonn
Date : October 17 2020, 08:10 PM
hop of those help? Youre just trying to define the image path? See
code :
 $ocr = new TesseractOCR();
 $ocr->image('uploads/img.jpg');
 $ocr->run();


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Variable "not found in list of covariates" error in Stata when using the "margins" command

Variable "not found in list of covariates" error in Stata when using the "margins" command


By : SidHandsome
Date : March 29 2020, 07:55 AM
Hope this helps Can you reproduce the error with public data set? Here's my attempt (with factor variable solution at the bottom):
code :
. use http://www.stata-press.com/data/r13/union
(NLS Women 14-24 in 1968)

. xtlogit union age grade not_smsa south##c.year

Fitting comparison model:

Iteration 0:   log likelihood =  -13864.23  
Iteration 1:   log likelihood = -13547.326  
Iteration 2:   log likelihood = -13542.493  
Iteration 3:   log likelihood =  -13542.49  
Iteration 4:   log likelihood =  -13542.49  

Fitting full model:

tau =  0.0     log likelihood =  -13542.49
tau =  0.1     log likelihood = -12923.751
tau =  0.2     log likelihood = -12417.651
tau =  0.3     log likelihood = -12001.665
tau =  0.4     log likelihood = -11655.586
tau =  0.5     log likelihood = -11366.441
tau =  0.6     log likelihood = -11128.749
tau =  0.7     log likelihood = -10946.399
tau =  0.8     log likelihood = -10844.833

Iteration 0:   log likelihood = -10946.488  
Iteration 1:   log likelihood =  -10557.39  
Iteration 2:   log likelihood = -10540.493  
Iteration 3:   log likelihood = -10540.274  
Iteration 4:   log likelihood = -10540.274  (backed up)
Iteration 5:   log likelihood = -10540.274  

Random-effects logistic regression              Number of obs      =     26200
Group variable: idcode                          Number of groups   =      4434

Random effects u_i ~ Gaussian                   Obs per group: min =         1
                                                               avg =       5.9
                                                               max =        12

Integration method: mvaghermite                 Integration points =        12

                                                Wald chi2(6)       =    227.46
Log likelihood  = -10540.274                    Prob > chi2        =    0.0000

------------------------------------------------------------------------------
       union |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         age |   .0156732   .0149895     1.05   0.296    -.0137056     .045052
       grade |   .0870851   .0176476     4.93   0.000     .0524965    .1216738
    not_smsa |  -.2511884   .0823508    -3.05   0.002    -.4125929   -.0897839
     1.south |  -2.839112   .6413116    -4.43   0.000    -4.096059   -1.582164
        year |  -.0068604   .0156575    -0.44   0.661    -.0375486    .0238277
             |
south#c.year |
          1  |   .0238506   .0079732     2.99   0.003     .0082235    .0394777
             |
       _cons |  -3.009365   .8414963    -3.58   0.000    -4.658667   -1.360062
-------------+----------------------------------------------------------------
    /lnsig2u |   1.749366   .0470017                      1.657245    1.841488
-------------+----------------------------------------------------------------
     sigma_u |   2.398116   .0563577                      2.290162    2.511158
         rho |   .6361098   .0108797                      .6145307    .6571548
------------------------------------------------------------------------------
Likelihood-ratio test of rho=0: chibar2(01) =  6004.43 Prob >= chibar2 = 0.000

. margins not_smsa, at(age=(10(5)20))
'not_smsa' not found in list of covariates
r(322);

. xtlogit union age grade i.not_smsa i.south##c.year

Fitting comparison model:

Iteration 0:   log likelihood =  -13864.23  
Iteration 1:   log likelihood = -13547.326  
Iteration 2:   log likelihood = -13542.493  
Iteration 3:   log likelihood =  -13542.49  
Iteration 4:   log likelihood =  -13542.49  

Fitting full model:

tau =  0.0     log likelihood =  -13542.49
tau =  0.1     log likelihood = -12923.751
tau =  0.2     log likelihood = -12417.651
tau =  0.3     log likelihood = -12001.665
tau =  0.4     log likelihood = -11655.586
tau =  0.5     log likelihood = -11366.441
tau =  0.6     log likelihood = -11128.749
tau =  0.7     log likelihood = -10946.399
tau =  0.8     log likelihood = -10844.833

Iteration 0:   log likelihood = -10946.488  
Iteration 1:   log likelihood =  -10557.39  
Iteration 2:   log likelihood = -10540.493  
Iteration 3:   log likelihood = -10540.274  
Iteration 4:   log likelihood = -10540.274  (backed up)
Iteration 5:   log likelihood = -10540.274  

Random-effects logistic regression              Number of obs      =     26200
Group variable: idcode                          Number of groups   =      4434

Random effects u_i ~ Gaussian                   Obs per group: min =         1
                                                               avg =       5.9
                                                               max =        12

Integration method: mvaghermite                 Integration points =        12

                                                Wald chi2(6)       =    227.46
Log likelihood  = -10540.274                    Prob > chi2        =    0.0000

------------------------------------------------------------------------------
       union |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         age |   .0156732   .0149895     1.05   0.296    -.0137056     .045052
       grade |   .0870851   .0176476     4.93   0.000     .0524965    .1216738
  1.not_smsa |  -.2511884   .0823508    -3.05   0.002    -.4125929   -.0897839
     1.south |  -2.839112   .6413116    -4.43   0.000    -4.096059   -1.582164
        year |  -.0068604   .0156575    -0.44   0.661    -.0375486    .0238277
             |
south#c.year |
          1  |   .0238506   .0079732     2.99   0.003     .0082235    .0394777
             |
       _cons |  -3.009365   .8414963    -3.58   0.000    -4.658667   -1.360062
-------------+----------------------------------------------------------------
    /lnsig2u |   1.749366   .0470017                      1.657245    1.841488
-------------+----------------------------------------------------------------
     sigma_u |   2.398116   .0563577                      2.290162    2.511158
         rho |   .6361098   .0108797                      .6145307    .6571548
------------------------------------------------------------------------------
Likelihood-ratio test of rho=0: chibar2(01) =  6004.43 Prob >= chibar2 = 0.000


. margins not_smsa, at(age=(10(5)20))

Predictive margins                                Number of obs   =      26200
Model VCE    : OIM

Expression   : Linear prediction, predict()

1._at        : age             =          10

2._at        : age             =          15

3._at        : age             =          20

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
_at#not_smsa |
        1 0  |  -2.674903   .3107206    -8.61   0.000    -3.283905   -2.065902
        1 1  |  -2.926092   .3148551    -9.29   0.000    -3.543196   -2.308987
        2 0  |  -2.596538   .2375601   -10.93   0.000    -3.062147   -2.130928
        2 1  |  -2.847726   .2432156   -11.71   0.000     -3.32442   -2.371032
        3 0  |  -2.518172   .1660016   -15.17   0.000    -2.843529   -2.192814
        3 1  |   -2.76936   .1743793   -15.88   0.000    -3.111137   -2.427583
------------------------------------------------------------------------------
java tesseract error in linux "Unable to load library 'tesseract': libtesseract.so"

java tesseract error in linux "Unable to load library 'tesseract': libtesseract.so"


By : Rhonda
Date : March 29 2020, 07:55 AM
it helps some times On Linux, Tess4J calls on Tesseract native library libtesseract.so to work. If you can't build or install Tesseract on Linux, you're in tough luck. Maybe if you can cross-compile to a .so on Windows using Cygwin or Mingw.
Error: -:Command not found, After running command "echo 'rvm_path="$HOME/.rvm"' >> ~/.rvmrc –"

Error: -:Command not found, After running command "echo 'rvm_path="$HOME/.rvm"' >> ~/.rvmrc –"


By : Bobby
Date : March 29 2020, 07:55 AM
it helps some times I am getting this error after i have executed this command , just remove the file:
code :
rm -f /home/abhinay/.rvmrc
GNU Parallel in BASH script with "export -f <func>" failed with "Command Not Found" error when

GNU Parallel in BASH script with "export -f <func>" failed with "Command Not Found" error when


By : user2990039
Date : March 29 2020, 07:55 AM
Hope that helps Congratulations. You've been shell-shocked.
You have two versions of bash installed on your system:
code :
export SHELL=/usr/software/bin/bash
# ...
/u/jsung/bin/parallel -j 0 --wd . --env ndmpcopy_cron_parallel --eta ndmpcopy_cron_parallel ::: local
SHELL=/usr/software/bin/bash /u/jsung/bin/parallel -j 0 --wd . --env ndmpcopy_cron_parallel --eta ndmpcopy_cron_parallel ::: local
In Mac terminal, why does this code give me "command not found", "syntax error near unexpected token"

In Mac terminal, why does this code give me "command not found", "syntax error near unexpected token"


By : zheng zhou
Date : March 29 2020, 07:55 AM
Does that help You need to respect spaces in bash scripts like @Jonny Henly said. Here is a modified version of your code, try it and see if it works.
code :
read command;

if [ $command = "make" ]
then
    echo "Hello"
elif [ $command = "make run" ]
then 
    echo "Goodbye"
fi
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