how to convert data which is saved as cell should be converted into double type how to do it?

I have extracted Image names means I have separated the image names and extensions and saved in an array. now i should convert those names into numbers.If I have converted those names into numbers I can concatenate th0se names at the end column of the database.

iam attaching my code below... plz help

load('Image_names.mat');

for i=1:size(Image_names);

[~,name{i}]=fileparts(Image_names{i});

Imagename=name';

end

[Walter Roberson]

str2double(imagename) possibly. It would have been easier if you had posted the text version of one of the names.

[hp]

thank you it works.. using fileparts() we can get the image name and extension separately

Answer 1

[Stephen23]

An explicit loop is not required to use fileparts with a cell array:

[P,N] = cellfun(@fileparts,Imagename,'uni',0)

But note that none of the character vectors in your sample cell array contain paths:

>> load('Imagename.mat')
>> [P,N] = cellfun(@fileparts,Imagename,'uni',0);
>> all(cellfun(@isempty,P))
ans = 1
>> isequal(Imagename,N)
ans = 1

"how to convert data which is saved as cell should be converted into double type how to do it?"

Using str2double:

>> vec = str2double(Imagename)
vec =
 Columns 1 through 23:
   1594   1595   1596   1597   1598   1599   1600   1601   1602   1603   1604   1605   1606   1607   1608   1609   1610   1611   1612   1613   1614   1615   1616
 Columns 24 through 46:
   1617   1618   1619   1620   1621   1622   1623   1624   1625   1626   1627   1628   1629   1630   1631   1632   1633   1634   1635   1636   1637   1638   1639
 Columns 47 through 69:
   1640   1641   1642   1643   1644   1645   1646   1647   1648   1649   1650   1651   1652   1653   1654   1655   1656   1657   1658   1659   1660   1661   1662
 Columns 70 through 92:
   1663   1664   1665   1666   1667   1668   1669   1670   1671   1672   1673   1674   1675   1676   1677   1678   1679   1680   1681   1682   1683   1684   1685
 Columns 93 through 115:
   1686   1687   1688   1689   1690   1691   1692   1694   2657   2658   2659   2660   2661   2662   2663   2664   2665   2666   2667   2668   2669   2670   2671
 Columns 116 through 138:
   2672   2673   2674   2675   2676   2677   2678   2679   2680   2681   2682   2683   2684   2685   2686   2687   2688   2689   2690   2691   2692   2693   2694
 Columns 139 through 161:
   2695   2696   2697   2698   2699   2700   2701   2702   2703   2704   2705   2706   2707   2708   2709   2710   2711   2712   2713   2714   2715   2716   2717
 Columns 162 through 184:
   2718   2719   2720   2721   2722   2723   2724   2725   2726   2727   2728   2729   2730   2731   2732   2733   2734   2735   2736   2737   2738   2739   2740
 Columns 185 through 207:
   2741   2742   2743   2744   2745   2746   2747   2748   2749   2750   2751   2752   2753   2754   2755   2766   9031   9032   9034   9035   9037   9038   9039
 Columns 208 through 230:
   9040   9041   9042   9044   9045   9046   9047   9048   9049   9050   9051   9052   9053   9054   9055   9056   9057   9058   9059   9060   9061   9062   9063
 Columns 231 through 253:
   9064   9065   9066   9067   9068   9069   9070   9071   9072   9073   9074   9075   9076   9077   9078   9079   9080   9081   9082   9083   9084   9085   9086
 Columns 254 through 276:
   9087   9088   9089   9090   9091   9092   9093   9094   9095   9096   9097   9098   9099   9100   9101   9102   9103   9104   9105   9106   9107   9108   9109
 Columns 277 through 299:
   9110   9111   9112   9113   9114   9115   9116   9117   9118   9119   9120   9121   9122   9123   9124   9125   9126   9127   9128   9129   9130   9131   9132
 Columns 300 through 322:
   9133    800    801    802    803    804    805    806    807    808    809    810    811    812    813    814    815    816    817    818    819    820    821
 Columns 323 through 345:
    822    823    824    825    826    827    828    829    830    831    832    833    834    835    836    837    838    839    840    841    842    843    844
 Columns 346 through 368:
    845    846    847    848    849    850    851    852    853    854    855    856    857    858    859    860    861    862    863    864    865    866    867
 Columns 369 through 391:
    868    869    870    871    872    873    874    875    876    877    878    879    880    881    882    883    884    885    886    887    888    889    890
 Columns 392 through 414:
    891    892    893    894    895    896    897    898   9283    700    701    702    703    704    705    706    707    708    709    710    711    712    713
 Columns 415 through 437:
    714    715    716    717    718    719    720    721    722    723    724    725    726    727    728    729    730    731    732    733    734    735    736
 Columns 438 through 460:
    737    738    739    740    741    742    743    744    745    746    747    748    749    750    751    752    753    754    755    756    757    758    759
 Columns 461 through 483:
    760    761    762    763    764    765    766    767    768    769    770    771    772    773    774    775    776    777    778    779    780    781    782
 Columns 484 through 500:
    783    784    785    786    787    788    789    790    791    792    793    794    795    796    797    798    799
>> class(vec)
ans = double
>> size(vec)
ans =
     1   500