Yalantis/uCrop · error · CImgArgumentException

[" cimg_appname "_math_parser] CImg<%s>::%s: %s: Input vecto

Error message

[" cimg_appname "_math_parser] CImg<%s>::%s: %s: Input vector size (%lu values) and its specified geometry (%u,%u,%u,%u) (%lu values) do not match.

What it means

The math parser allows assigning an explicit geometry (width,height,depth,spectrum) to a vector. This error is thrown when the product of the four specified dimensions does not equal the actual number of values in the input vector (max(1,p1)), i.e. the declared shape and the data size disagree.

Source

Thrown at ucrop/src/main/jni/CImg.h:22589

              s2 = ++s1; while (s2<se1 && (*s2!=',' || level[s2 - expr._data]!=clevel1)) ++s2;
              arg4 = compile(s1,s2,depth1,0,block_flags);
              s1 = ++s2; while (s1<se1 && (*s1!=',' || level[s1 - expr._data]!=clevel1)) ++s1;
              arg5 = compile(s2,s1,depth1,0,block_flags);
              arg6 = compile(++s1,se1,depth1,0,block_flags);
              _cimg_mp_check_type(arg1,1,2,0);
              _cimg_mp_check_const_scalar(arg2,2,3);
              _cimg_mp_check_const_scalar(arg3,3,3);
              _cimg_mp_check_const_scalar(arg4,4,3);
              _cimg_mp_check_const_scalar(arg5,5,3);
              p1 = size(arg1);
              p2 = size(arg6);
              arg2 = (unsigned int)mem[arg2];
              arg3 = (unsigned int)mem[arg3];
              arg4 = (unsigned int)mem[arg4];
              arg5 = (unsigned int)mem[arg5];
              if (arg2*arg3*arg4*arg5!=std::max(1U,p1)) {
                _cimg_mp_strerr;
                throw CImgArgumentException("[" cimg_appname "_math_parser] "
                                            "CImg<%s>::%s: %s: Input vector size (%lu values) and its specified "
                                            "geometry (%u,%u,%u,%u) (%lu values) do not match.",
                                            pixel_type(),_cimg_mp_calling_function,s_op,
                                            std::max(p1,1U),arg2,arg3,arg4,arg5,(ulongT)arg2*arg3*arg4*arg5);
              }
              pos = vector(arg2*arg3*arg4*arg5);
              CImg<ulongT>::vector((ulongT)mp_mirror,pos,arg1,arg2,arg3,arg4,arg5,arg6,p2).move_to(code);
              return_comp = true;
              _cimg_mp_return(pos);
            }

            if (!std::strncmp(ss,"mproj(",6)) { // Project matrix onto dictionary
              _cimg_mp_op("Function 'mproj()'");
              s1 = ss6; while (s1<se1 && (*s1!=',' || level[s1 - expr._data]!=clevel1)) ++s1;
              arg1 = compile(ss6,s1,depth1,0,block_flags); // S
              s2 = ++s1; while (s2<se1 && (*s2!=',' || level[s2 - expr._data]!=clevel1)) ++s2;
              arg2 = compile(s1,s2,depth1,0,block_flags); // ncolS
              s1 = ++s2; while (s1<se1 && (*s1!=',' || level[s1 - expr._data]!=clevel1)) ++s1;

View on GitHub (pinned to f788b534b4)

Solutions

Compute w*h*d*s and compare against the actual vector size; fix the wrong dimension
Use size(#ind) in a debug print to confirm the real element count
Let the parser infer geometry by omitting explicit dims when possible
Reshape the data first (e.g. with 'resize' or 'unroll') so the count matches

Example fix

// before (12 values declared as 3,4,1,1 = 12? no, declared 3,4,2,1=24)
V = vector([1,2,3,4,5,6,7,8,9,10,11,12],3,4,2,1)
// after
V = vector([1,2,3,4,5,6,7,8,9,10,11,12],3,4,1,1)

Defensive patterns

Strategy: validation

Validate before calling

w*h*d*s == max(1,size(vec)) || error "geometry mismatch"

Try / catch

try { run(expr) } catch (CImgArgumentException &e) { log(e.what()); }

Prevention

Compute geometry product before hardcoding dims
Account for the spectrum/channel dimension
Prefer ops that infer geometry over explicit dims

When it happens

Trigger: Calling an expression like 'vector(v,w,h,d,s)' or a geometry-specifying op where w*h*d*s != vector length; typical with 'resize(#ind,...)' style ops or explicit vector declarations with wrong dimension values.

Common situations: Hardcoded geometry constants left over from an older image size, off-by-one in width/height, or forgetting the spectrum/channel factor (e.g. RGB vs gray).

Understand the failure class

Background: Tensor shape mismatch errors ("must have shape", "expected shape ... got ..."): when tensor dimensions disagree with what an op or layer was told to expect — this error's family across 6 libraries.

Related errors

AI-assisted analysis of Yalantis/uCrop@f788b534b4 (2026-09-08). Data as JSON: /api/errors/b12936667020cf2d. Report an issue: GitHub.