unit formUnit; 
{$h+}

interface
uses onnxruntime_pas_api, onnxruntime, Classes etc... ;

var 
  session : TORTSession;
begin
  session := TORTSession.Create('./mymodel/filname.onnx'); 
{ 
*****************************************************************
    Check your model requirements for input/output 
    names and value dimensions before preparing the inputs.
    to explore the model before preparing use :
      session.GetInputCount and session.GetOutputCount
      session.GetInputName and session.GetOutputName
      session.GetInputTypeInfo and session.GetOutputTypeInfo
 ****************************************************************
}

var 
  x,y:integer;
  imageData : array of array of single;
  inTensor : TORTTensor<single> ; 
  inputs : TORTNameValueList  ;
begin
  // assuming the model input name is 'image' and the tensor shape is [width, height]
  inTensor := TORTTensor<single>.Create([width, height{, depth ,etc...}]);
  for y:=0 to inTensor.shape[1]-1 do
      for x:=0 to inTensor.shape[0]-1 do
          inTensor.index2[x, y]:= imageData[x, y];  // your float values
  inputs['image'] := inTensor;

  var
    myDetection : array of single;
    i:integer;
    outputs : TORTNameValueList;
    outTensor : TORTTensor<single>
  begin 
      outputs   := session.run(inputs);
      outTensor := outputs['result']
     
      for i:=0 to outTensor.shape[0] do
        myDetection[i] := outTensor.index1[i]