dnn resize_layer assertion 'getmemoryshapes'

edit

hi, aguila, can you be a bit more concise about what you are doing here ? there must be a prebuilt model, code, etc.

Hi @berak, the prebuilt model i downloaded from the repo https://wywu.github.io/projects/LAB/s... and there is an implementation in caffe https://github.com/wywu/LAB/blob/mast... i based myself in that one and this one https://github.com/HandsomeHans/Easy-LAB

I started something like this:

Net net_lab = readNet("rel.prototxt", "model.bin");
Mat imge = imread("faceImg.jpg",0);

resize(imge, imge, Size(256,256));
imge.convertTo(imge, CV_32F);
Mat inputBlob = blobFromImage(imge, 1.0, Size(), Scalar(127,127,127), false, false);
net_lab.setInput(inputBlob);
Mat outputBlob = net_lab.forward();

Author uses customized Interp layer (see https://github.com/wywu/LAB/blob/mast...). It resizes the first input blob to size of the second one. If your model always works with 1x1x256x256 input you can easy compute a destination shape and use an origin Interp layer introduced in https://github.com/cdmh/deeplab-public.

Hello @dkurt thank you for your help, sorry i did not checked in the past week the two different layers. I am looking now the differences between the Interp Layer from opencv (the one from deeplab) and the custom layer from the author.

In my case, i will always have the same input size 256x256.

For this, if i am correct, i should explicit give the output size as input in the Interp Layer no? something like:

layer {
  name: "hourglass_1/upper_4/interp"
  type: "Interp"
  bottom: "hourglass_1/lower_4_3/res"
  bottom: "hourglass_1/lower_3/res"
  top: "hourglass_1/upper_4/interp"
  param {
  width:  XX        <--- My inputs
  height: XX
  }
}

@aguila, Try this:

layer {
  name: "hourglass_1/upper_4/interp"
  type: "Interp"
  bottom: "hourglass_1/lower_4_3/res"
  # bottom: "hourglass_1/lower_3/res"  Now we don't need it with explicit output sizes
  top: "hourglass_1/upper_4/interp"
  interp_param {
    width:  256
    height: 256
  }
}

ok i will try it later today and post my results here.. thanks!

@benjamin, please do not post answers here, if you have a question or a comment, thank you

(apart from that, questons like yours never work here, leave older questions alone, noone's here anymore)