I am currently trying to call my for the DPU compiled Yolov3 Model but have problems with it.

I’ve managed to successfully use the darknet2caffe workflow to compile the Yolov3 Model for the DPU.

However the compiled model differs that from Xilinx provided model (it is a TensorFlow Model with a different output channel size):

In the repo DPU-PYNQ they have 3 output nodes:

conv2d_59_convolution(0) : 13x13x**75**

conv2d_67_convolution(0) : 26x26x**75**

conv2d_75_convolution(0) : 52x52x**75**

But my output channel sizes are:

layer81_conv(0) : 13x13x**255**

layer93_conv(0) : 26x26x**255**

layer105_conv(0) : 52x52x**255**

I am not sure why Xilinx Model has the the 75 instead of the 255, because the 255 matches the orignal Model. The problem that the difference output channel size is rising an error in the tf_yolov3_voc.py and I’ve lack the knowledge what to change in the tf_yolov3_voc.py to get the correct bounding boxes.

Did somebody also face the problem?