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Good day.
There are two file: json and .h5, first with description of NN layers, second with weights. Files are generated by Keras framework with tools model to json. Can I convert this NN to IR format directly for OpenVINO use? Or I should load this model to Keras, save as TensorFlow and then convert to IR?
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Hi,
I have converted my H5 file to frozen model then converted into open vino model.
But, after executing the openvino model , the result is having the ndarray, i am not understanding how to handle the output.
my objective is to detect the Face mask, with confidence and bounding boxes.
result {'conv_81/BiasAdd/Add': array([[[[-1.66312973e+02, -2.46958740e+02, -1.74602142e+02, ...,
-2.83901031e+02, -2.21121582e+02, -9.00830765e+01],
[-1.20000076e+02, -2.66399963e+02, -1.58648590e+02, ...,
-2.18675812e+02, -2.38010468e+02, -1.37554138e+02],
[-1.06553749e+02, -2.97883667e+02, -1.27020409e+02, ...,
-1.77826111e+02, -2.24372299e+02, -1.44611572e+02],
...,
[-4.78074760e+01, -1.75183441e+02, -1.38157776e+02, ...,
-4.33831978e+01, -4.24874916e+01, -6.06762924e+01],
[-1.84533119e+01, -1.68425415e+02, -1.11759216e+02, ...,
-6.22600098e+01, -5.67313538e+01, -4.46702423e+01],
[ 2.93867760e+01, -6.70677872e+01, -5.70977402e+01, ...,
-4.19528961e+01, -3.55563469e+01, -2.01602802e+01]],
[[ 1.40633591e+02, 1.15974365e+02, 1.17529114e+02, ...,
1.81284317e+02, 1.42111740e+02, 7.96556702e+01],
[ 1.27407059e+02, 2.11995117e+02, 1.85863602e+02, ...,
2.60103180e+02, 2.27830368e+02, 1.25303055e+02],
[ 1.64037766e+02, 1.96629532e+02, 1.11918442e+02, ...,
1.56511246e+02, 1.54128342e+02, 8.48983231e+01],
...,
[ 6.33352051e+01, 6.37791214e+01, 7.07268333e+00, ...,
-4.78412857e+01, -4.94226074e+01, -4.03650360e+01],
[-2.00031033e+01, 6.08664474e+01, 8.17405510e+00, ...,
-4.89005280e+01, -5.90939636e+01, -4.14923592e+01],
[-1.53922958e+02, -4.38242569e+01, -4.53684692e+01, ...,
-7.21609192e+01, -6.14896317e+01, -3.65516281e+01]],
[[-4.73735008e+01, -3.41962051e+01, -3.74608269e+01, ...,
-7.45596504e+00, -7.31755733e+00, -1.60885124e+01],
[-6.24234428e+01, -2.96515732e+01, -4.65041237e+01, ...,
-4.72871256e+00, -2.03644466e+00, -9.75383663e+00],
[-7.78091431e+01, -6.62882233e+01, -8.26859665e+01, ...,
-7.36377258e+01, -4.45033646e+01, -4.27225037e+01],
...,
[-5.21416435e+01, -4.79345245e+01, -1.94807243e+01, ...,
-4.63317719e+01, -5.14390182e+01, -4.86955376e+01],
[-5.49678001e+01, -4.29327850e+01, -1.45485783e+01, ...,
-3.20624237e+01, -2.77655869e+01, -3.03304882e+01],
[-3.63332634e+01, -5.35129395e+01, -2.23160210e+01, ...,
-3.47856407e+01, -3.04427185e+01, -2.80112000e+01]],
...,
[[-4.74601059e+01, -7.61016312e+01, -6.27142792e+01, ...,
-5.15001526e+01, -1.97596245e+01, 1.56756973e+00],
[-1.09927811e+02, -1.40803879e+02, -1.29083405e+02, ...,
-9.53482056e+01, -1.30481453e+01, 1.54791842e+01],
[-1.52028290e+02, -2.05058655e+02, -1.97106476e+02, ...,
-1.51681152e+02, -3.56237297e+01, 1.12130127e+01],
...,
[-8.74849091e+01, -4.64156952e+01, -1.48516827e+01, ...,
-5.56459236e+01, -1.25644817e+01, 1.05311594e+01],
[-8.36514206e+01, -5.47760010e+01, -1.75369740e+01, ...,
-1.92452297e+01, 6.29400921e+00, 1.16010056e+01],
[-8.55055695e+01, -6.86285858e+01, -3.49647751e+01, ...,
-2.27549591e+01, -8.11953735e+00, 2.38107443e-01]],
[[-7.85665161e+02, -8.74612976e+02, -9.88772461e+02, ...,
-1.27541602e+03, -9.81773193e+02, -5.76246216e+02],
[-1.26309900e+03, -1.26470850e+03, -1.29349731e+03, ...,
-1.47686731e+03, -1.09906421e+03, -6.09180664e+02],
[-1.78284009e+03, -1.69450464e+03, -1.49403320e+03, ...,
-1.78028442e+03, -1.26287354e+03, -7.03716125e+02],
...,
[-1.00871576e+03, -8.21046570e+02, -6.36620422e+02, ...,
-9.28006348e+02, -7.18372314e+02, -4.14899475e+02],
[-9.60229553e+02, -8.18582581e+02, -5.88664917e+02, ...,
-6.90466431e+02, -5.43034790e+02, -3.17665497e+02],
[-8.69738403e+02, -8.36209045e+02, -5.64757874e+02, ...,
-5.97556946e+02, -4.59418213e+02, -2.51658508e+02]],
[[-4.45263901e+01, -7.05552368e+01, -1.44238162e+00, ...,
-3.45628738e+01, -5.43552780e+01, -4.13258972e+01],
[-8.26740570e+01, -1.21586502e+02, -1.14394188e+01, ...,
-5.72901840e+01, -7.67189178e+01, -5.92793922e+01],
[-1.42641937e+02, -1.68532562e+02, -4.49021759e+01, ...,
-9.04630585e+01, -7.94408722e+01, -5.09029770e+01],
...,
[-9.37536774e+01, -6.21579819e+01, 3.14342213e+01, ...,
3.28904057e+00, -1.52875957e+01, -4.29225874e+00],
[-7.81461029e+01, -7.22118607e+01, 1.63341351e+01, ...,
7.96173859e+00, 2.67618060e+00, 5.32587767e+00],
[-6.89589844e+01, -4.00298271e+01, -2.01719403e-01, ...,
-5.96850276e-01, 8.10801268e-01, 3.34924364e+00]]]],
dtype=float32)}
above is the printout of my result.
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