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OpenCv4.1.1 windows 10 Inference engin R3 2019 Visual studio 2019. I run sample of opencv dnn. I have the following models: 1. ssd mobilenet tensorflow model that do licenseplate recognition (ocr). 2. ssd mobilenet tensorflow model optimized by mo_tf.py that do licenseplate recognition (ocr). 3. Tiny yolo darknet model that locate license plates and classify jurisdiction. 4. Tiny yolo darknet model optimized by mo_tf.py after conversion that locate license plates and classify jurisdiction.

The first 3 I am able to run correctly by the sample. The last one returns 2 matrices of size -1 -1. The routine static std::string outLayerType = net.getLayer(outLayesr[0])->type; returns "regionYolo" which is not supported by the sample. https://www.dropbox.com/sh/nir2yqqjd9ufz29/AABRk4PhZmrGaJH3GFmNEiTka?dl=0 above is link to my projects and models.

OpenCv4.1.1 windows 10 Inference engin R3 2019 Visual studio 2019. I run sample of opencv dnn. I have the following models: 1. ssd mobilenet tensorflow model that do licenseplate recognition (ocr). 2. ssd mobilenet tensorflow model optimized by mo_tf.py that do licenseplate recognition (ocr). 3. Tiny yolo darknet model that locate license plates and classify jurisdiction. 4. Tiny yolo darknet model optimized by mo_tf.py after conversion that locate license plates and classify jurisdiction.

The first 3 I am able to run correctly by the sample. The last one returns 2 matrices of size -1 -1. The routine static std::string outLayerType = net.getLayer(outLayesr[0])->type; net.getLayer(outLayesr[0])->type; returns "regionYolo" which is not supported by the sample. https://www.dropbox.com/sh/nir2yqqjd9ufz29/AABRk4PhZmrGaJH3GFmNEiTka?dl=0 above is link to my projects and models.

OpenCv4.1.1 windows 10 Inference engin R3 2019 Visual studio 2019. I run sample of opencv dnn. I have the following models: 1. models:

1. ssd mobilenet tensorflow model that that do licenseplate recognition (ocr). (ocr).
2.
2. ssd mobilenet tensorflow model model optimized by mo_tf.py that do do licenseplate recognition (ocr). (ocr).
3.
3. Tiny yolo darknet model that locate locate license plates and classify jurisdiction. 4. classify jurisdiction.
4. Tiny yolo darknet model optimized by by mo_tf.py after conversion that that locate license plates and classify classify jurisdiction.

The first 3 I am able to run correctly by the sample. The last one returns 2 matrices of size -1 -1. The routine static std::string outLayerType = net.getLayer(outLayesr[0])->type; returns "regionYolo" which is not supported by the sample. https://www.dropbox.com/sh/nir2yqqjd9ufz29/AABRk4PhZmrGaJH3GFmNEiTka?dl=0 above is link to my projects and models.