Not able to compile Variable sized image as input.

[idata]

I have made a Object Detector using Keras.

input_1 (InputLayer) (None, None, None, 3)

fcn_conv0 (Conv2D) (None, None, None, 32)fcn_conv1 (Conv2D) (None, None, None, 64)fcn_conv2 (Conv2D) (None, None, None, 128)max_pooling2d_1 (MaxPooling2 (None, None, None, 128)fcn_conv3 (Conv2D) (None, None, None, 64) max_pooling2d_2 (MaxPooling2 (None, None, None, 64) fcn_conv4 (Conv2D) (None, None, None, 32)max_pooling2d_3 (MaxPooling2 (None, None, None, 32)fcn_conv5 (Conv2D) (None, None, None, 32) fcn_conv6 (Conv2D) (None, None, None, 512)fcn_conv7 (Conv2D) (None, None, None, 6)global_max_pooling2d_1 (Glob (None, 6)

Since I am dealing with variable sized object, I have kept the input as None and made a custom loss.

But after converting my Keras model to Tensorflow model and compiling using mvNCCompile command line tool it throws an error that

input_data = np.random.uniform(0, 1, shape)

File "mtrand.pyx", line 1307, in mtrand.RandomState.uniform File "mtrand.pyx", line 242, in mtrand.cont2_array_scTypeError: 'NoneType' object cannot be interpreted as an integer

Command I am using is:

mvNCCompile tf_model.meta -in=input_1 -on=fcn_conv11/BiasAdd

I've the TF_Model folder which contains checkpoint file, .meta file, .data file, .index file.

Kindly help. I am stuck with these for the past one week

Thanks

[idata]

@bumzo The NCSDK doesn't support models that use variable input sizes. For reference, the NCSDK takes a model and compiles a version of that model in the form of a static Movidius graph file. The input size is set for the graph file and cannot be changed. You can always resize input images to a set input size resolution, but I understand that based on what you are doing, it may not be suitable. Currently there isn't a workaround for implementing variable input sizes.

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@Tome_at_Intel But then how it is supporting Yolo?

Even it works on the principle of R-FCN and variable size.

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@bumzo The input size for Tiny Yolo is set at 448x448. This doesn't change. When using input images that are of a different resolution, the images are resized and passed through the model.

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@Tome_at_Intel thanks for the information.

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Hi, I am getting the same exact problem but I took a Resnet Inception V2 model from TensorFlow Zoo which should be supported and I retrained it on my custom dataset. After retraining, I took the weights from inference folder and tried to use the mvncCompile on them and got the same exact error. How can I change the input size to 1 in this case? @bumzo @Tome_at_Intel

[idata]

Hi @ali18997

I've answered your question on your other thread here.

Best Regards,

Sahira