Problem with testing on my data

I want to test DenseDepth on a specific dataset but I got this error:

 return tf.concat([to_dense(x) for x in tensors], axis)

    ValueError: Exception encountered when calling layer 'up1_concat' (type Concatenate).

    Dimension 1 in both shapes must be equal, but are 32 and 33. Shapes are [?,32,48] and [?,33,49]. for '{{node model_1/up1_concat/concat}} = ConcatV2[N=2, T=DT_FLOAT, Tidx=DT_INT32](model_1/up1_upsampling2d/resize/ResizeBilinear, model_1/pool3_pool/AvgPool, model_1/up1_concat/concat/axis)' with input shapes: [?,32,48,1664], [?,33,49,256], [] and with computed input tensors: input[2] = <3>.

    Call arguments received by layer 'up1_concat' (type Concatenate):
      • inputs=['tf.Tensor(shape=(None, 32, 48, 1664), dtype=float32)', 'tf.Tensor(shape=(None, 33, 49, 256), dtype=float32)']

The dataset is Enrich: https://github.com/davidemarelli/ENRICH ENRICH-Statue, cityW Can you please help me with this problem?

ialhashim / DenseDepth

Problem with testing on my data #222