When setting a tensor for a model I have converted to tf.lite from keras I get the error ValueError: Cannot set tensor: Dimension mismatch. Got 416 but expected 1 for dimension 1 of input 0.

The input sample is an three channel image with shape (1, 416, 416, 3)

The input details got from the interpreter are:

{‘name’: ‘serving_default_input_2:0’,

‘index’: 0,

‘shape’: array([1, 1, 1, 3]),

‘shape_signature’: array([-1, -1, -1, 3]),

‘dtype’: numpy.uint8,

‘quantization’: (0.003921568859368563, 0),

‘quantization_parameters’: {‘scales’: array([ 0.0039216], dtype=float32),

‘zero_points’: array([0]),

‘quantized_dimension’: 0},

‘sparsity_parameters’: {}}

test_image_.shape

The shape signature matches the image, but the interpreter shape is wrong. Any ideas why the tf.lite model got this parameter wrong?

Thanks,

Juan