Hi,
I try to run the Super Resolution with RCAN method with RCAN_BDX3-0000 params and json.
My input image has a 224x224 dimension. I load the model as following:
symbol, arg_params, aux_params = mx.model.load_checkpoint('RCAN_BDX3', 0)
model = mx.mod.Module(symbol=symbol, label_names=None)
model.bind(data_shapes=[('data', (1, 3, 224, 224))], for_training=False)
model.init_params(arg_params=arg_params, aux_params=aux_params, allow_missing=False, allow_extra=False)
Then I load the image:
img = mx.image.imread(fname)
img_batch = DataBatch(mx.nd.array(img), 0)
And forward the model:
model.forward(img_batch)
The forward method generates the following error:
MXNetError: Error in operator pre_mean_shift: [14:55:42] c:\jenkins\workspace\mxnet-tag\mxnet\src\operator\tensor\./elemwise_binary_broadcast_op.h:68: Check failed: l == 1 || r == 1 operands could not be broadcast together with shapes [224,224,3] [1,3,1,1]
Does there is any modification to do inside JSON file ("attr": {"__shape__": "(1, 3, 1, 1)"}
for instance) to run the model?
Thank you