Function opencv::dnn::read_net_from_torch

pub fn read_net_from_torch(
    model: &str, 
    is_binary: bool, 
    evaluate: bool
) -> Result<Net>

Reads a network model stored in Torch7 framework's format.

Parameters

• model: path to the file, dumped from Torch by using torch.save() function.
• isBinary: specifies whether the network was serialized in ascii mode or binary.
• evaluate: specifies testing phase of network. If true, it's similar to evaluate() method in Torch.

Returns

Net object.

Note: Ascii mode of Torch serializer is more preferable, because binary mode extensively use long type of C language, which has various bit-length on different systems.

The loading file must contain serialized nn.Module object with importing network. Try to eliminate a custom objects from serialazing data to avoid importing errors.

List of supported layers (i.e. object instances derived from Torch nn.Module class):

• nn.Sequential
• nn.Parallel
• nn.Concat
• nn.Linear
• nn.SpatialConvolution
• nn.SpatialMaxPooling, nn.SpatialAveragePooling
• nn.ReLU, nn.TanH, nn.Sigmoid
• nn.Reshape
• nn.SoftMax, nn.LogSoftMax

Also some equivalents of these classes from cunn, cudnn, and fbcunn may be successfully imported.

C++ default parameters

• is_binary: true
• evaluate: true