deformable onnx

Deformable ONNX refers to a version of the Open Neural Network ExchangeONNX) format that support for deformable convolutional neural networks (DCNNs). Deformable convolutions are a type of convolutional layer used in computer vision tasks, which allow for more flexible and accurate feature extraction by allowing the receptive field of the convolutional filters to be adjusted based on the input data.

To support deformable convolutions in ONNX, additional operators and attributes are added to the standard ONNX specification. These include the DeformableConv operator, which performs the deformable convolution operation, as well as attributes that specify the parameters of the deformable convolution such as the number of output channels and the kernel size.

With support for deformable convolutions in ONNX, models that use these types of layers can be exported and used across different deep learning frameworks and hardware platforms that support the ONNX format. This allows for greater flexibility and portability of DCNN models, which can be particularly useful in scenarios where real-time inference is required or where hardware constraints limit the use of certain deep learning frameworks.