Hands-On Machine Learning with C++

Loading images into Caffe2 tensors

Let's learn how to load an image into the Caffe2 tensor object and modify it according to the model's input requirements. The model expects the input images to be normalized and three-channel RGB images whose shapes are (N x 3 x H x W), where N is the batch size and H and W are expected to be at least 224 pixels wide. Normalization assumes that the images are loaded into a range of [0, 1] and then normalized using means equal to [0.485, 0.456, 0.406] and standard deviations equal to [0.229, 0.224, 0.225].

Let's assume that we have the following function definition for image loading:

caffe2::TensorCPU ReadImageTensor(const std::string& file_name,                                                 int width,                                                 int height) {   ...}

Let's write its implementation. ...