Any example of input multiple image(batch processing) into the model by c++ api?

Follow the example at here, but instead of input multiple words, I input multiple images into the network but the results are not as expected(it work for one input image).

I am using the model from deepinsight(resnet100)

You can find the source codes at github, the main points are

A. If batch size greater than 1, add a “data1” argument

args["data"] = NDArray(input_shape, context);
if(input_shape[0] > 1){
    args["data1"] = NDArray(Shape(1), context, false);

B. Copy the contents of multiple images into a std::vector

std::vector<float> dlib_matrix_to_float_array(std::vector<dlib::matrix<dlib::rgb_pixel> const*> const &rgb_image)
    size_t const pixel_size = static_cast<size_t>(rgb_image[0]->nc() * rgb_image[0]->nr()) * 3;
    std::vector<float> image_vector(pixel_size * rgb_image.size());
    size_t index = 0;
    for(size_t i = 0; i != rgb_image.size(); ++i){
        for(size_t ch = 0; ch != 3; ++ch){
            for(long row = 0; row != rgb_image[i]->nr(); ++row){
                for(long col = 0; col != rgb_image[i]->nc(); ++col){
                    auto const &pix = (*rgb_image[i])(row, col);
                    case 0:
                        image_vector[index++] =;
                    case 1:
                        image_vector[index++] =;
                    case 2:
                        image_vector[index++] =;

    return image_vector;

C. Copy and Forward the data

//input is the std::vector with data of the images
executor_->arg_dict()["data"].SyncCopyFromCPU(, input.size());
executor_->arg_dict()["data1"] = batch_size;

D. Split the NDArray into multiple NDArray

        auto features = executor_->outputs[0].Copy(Context(kCPU, 0));
        Shape const shape(1, step_per_feature);
        for(size_t i = 0; i != batch_size; ++i){
            NDArray feature(features.GetData() + i * 512, shape, Context(kCPU, 0));
            //following solution do not work either
            /*std::vector<float> buffer(512);
            for(size_t j = 0; j != 512; ++j){
                buffer[j] = features.At(i, j);
            NDArray feature(&buffer[0], shape, Context(kCPU, 0));
            //problem is, the feature extract is not correct

What kind of errors I commit?Thanks

ps : Do I need to re-export the model and change the batch size too?

Solve the issue by myself, the bug is I did not make sure the input size of the vector, has the same batch size as following line

args["data"] = NDArray(input_shape, context);

You can find the working example on github, if anyone want to deploy deepinsight model to their app, I believe this is a good starting point, please point out if you found any bugs, thanks.


Thanks @stereomatchingkiss for sharing your solution.