How to classify a single image?

[marc40000]

I'm trying to write a function that classifies a single image. I looked into convert_imageset.cpp, test_net.cpp and wrapper.py while trying to figure it out.

So far I managed to load the net, load the image, resize it and convert it into a caffe::Blob. But when I call net::Forward(), it crashes:

template <typename Dtype>
const vector<Blob<Dtype>*>& Net<Dtype>::Forward(
    const vector<Blob<Dtype>*> & bottom, Dtype* loss) {
  // Copy bottom to internal bottom
  for (int i = 0; i < bottom.size(); ++i) {
    net_input_blobs_[i]->CopyFrom(*bottom[i]);
  }
  return ForwardPrefilled(loss);
}

The vector bottom holds 1 entry, the blob I created from the loaded image. However net_input_blobs has 0 entries, and therefore doing [i] crashes. How do I have to set things up correctly so net_input_blobs is set correcly?

My code so far

caffe::Caffe::set_phase(caffe::Caffe::TEST);
caffe::Caffe::set_mode(caffe::Caffe::CPU);

// read trained net
caffe::Net<Dtype> * net = new caffe::Net<Dtype>("lenet_test.prototxt");
net->CopyTrainedLayersFrom("lenet_iter_50");

// load and resize image to 256^2
const int width = 256;
const int height = 256;
cv::Mat cv_img;
cv::Mat cv_img_origin = cv::imread("valpics\\Banane.jpg", CV_LOAD_IMAGE_COLOR);
cv::resize(cv_img_origin, cv_img, cv::Size(height, width));
if (!cv_img.data) {
    printf("Could not open or find input file.\n");
    return 1;
}

// convert the image to a caffe::Blob
caffe::Blob<Dtype> * blob = new caffe::Blob<Dtype>(1, 3, width, height);
for (int c = 0; c < 3; ++c) {
    for (int h = 0; h < cv_img.rows; ++h) {
        for (int w = 0; w < cv_img.cols; ++w) {
            blob->mutable_cpu_data()[blob->offset(0, c, h, w)] = cv_img.at<cv::Vec3b>(h, w)[c];
        }
    }
}

// create input and output vectors for the Forward call
vector<caffe::Blob<Dtype>*> bottom_vecs;
vector<caffe::Blob<Dtype>*> top_vecs;
bottom_vecs.push_back(blob);

Dtype loss;
top_vecs = net->Forward(bottom_vecs, &loss);

// calculate mean of the resulting blob, which is the classification result?
caffe::Blob<Dtype>* topvec = top_vecs[0];
float mean = 0;
for (int c = 0; c < topvec->channels(); ++c) {
    for (int h = 0; h < topvec->height(); ++h) {
        for (int w = 0; w < topvec->width(); ++w) {
            mean += topvec->data_at(0, c, h, w);
        }
    }
}
mean /= (topvec->channels() * topvec->height() * topvec->width());

printf("mean=%f\n", mean);

delete blob;
delete net;

[bhack]

Take a look here: #499

[shelhamer]

This is most easily done by the Python or MATLAB interfaces but #499 does give you the details on how to do this purely in Caffe.

[wguo68]

How to solve the problem that net_input_blobs_.size is 0?

[linson007]

Is there any java sample code for classifying a single image?