Comments (3)
you need to change
image load_image_stb_squeezenet(char *filename, int channels)
{
int w, h, c;
unsigned char *data = stbi_load(filename, &w, &h, &c, channels);
if (!data) {
fprintf(stderr, "Cannot load image!!!!!!!!!!!! "%s"\nSTB Reason: %s\n", filename, stbi_failure_reason());
exit(0);
image im;
im.data=0;
return im;
}
if(channels) c = channels;
int i,j,k;
image im = make_image(w, h, c);
//For Squeezenet
for(k = 0; k < c; ++k){
for(j = 0; j < h; ++j){
for(i = 0; i < w; ++i){
if (k==0) {
int dst_index = i + w*j + w*h*(k+2);
int src_index = k + c*i + c*w*j;
im.data[dst_index] = ((float)data[src_index]-123);
}
if (k==1) {
int dst_index = i + w*j + w*h*k;
int src_index = k + c*i + c*w*j;
im.data[dst_index] = ((float)data[src_index]-117);
}
if (k==2) {
int dst_index = i + w*j + w*h*(k-2);
int src_index = k + c*i + c*w*j;
im.data[dst_index] = ((float)data[src_index]-104);
}
}
}
}
free(data);
return im;
}
from squeezenet-darknet-model.
Hi. Thank you for sharing your code.
I downloaded your cfg file and weight file and run following command:
./darknet classifier predict cfg/imagenet1k.data cfg/squeezenet.cfg squeezenet_darknetformat.weight data/dog.jpg
In this command, cfg/squeezenet.cfg and squeezenet_darknetformat.weight is downloaded from your github.
And cfg/imagenet1k.data and data/dog.jpg is basic files of darknet.
I also changed the image.c file following your reply of this issue.
But an accuracy is very low...
Should I perform a training for high accuracy?
Thank you.
from squeezenet-darknet-model.
no I am not trained, you also should change the code in classifier.c to call the load_image_stb_squeezenet()
from squeezenet-darknet-model.
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from squeezenet-darknet-model.