why do these in load_image_stb

[azuryl]

//For MobileNet v2 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 + wj + wh(k+2); int src_index = k + ci + cwj; im.data[dst_index] = ((float)data[src_index]-123.68)0.017; } if (k==1) { int dst_index = i + wj + whk; int src_index = k + ci + cwj; im.data[dst_index] = ((float)data[src_index]-116.78)0.017; } if (k==2) { int dst_index = i + wj + wh(k-2); int src_index = k + ci + cwj; im.data[dst_index] = ((float)data[src_index]-103.94)*0.017; } } } }

[WePCf]

This was inherited from original Caffe's preprocessing method. Just image normalization.

[azuryl]

thank you I have converted Squeezenet 1.1 caffe model to darknet format and use the method as you used , you can download from https://github.com/azuryl/squeezenet-darknet-model

[WePCf]

First I would say it's a really nice work. But may I ask have you tested the model on darknet? I tried to use "predict" to see some images' results, however, the results were all wrong.

Could you please show more details, for example, the normalization method or "synset.labels.list" or "imagenet.labels.list"?

[azuryl]

classes=1000 train = /data/imagenet/imagenet1k.train.list valid = squeezenet/inet.val.list backup = /home/pjreddie/backup/

labels = data/imagenet.labels.list

labels = squeezenet/synsets.labels.list names = data/imagenet.shortnames.list top=5

the inet.val.list is created by youself

./darknet classifier predict squeezenet/imagenet1k.data squeezenet/squeezenet.cfg squeezenet/squeezenet_darknetformat.weights data/eagle.jpg 9 layer filters size input output 0 conv 64 3 x 3 / 2 227 x 227 x 3 -> 113 x 113 x 64 1 max 3 x 3 / 2 113 x 113 x 64 -> 57 x 57 x 64 2 conv 16 1 x 1 / 1 57 x 57 x 64 -> 57 x 57 x 16 3 conv 64 1 x 1 / 1 57 x 57 x 16 -> 57 x 57 x 64 4 route 2 5 conv 64 3 x 3 / 1 57 x 57 x 16 -> 57 x 57 x 64 6 route 3 5 7 conv 16 1 x 1 / 1 57 x 57 x 128 -> 57 x 57 x 16 8 conv 64 1 x 1 / 1 57 x 57 x 16 -> 57 x 57 x 64 9 route 7 10 conv 64 3 x 3 / 1 57 x 57 x 16 -> 57 x 57 x 64 11 route 8 10 12 max 3 x 3 / 2 57 x 57 x 128 -> 29 x 29 x 128 13 conv 32 1 x 1 / 1 29 x 29 x 128 -> 29 x 29 x 32 14 conv 128 1 x 1 / 1 29 x 29 x 32 -> 29 x 29 x 128 15 route 13 16 conv 128 3 x 3 / 1 29 x 29 x 32 -> 29 x 29 x 128 17 route 14 16 18 conv 32 1 x 1 / 1 29 x 29 x 256 -> 29 x 29 x 32 19 conv 128 1 x 1 / 1 29 x 29 x 32 -> 29 x 29 x 128 20 route 18 21 conv 128 3 x 3 / 1 29 x 29 x 32 -> 29 x 29 x 128 22 route 19 21 23 max 3 x 3 / 2 29 x 29 x 256 -> 15 x 15 x 256 24 conv 48 1 x 1 / 1 15 x 15 x 256 -> 15 x 15 x 48 25 conv 192 1 x 1 / 1 15 x 15 x 48 -> 15 x 15 x 192 26 route 24 27 conv 192 3 x 3 / 1 15 x 15 x 48 -> 15 x 15 x 192 28 route 25 27 29 conv 48 1 x 1 / 1 15 x 15 x 384 -> 15 x 15 x 48 30 conv 192 1 x 1 / 1 15 x 15 x 48 -> 15 x 15 x 192 31 route 29 32 conv 192 3 x 3 / 1 15 x 15 x 48 -> 15 x 15 x 192 33 route 30 32 34 conv 64 1 x 1 / 1 15 x 15 x 384 -> 15 x 15 x 64 35 conv 256 1 x 1 / 1 15 x 15 x 64 -> 15 x 15 x 256 36 route 34 37 conv 256 3 x 3 / 1 15 x 15 x 64 -> 15 x 15 x 256 38 route 35 37 39 conv 64 1 x 1 / 1 15 x 15 x 512 -> 15 x 15 x 64 40 conv 256 1 x 1 / 1 15 x 15 x 64 -> 15 x 15 x 256 41 route 39 42 conv 256 3 x 3 / 1 15 x 15 x 64 -> 15 x 15 x 256 43 route 40 42 44 dropout p = 0.50 115200 -> 115200 45 conv 1000 1 x 1 / 1 15 x 15 x 512 -> 15 x 15 x1000 46 avg 15 x 15 x1000 -> 1000 47 softmax 1000 48 cost 1000 Loading weights from squeezenet/squeezenet_darknetformat.weights...

predictions:0.000000 data/eagle.jpg: Predicted in 0.598544 seconds. 30.64%: bald eagle 19.15%: ruddy turnstone 14.06%: kite 8.25%: dowitcher 3.65%: vulture

[azuryl]

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 + wj + wh(k+2); int src_index = k + ci + cwj; im.data[dst_index] = ((float)data[src_index]-123); } if (k==1) { int dst_index = i + wj + whk; int src_index = k + ci + cwj; im.data[dst_index] = ((float)data[src_index]-117); } if (k==2) { int dst_index = i + wj + wh(k-2); int src_index = k + ci + cwj; im.data[dst_index] = ((float)data[src_index]-104); } } } }

free(data); return im;