how_to_debug.md

Before comparing the middle results, please use png images instead of jpeg images without resize.

Pytorch-yolo2

1. set model to evaluation

m = m.eval()

2. In darknet.py, uncomment if condition to stop forward on certain layer

    def forward(self, x):
        ind = -2
        self.loss = None
        outputs = dict()
        for block in self.blocks:
            ind = ind + 1
            #if ind > 27:
            #    break

3. In utils.py:do_detect, add

print(output.storage()[0:100])

to get the layer output

4. Prepare a test image, resized to 416x416, save to test.png. Stop resize in detect.py:detect

sized = img.resize((m.width, m.height)) ->
sized = img

Darknet

1. set GPU and CUDNN to 0 in Makefile

2. In src/detector.c:test_dector, stop resize

image sized = letterbox_image(im, net.w, net.h);  ->
image sized = im

And add output print

layer ll = net.layers[27];
float *Y = ll.output;
printf("---- Y ----\n");
for(j = 0; j < 169; j++) printf("%d: %f\n", j, Y[j]);
printf("\n");

Reorg Problem

There seems the problem in darknet

get_region_boxes speed up

detect.py cfg/yolo.cfg yolo.weight data/dog.jpg

• slow : 0.145544
• fast : 0.050640
• faster: 0.009280

train.py

• slow: 380ms
• fast: 114ms
• faster: 22ms (batch=64 1.5s)
• fasterer: gpu to cpu (batch=64 0.15s)