When run
darknet.exe detector test areca-c.data yolov3-tiny.cfg backup/yolov3-tiny_13500.weights E:\AI\Data\areca-train\train\DJI_0775_2.jpg
I got these:
================================================
layer filters size input output
0 conv 16 3 x 3 / 1 416 x 416 x 3 -> 416 x 416 x 16 0.150 BF
1 max 2 x 2 / 2 416 x 416 x 16 -> 208 x 208 x 16 0.003 BF
2 conv 32 3 x 3 / 1 208 x 208 x 16 -> 208 x 208 x 32 0.399 BF
3 max 2 x 2 / 2 208 x 208 x 32 -> 104 x 104 x 32 0.001 BF
4 conv 64 3 x 3 / 1 104 x 104 x 32 -> 104 x 104 x 64 0.399 BF
5 max 2 x 2 / 2 104 x 104 x 64 -> 52 x 52 x 64 0.001 BF
6 conv 128 3 x 3 / 1 52 x 52 x 64 -> 52 x 52 x 128 0.399 BF
7 max 2 x 2 / 2 52 x 52 x 128 -> 26 x 26 x 128 0.000 BF
8 conv 256 3 x 3 / 1 26 x 26 x 128 -> 26 x 26 x 256 0.399 BF
9 max 2 x 2 / 2 26 x 26 x 256 -> 13 x 13 x 256 0.000 BF
10 conv 512 3 x 3 / 1 13 x 13 x 256 -> 13 x 13 x 512 0.399 BF
11 max 2 x 2 / 1 13 x 13 x 512 -> 13 x 13 x 512 0.000 BF
12 conv 1024 3 x 3 / 1 13 x 13 x 512 -> 13 x 13 x1024 1.595 BF
13 conv 256 1 x 1 / 1 13 x 13 x1024 -> 13 x 13 x 256 0.089 BF
14 conv 512 3 x 3 / 1 13 x 13 x 256 -> 13 x 13 x 512 0.399 BF
15 conv 18 1 x 1 / 1 13 x 13 x 512 -> 13 x 13 x 18 0.003 BF
16 yolo
17 route 13
18 conv 128 1 x 1 / 1 13 x 13 x 256 -> 13 x 13 x 128 0.011 BF
19 upsample 2x 13 x 13 x 128 -> 26 x 26 x 128
20 route 19 8
21 conv 256 3 x 3 / 1 26 x 26 x 384 -> 26 x 26 x 256 1.196 BF
22 conv 18 1 x 1 / 1 26 x 26 x 256 -> 26 x 26 x 18 0.006 BF
23 yolo
Total BFLOPS 5.448
Loading weights from backup/yolov3-tiny_13500.weights...
seen 64
Done!
E:\AI\Data\areca-train\train\DJI_0775_2.jpg: Predicted in 10.122000 milli-seconds.
areca: 100%
areca: 100%
areca: 100%
areca: 100%
areca: 100%
areca: 100%
areca: 100%
areca: 100%
areca: 100%
areca: 100%
areca: 100%
saving to DJI_0775_2.jpg
However, with OpenVINO/NCS2, I got this
Is this because we have different layers in IE model compared to darknet model?
Link Copied
Shubha R. (Intel) wrote:Dear Ross,
Please use PINTO's github repo for inspiration :
https://github.com/PINTO0309/OpenVINO-YoloV3
My guess is that your anchor settings are incorrect.
Thanks for using OpenVino !
Shubha
Hi Shubha,
I tried, but seemed not working,
check it out
