Comments (2)
ayooshkathuria
commented on August 25, 2024
1
Well, I think I can help you out a bit.
First of all, in detect.py there's a variable called imlist which stores the paths of the images. Keep note of index of each image.
Then, in the code, at around line 250, precisely after the line
output[:,1:5] *= im_dim_list
There is a variable output, a 2-d tensor which contains the details of each detection per row. Here is what the output looks like for default imgs directory.
Columns 0 to 6
0.0000 118.2249 119.4276 572.4760 429.8945 0.9985 0.9982
0.0000 477.6349 84.2408 687.1730 170.4992 0.9546 0.8620
0.0000 120.2748 207.8708 313.6242 541.9991 0.9987 0.9932
1.0000 44.5722 16.6605 798.5769 725.9565 0.9994 1.0000
1.0000 632.7744 117.8598 1144.7529 718.2219 0.9976 1.0000
1.0000 1193.0134 475.0443 1287.9580 684.4681 0.9952 0.9997
1.0000 373.5918 380.6013 445.9761 505.4237 0.5078 0.8786
3.0000 130.2477 78.4422 606.2959 447.8753 0.9999 0.9969
4.0000 189.4601 88.3928 274.2381 367.9490 0.9989 0.9999
4.0000 68.5351 266.8620 204.5787 348.1553 0.9984 0.9985
4.0000 392.5365 139.0717 600.5876 344.8741 0.9991 0.9959
5.0000 161.6265 261.8117 252.6919 369.4432 0.9814 0.9979
5.0000 3.5819 243.2121 68.0432 373.8014 0.9427 0.9748
5.0000 456.5395 148.8004 474.4457 168.4535 0.6563 0.9994
6.0000 0.0000 186.0073 376.2489 404.3224 0.9967 0.9982
6.0000 435.6129 213.8517 598.8758 345.5339 0.9901 0.8957
6.0000 230.9883 180.6014 460.7431 358.8419 0.7936 0.9951
7.0000 231.7281 329.7414 333.4314 375.6737 0.9992 0.9991
7.0000 15.5507 310.3270 81.2751 364.0855 0.9973 0.5676
7.0000 362.2694 331.0900 497.7398 388.7157 0.9948 0.9307
7.0000 172.1066 327.6013 254.0974 365.0104 0.9873 0.9853
7.0000 139.6422 323.4359 190.3763 357.8081 0.9847 0.9893
7.0000 83.0906 328.0125 112.1545 348.0191 0.8918 0.9972
7.0000 106.8326 326.4905 134.6070 351.3198 0.7799 0.9954
7.0000 2.4614 322.7372 13.5060 341.0310 0.6313 0.9664
7.0000 18.7216 311.1300 84.3383 362.4027 0.9951 0.6338
7.0000 381.9297 107.4763 408.2099 167.2793 0.9309 0.9999
8.0000 138.5508 196.7630 209.1340 295.7622 0.9964 0.9993
9.0000 17.9466 0.0000 353.0000 500.0000 0.9902 0.9948
9.0000 56.6002 225.1510 190.4027 360.4565 0.9786 0.9925
10.0000 247.1123 192.6713 426.7067 451.9630 0.9985 0.9464
10.0000 145.4339 37.6159 459.5411 421.7098 0.9981 0.9988
Columns 7 to 7
1.0000
7.0000
16.0000
0.0000
0.0000
0.0000
29.0000
14.0000
0.0000
16.0000
17.0000
56.0000
56.0000
74.0000
17.0000
17.0000
17.0000
2.0000
2.0000
2.0000
2.0000
2.0000
2.0000
2.0000
2.0000
7.0000
9.0000
6.0000
0.0000
16.0000
22.0000
23.0000
[torch.FloatTensor of size (32,8)]
You see, the column number 0 represents the index of the image in imlist, the columns 1-4 represent the corner co-ordinates of that bounding box in form (x1, y1, x2, y2) and the last column is the object class of that detection.
Given you have the co-ordinates for the bounding boxes, just slice the array containing the image and do your thing.
from yolo_v3_tutorial_from_scratch.
P-Lubinski
commented on August 25, 2024
Great! Thanks a lot for a quick response!
from yolo_v3_tutorial_from_scratch.
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