lucasjinreal / centernet_pro_max Goto Github PK

需要的话可以加wx/qq 355152992

Although I had a lot of troubles running the code, I succeeded in the end! !! This is a great job！

the code for gaussian radius from CenterNet repo was brought from Cornernet and the gaussian_radius() function is wrong, it has been fixed by the author here is the code

def gaussian_radius(det_size, min_overlap):
    height, width = det_size

    a1  = 1
    b1  = (height + width)
    c1  = width * height * (1 - min_overlap) / (1 + min_overlap)
    sq1 = np.sqrt(b1 ** 2 - 4 * a1 * c1)
    r1  = (b1 - sq1) / (2 * a1)

    a2  = 4
    b2  = 2 * (height + width)
    c2  = (1 - min_overlap) * width * height
    sq2 = np.sqrt(b2 ** 2 - 4 * a2 * c2)
    r2  = (b2 - sq2) / (2 * a2)

    a3  = 4 * min_overlap
    b3  = -2 * min_overlap * (height + width)
    c3  = (min_overlap - 1) * width * height
    sq3 = np.sqrt(b3 ** 2 - 4 * a3 * c3)
    r3  = (b3 + sq3) / (2 * a3)
    return min(r1, r2, r3)

Please refer to this for formula derivation
princeton-vl/CornerNet#110

简单看了一下想训练coco试试，但是在代码里没找到定位数据集path的地方。。。以及怎么指定使用第几个GPU训练，如果单机多卡训练的话应该改哪些设置，谢谢!

Thanks for your amazing work! I have tried to train the code on my own dataset with multi gpus, but it still works on the first one! And I find that the parameter '--num-gpus' not be used! How did you train on 8 gpus?

Thanks for the great job.
So far I m trying to train with "resnet18 + without DCN". But it occurs error as bellow.
File "/home/administrator/anaconda3/envs/CenterNet/lib/python3.6/site-packages/torch/nn/modules/conv.py", line 778, in forward output_padding, self.groups, self.dilation) RuntimeError: Given transposed=1, weight of size 2048 256 4 4, expected input[8, 512, 16, 16] to have 2048 channels, but got 512 channels instead

RuntimeError: Only tuples, lists and Variables supported as JIT inputs, but got dict
我需要改下那个文件呢

Good job @jinfagang

BTW I find a recent implementation for effdet. Try this repo, https://github.com/rwightman/efficientdet-pytorch/blob/master/train.py

Good luck to you,

Dear Sir:

when i run the demo code with CPU mode, nothing detected, the output is :

try load weights from: ./weights/model_0509999.pth
INFO 03.21 16:31:38 checkpoint.py:121: Loading checkpoint from ./weights/model_0509999.pth
tensor([ 1, 80, 112, 168])
tensor([[[18815, 16863, 16887, ..., 2773, 2781, 2757],
[18207, 18703, 18231, ..., 9472, 15063, 15039],
[18728, 18720, 18752, ..., 18243, 18227, 18251],
...,
[18648, 11093, 11760, ..., 7292, 7316, 7324],
[ 167, 18815, 18648, ..., 18670, 12431, 9408],
[18815, 18648, 167, ..., 3, 18773, 16743]]])
tensor(112)
tensor(168)
tensor(18816)
b.pred_boxes: []
b.scores: []
b.pred_classes: []