lxg2015 / faceboxes Goto Github PK

/opt/conda/conda-bld/pytorch_1524584710464/work/aten/src/THC/THCTensorScatterGather.cu:97: void THCudaTensor_gatherKernel(TensorInfo<Real, IndexType>, TensorInfo<Real, IndexType>, TensorInfo<long, IndexType>, int, IndexType) [with IndexType = unsigned int, Real = float, Dims = 2]: block: [315,0,0], thread: [200,0,0] Assertion indexValue >= 0 && indexValue < src.sizes[dim] failed.
/opt/conda/conda-bld/pytorch_1524584710464/work/aten/src/THC/THCTensorScatterGather.cu:97: void THCudaTensor_gatherKernel(TensorInfo<Real, IndexType>, TensorInfo<Real, IndexType>, TensorInfo<long, IndexType>, int, IndexType) [with IndexType = unsigned int, Real = float, Dims = 2]: block: [315,0,0], thread: [219,0,0] Assertion indexValue >= 0 && indexValue < src.sizes[dim] failed.
/opt/conda/conda-bld/pytorch_1524584710464/work/aten/src/THC/THCTensorScatterGather.cu:97: void THCudaTensor_gatherKernel(TensorInfo<Real, IndexType>, TensorInfo<Real, IndexType>, TensorInfo<long, IndexType>, int, IndexType) [with IndexType = unsigned int, Real = float, Dims = 2]: block: [262,0,0], thread: [117,0,0] Assertion indexValue >= 0 && indexValue < src.sizes[dim] failed.
Traceback (most recent call last):
File "/home/t1070/TeddyZhang/DEEP_LEARNING/faceboxes-master/trainvisdom.py", line 116, in
train()
File "/home/t1070/TeddyZhang/DEEP_LEARNING/faceboxes-master/trainvisdom.py", line 73, in train
loss = criterion(loc_preds,loc_targets,conf_preds,conf_targets)
File "/home/t1070/anaconda2/envs/TeddyZhang/lib/python3.6/site-packages/torch/nn/modules/module.py", line 491, in call
result = self.forward(input, **kwargs)
File "/home/t1070/TeddyZhang/DEEP_LEARNING/faceboxes-master/multibox_loss.py", line 64, in forward
neg = self.hard_negative_mining(conf_loss, pos) # (1621824, (16,21824))
File "/home/t1070/TeddyZhang/DEEP_LEARNING/faceboxes-master/multibox_loss.py", line 29, in hard_negative_mining
conf_loss[pos.view(-1,1)] = 0 #去掉正样本,the rest are neg conf_loss
RuntimeError: device-side assert triggered

Nice job! Any data about fps on CPU and GPU?

在Wider数据集训练中也出现了loss爆炸，请问你是如何避免loss爆炸并且训练的呢？

In you code, the density is density = [[-3,-1,1,3],[-1,1],[0]].

but I think it's density = [[-3,-1,1,3],[-2,2],[0]].
See this:

Hi, I'm reading the paper and curious about your implementation.

CReLU layer seems defined but not used. Instead, the code implements it again in the layer construction.

Also, the paper has a batch norm layer but it's not implemented.

What is the consideration for this implementation? Better performance?

Thanks

“path/image_name.jpg num_face x y w h 1 x y w h 1”，x and y is the center of the face box or the leftup ?
thank you!

it looked like no anchor densification strategy?
the effect was bad when detecting more than 20 faces.

Hi,
I made changes to your network. Added the batchnorm and xavier initializations, but i noticed you have used Adam optimizer while paper used SGD with decay and momentum, even the parameters are not the same of paper. I followed the same methodology, but my loss is still pretty high (~3.5),still need to do eval using widerface eval.

1. Did you train it on widerface train+val or only train?
2. For eval, did you use the evaluation tool present in site?