When I use the model on a cropped face( 112*112), it return

tensor([[ 2.5031, 0.5400, 2.5610, 1.6902, 2.3800, 1.4249, 2.3219, 1.9674, 2.2124, 2.0817, 1.9422, 2.3128, 1.8053, 2.5855, 1.4570, 2.7046, 1.0818, 3.6230, 0.6297, 3.7358, 0.9336, 3.7999, 0.6649, 4.2318, 0.8000, 4.3501, 0.9931, 5.3472, 0.8499, 5.6622, 0.9833, 5.7424, 0.6650, 6.2639, 1.5096, 6.6354, 1.8387, 6.0361, 2.4721, 5.5128, 3.3405, 5.9895, 3.7352, 5.5592, 4.0576, 5.5659, 4.9748, 5.4990, 4.6798, 5.3513, 5.2311, 4.9756, 5.6050, 4.5588, 5.4349, 4.1934, 5.5895, 3.8537, 5.6141, 3.2810, 5.7145, 2.4732, 6.3659, 2.4489, 5.7713, 1.4750, 1.7614, 0.7001, 1.7819, -0.0296, 1.6259, -0.0539, 1.9667, 0.1593, 2.0979, 0.6584, 2.1205, 0.5665, 1.8736, 0.6672, 2.0189, 0.6153, 1.7041, 0.2538, 1.9706, 0.5217, 2.1157, -0.1328, 3.3149, 0.1556, 3.4920, 0.5049, 4.1756, 1.3516, 3.9482, 0.8055, 2.9670, 0.5373, 1.9500, 0.2579, 1.6205, 0.7916, 1.7664, 0.8393, 1.6058, 1.0465, 0.9469, 0.4592, 1.0506, 0.5595, 0.8714, 1.6369, 1.1845, 1.7528, 1.4024, 1.7032, 1.5809, 1.6675, 2.1324, 2.1407, 1.5833, 0.9698, 1.3089, 0.5519, 1.7143, 0.8796, 1.6684, 0.9314, 2.1470, 1.0451, 2.0533, 1.2146, 1.7021, 1.2716, 1.0598, 1.2469, 2.6481, 1.2449, 2.3563, 0.7741, 2.9258, 0.9934, 3.3385, 1.0512, 2.9415, 1.2636, 2.4886, 1.6280, 2.8286, 0.8264, 2.2652, 1.6024, 0.7494, 2.4899, 0.8105, 2.0038, 1.2357, 1.9055, 1.4521, 1.6275, 1.1433, 1.3466, 2.2189, 2.1250, 2.5340, 2.9909, 2.0008, 2.6108, 1.4500, 3.5718, 0.6595, 3.2810, 0.6810, 3.4444, 0.3239, 2.8738, 0.3464, 2.4799, 0.8839, 2.2725, 1.8056, 2.2162, 2.5020, 1.7966, 2.4657, 2.7388, 1.7206, 2.9695, 0.7993, 3.0288, 0.4674, 3.1466, 1.3650, 0.8892, 2.6473, 1.1290]], grad_fn=)

What's that mean? That's no the coordinate, right? And how can I draw dot on a picture by those results? Thanks

original paper:

For instance,if disabling the geometry and data imbalance functionalities, our loss degenerates to a simple`2loss

your code:

        mat_ratio = torch.mean(attributes_w_n, axis=0)
        mat_ratio = torch.Tensor([
            1 / (x*256) if x > 0 else 1 for x in mat_ratio
        ]).cuda()
        weight_attribute = torch.sum(attributes_w_n.mul(mat_ratio), axis=1)

        l2_distant = torch.sum((landmark_gt - landmarks) * (landmark_gt - landmarks), axis=1)
        return torch.mean(weight_angle * weight_attribute * l2_distant), torch.mean(l2_distant)

1 / (x*256) if x > 0 else 1 for x in mat_ratio

you are decreasing weight_attribute if the geometry and data imbalance functionalities are present, but should be vice versa

angle = tensor([[-0.0873, 0.7688, -0.2588]], device='cuda:0') angle_gt = tensor([[ 88.0343, -60.7853, -62.0728]], device='cuda:0') angle = tensor([[-0.1598, 0.5773, -0.4115]], device='cuda:0') angle_gt = tensor([[ 66.4287, -53.0196, -49.0985]], device='cuda:0') angle = tensor([[-0.0510, 0.7076, -0.3719]], device='cuda:0') angle_gt = tensor([[ 48.0916, -45.6873, -17.9782]], device='cuda:0') angle = tensor([[ 0.0888, 0.7797, -0.3578]], device='cuda:0') angle_gt = tensor([[ 54.0094, -37.7794, -10.2092]], device='cuda:0') angle = tensor([[-0.0731, 0.8048, -0.0279]], device='cuda:0') angle_gt = tensor([[15.3467, 3.7500, 10.6802]], device='cuda:0') angle = tensor([[ 0.0906, 0.6620, -0.2479]], device='cuda:0') angle_gt = tensor([[ 79.5670, -63.5313, -39.0085]], device='cuda:0')

thank you for your code ,when i download this code and try to run camera.py ,some error happend, first ,my torch version is 1.1.0, it say volatile was moved ,use torch.no_grad() instead,second ,Illegal instruction (core dumped), do you have this question, how to fix it? thank you

Bumps opencv-python from 4.1.0.25 to 4.1.1.26.

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Hello how does your tensorboard work? I have trained as required, and the corresponding files are also generated in checkpoints, but when viewing tensorboard, there is no output on the web page. This page isn’t working

class PFLDInference(nn.Module): def init(self): super(PFLDInference, self).init()

    self.conv1 = nn.Conv2d(
        3, 64, kernel_size=3, stride=2, padding=1, bias=False)
    self.bn1 = nn.BatchNorm2d(64)
    self.relu = nn.ReLU(inplace=True)

    self.conv2 = nn.Conv2d(
        64, 64, kernel_size=3, stride=1, padding=1, bias=False)
    self.bn2 = nn.BatchNorm2d(64)
    self.relu = nn.ReLU(inplace=True)

@polarisZhao I think conv2 is a depth-wise convolution instead of a normal convolution, right?

您好，非常感谢你的工作。 我在运行train.py的时候遇到了上面这个问题。具体的错误如下：Traceback (most recent call last):

File "train.py", line 232, in main(args) File "train.py", line 173, in main criterion, epoch) File "train.py", line 85, in validate for img, landmark_gt, attribute_gt, euler_angle_gt in wlfw_val_dataloader: File "/home//anaconda3/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 819, in next return self._process_data(data) File "/home//anaconda3/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 846, in _process_data data.reraise() File "/home//anaconda3/lib/python3.6/site-packages/torch/_utils.py", line 369, in reraise raise self.exc_type(msg) RuntimeError: Caught RuntimeError in DataLoader worker process 0. Original Traceback (most recent call last): File "/home/anaconda3/lib/python3.6/site-packages/torch/utils/data/_utils/worker.py", line 178, in _worker_loop data = fetcher.fetch(index) File "/home/anaconda3/lib/python3.6/site-packages/torch/utils/data/_utils/fetch.py", line 47, in fetch return self.collate_fn(data) File "/hom/anaconda3/lib/python3.6/site-packages/torch/utils/data/_utils/collate.py", line 80, in default_collate return [default_collate(samples) for samples in transposed] File "/home/anaconda3/lib/python3.6/site-packages/torch/utils/data/_utils/collate.py", line 80, in return [default_collate(samples) for samples in transposed] File "/home/anaconda3/lib/python3.6/site-packages/torch/utils/data/_utils/collate.py", line 56, in default_collate return torch.stack(batch, 0, out=out) RuntimeError: invalid argument 0: Sizes of tensors must match except in dimension 0. Got 188 and 156 in dimension 2 at /pytorch/aten/src/TH/generic/THTensor.cpp:689

hi! I have no nvidia gpu on my computer .When I run the script train.py the error shows: "AssertionError: Found no NVIDIA driver on your system. Please check that you have an NVIDIA GPU and installed a driver from" How can I train on cpu?

I try to train on NV2080 (8G), but failed with out of memory. What's your training environment? What GPU do you use?

RuntimeError: CUDA out of memory. Tried to allocate 26.00 MiB (GPU 0; 7.76 GiB total capacity; 6.88 GiB already allocated; 7.56 MiB free; 34.09 MiB cached)

Hello in your test.py you have parser.add_argument('--test_dataset', default='./data/test_data/list.txt', type=str) however, what is the list.txt here and could you give us a format to test the WLFWDatasets/ Thanks

Hello, Thank you for your nice repository I make some tests for face with mask but the model cannot detect landmarks because face detection is not generated any bouding box. Could you try with some cases like this? Please help me to figure out what is the problem Thank you

Hello, great work there!!!

I executed the camera.py file with your pre-trained model at "./checkpoint/snapshot/checkpoint.pth.tar".

I realize that eye landmarks generated when eyes are closed are very bad (shown in the below figure). Is this behavior normal? if "not", can you give me some advice to overcome this? Thanks in advance.

Hi! Nice work there. I could download he images from the link provided but Annotations are unavailable. Can You please share sample txt for annotations. I need to annotate my custom dataset and try on this model. Many thanks...

Bumps numpy from 1.17.2 to 1.22.0.

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