Can you gave a test example?

I tried to run your code, but it seems incompatible. First of all, I run under python3.7: pip install deep-alignment-pytorch.
But I got the following error：

Then I went back to 3.6 and anaconda to try to install, but it also failed.
Finally I tried to use google colab, it worked miraculously.
But I still encountered many problems, including TensorFlow version problems, path loss problems, etc., but I have solved them. But in the end, during training, I got a problem I couldn't solve:

Can you give me some suggestions, I will be very grateful!

sorry to take your time! I used your imagetransfrom layer, landmarkstransfrom layer and the Heatmap layer for some tests. When the estimatetransform layer process a affine matrix. the landmarks are good to be transformed. But the image is not transformed, the transformed image become almost black!
the images are all [batch, 3, 256, 256]
Here is my define:
mean_shape = torch.Tensor(np.load("meanshape.npy")) trafo_param_layer = EstimateAffineParams(mean_shape.squeeze(0)) img_trafo_layer = AffineImageTransformation((256, 256)) landmark_trafo_layer = AffineLandmarkTransformation() heatmap_layer = HeatMap((256, 256), 32)
Here is my transform process:
affine_params = trafo_param_layer(out.data.cpu()) transformed_img = img_trafo_layer(inp.data.cpu(), affine_params) transformed_lmks = landmark_trafo_layer(out.data.cpu(), affine_params) heatmap = heatmap_layer(transformed_lmks)
Here is my debug show:
ori_inp = inp.data.cpu().numpy() debug_inp = transformed_img.numpy() debug_lmk = transformed_lmks.numpy() for num in range(out.size(0)): plt.imshow(ori_inp[num].transpose(1,2,0)) plt.show() plt.imshow(debug_inp[num].transpose(1,2,0)) plt.plot(debug_lmk[num][:,0], debug_lmk[num][:,1], ".") plt.show()

It is the result. I don't know why the transformed image is wrong? can you help me? please! Thank you!

Can you provide me the pretrained model?

1. I try to run your code, but I got this:./dataset/trainset is not a valid directory and It happened in
   Traceback (most recent call last): File "preprocess.py", line 57, in <module> random_scale=RANDOM_SCALE File "/home/wqzhaha/anaconda3/envs/py36_torch_gpu/lib/python3.6/site-packages/shapedata/single_shape/dataset.py", line 161, in __init__ img_files = make_dataset(data_path) File "/home/wqzhaha/anaconda3/envs/py36_torch_gpu/lib/python3.6/site-packages/shapedata/utils.py", line 36, in make_dataset assert os.path.isdir(dir), '%s is not a valid directory' % dir AssertionError: ./data/dataset/trainset/ is not a valid directory
2. if I want to do some experiment about changing the structure of network and changing the loss function, where should I modify?