ly015 / intrinsic_flow Goto Github PK

The download link for the DeepFashion dataset fails. Can you update it? Thanks!

Thanks for sharing your brilliant codes.
Here is a question. What is the variable d in line 146 of 'data/pose_transfer_dataset.py'?

when I run the test scripts with batch_size=8:

python scripts/test_pose_transfer_model.py --gpu_ids 0 --id PoseTransfer_0.5 --batch_size 8 --n_vis 8 --which_epoch best --save_output

the results look well:

but if I change batch_size to 1:

python scripts/test_pose_transfer_model.py --gpu_ids 0 --id PoseTransfer_0.5 --batch_size 1 --n_vis 8 --which_epoch best --save_output

the results are different and worse than batch_size=8

Hi. Thanks for the update.
By using the code for create_seg.py i am getting images for silhouette 24, silhouette6 like below, which is not giving accurately. Can you tell me how to get exact segmentation with silhouette. Can i change flength, near, far values in renderer function.
for silhouette 24, getting like this:


For silhouette 6 getting like this:

Thanks in advance.

Hello, Thank you for your great work
Can you provide this implementation in Python 3, Python 2 is no longer maintained and deprecated
Thank you

Hi ly015. Thanks for keeping the repository public available. Currently i am also working on same concept.
I have some doubts

1. How can we test the flow_regression_module.py ??
2. Can i train with my own data with some other segmentation concept like "https://github.com/Engineering-Course/CIHP_PGN"?
3. How to test for posetranser_0.1 (dual)?
   with hmr, now i am able to create visibility and flow_maps for my own data. But struck at segmentation. So can i use above mentioned segmentation??
   Your help is more helpful to me to go further.

Thanks & Regards,
SandhyaLaxmi

Hi, can you provide the code of generating 3d ground truth for flow map and visibility map?

Thanks for your brilliant code.

When I try to train a full model as you suggested:
"# full (need a pretrained pose transfer model without pixel warping)"

How do I select the pre-trained G epoch? I the REDME.md, you selected the 8-th epoch.
"--pretrained_G_id id_pose_4 --pretrained_G_epoch 8"

But according to my results obtained after training the model without pixel warp, the best model is 5-th epoch, and the visualization results suggest that the results from last epoch are more better than previous models. So, with what metric do you select the pre-trained model?

Hi Pro.Li! I want to ask how can i test on my dataset?
Thanks a lot!

hello, I wonder if we can use our own pictures(176x256 size) instead of deepfashion_datasets.
And how should we pre-process our dataset to use your pre-trained model?

Thanks for sharing your work.
I am interested in the Pixel Warping(section 3.5) of your paper. As I understand, pixel warping would work when the pose does not change much, cause the visiable region of reference pose can offer some details. When the pose changes drastically, the visiable region from reference image is almost non-existent, how the details from reference image could be added to the final result as the Fig. 8 (row 2,3,4) shows?

Hi, all datasets and models cannot be downloaded anymore.
Could you update the links in readme.md ?
Thanks!