opened
neonb88
username_0
Don't mean to be rude.  I appreciate what documentation you've written.  But it's still pretty unclear to me.

Does it fit the clothes in the `test_data.pkl` file to the SMPL approximation of the body also in `test_data.pkl`?  If so, why are
1. `visualize_scan.py`
2. `visualize_garments.py`
3.  `dress_SMPL.py`

also necessary?  I expect I will understand this well enough by the time you address this answer, but a high level description of each of the 4 `.py` files would still probably help future readers

===============================================
===============================================
===============================================

My current understanding is:

1.  `visualize_scan.py` allows us to create a SMPL model that best approximates the 1-8 images, PGN segmentations, and openpose keypoints, (and then dresses?  right now my understanding is that `visualize_scan.py` **_doesn't_** do any clothes)
2.  `visualize_garments.py` doesn't allow us to swap in our own body (scan info)
3.  `dress_SMPL.py`: I'm not sure how this is different from `visualize_garments.py`.

I will update as I start to understand better.  If anything, it will be useful notes for me, and hopefully for others

Cheers,
Nathan
What does `test_network.py` actually do?
issue
created
bharat-b7
username_1
Hi,
Sorry for the confusion. I'll try to update the descriptions asap.
For now here's a brief clarifications:
1. visualize_scan.py, just loads a scan (not SMPL) and visualizes segmentation and texture on top. It has nothing to do with SMPL registration or garments.
2. visualize_garments.py, visualizes garments on their original SMPL body (with original pose and shape).
3. dress_SMPL.py, allows to select garments from digital wardrobe and dress any SMPL body (user can supply pose and shape parameters)

Hope this helps.
Best,
Bharat
comment
created
neonb88
username_0
Hi,

Thanks for your prompt reply. The whole pipeline is very impressive and obviously took a lot of time and effort.

In that case, I think `dress_smpl.py` currently fits my main needs

Cheers,
Nathan
comment
created
neonb88
username_0
Oh also, I edited some of your code to work with python3.7, and when I ran `test_network.py` the clothing looked a little strange.  I can send photos when I get back to my laptop. Should I do something to fix this?

Thanks again,
Nathan
comment
created
bharat-b7
username_1
Thanks for the update. if you could share the images, we can take a look at what could be going wrong. A fix would be great!
comment
created
neonb88
username_0
Hi.  At this point I don't remember the exact conditions under which I ran this, but here's the image anyway.  Maybe it can help someone else
![mgn_failure_Feb_23_2020](https://user-images.githubusercontent.com/5565691/75733581-b7305e80-5cc3-11ea-889c-8b28a7e239ea.png)
comment
created
bharat-b7
username_1
This seems weird. Do you have the results for MGN prediction before the 2D refinement step?
comment
created
neonb88
username_0
@username_1  Can address that later, but of more importance to me is a simple question:  does this code recommend clothing that might fit a person (ie. given 1. a SMPL mesh and 2. a clothing mesh/registration/whatever you call it, can MGN output 3. a score predicting how good the clothes will fit on the person)
comment
created
bharat-b7
username_1
MGN predicts the 3D body (SMPL parameters) and garment meshes based on the input images.
I'm afraid MGN cannot predict quality of fit.
comment
created
neonb88
username_0
Okay.  Thank you
comment
closed
bharat-b7
username_1
issue
created
xiezhy6
username_2
Hi,
Thanks for your excellent work. I have just come up with this topic, so maybe my question is a little trivial.
When I finished running the test_network.py, I can find any result file in my directory. My question is How can I get the result file after running the test_network.py script and what datas should I save?

Thanks again!
Zhenyu
comment