Hi! I'm new to the way your code organizes and I wonder where the output of the model is. And how to visualize it using the utils3d tools? Many thanks!

Hi, according to the tutorial, I have realized the visualization of test results of the real word dataset, which depends on the input of depth images and RGB images. However, how to visualize the test results of the shape2motion dataset? Thank you very much for your help!

Hello, we have tested using the pre-trained model provided in this paper, but the results seem to be incorrect. Where may there be a problem? We haven't changed the program code during this period. Thank you for your reply.

Hi,

I notice that in the demo, the laptop is converted from depth image to camera coordinate, then to world coordinate. What's the reason to convert into the world coordinate? Does it promise that the object is in the canonical object space?

When training on the shape2motion data, is the training data in the canonical object space (with a canonical pose)? Or it's just in the camera coordinate

Hi,

Thanks for your great work. When going through the demo code, I don't quite understand about the recenter process. Can you help exaplain a bit. Based on my current understanding, the pivot point has been the averaged motion origin. Why do we want another recenter operation? What's the use of the double cross?

if recenter: pivot_point = np.cross(axis, np.cross(pivot_point, axis))

Hi, I'd like to ask what data are contained in camera2base.json file? It looks like the pose of the camera, but what does the base coordinate system mean?

I have been replicating the visualization result shown in demo_depth_map.ipynb (https://github.com/UT-Austin-RPL/Ditto/blob/master/notebooks/demo_depth_map.ipynb). The following are the steps I executed:

1. Clone the Ditto repo and create a virtual env in PyCharm. (Python 3.8.10). Then perform the rest in the created virtual env.
2. install the required packages by 'pip install -r requirements.txt'
3. build the dependencies by 'python scripts/convonet_setup.py build_ext --inplace'
4. collect all the required data and put them under root/data directory, following the README.m (https://github.com/UT-Austin-RPL/Ditto#data-and-pre-trained-models, https://utexas.box.com/s/ujb2ky8y9vaog7nheth1n3tmm1rgx9t7, https://utexas.box.com/s/a4h001b3ciicrt3f71t4xd3wjsm04be7, https://utexas.box.com/s/zbf5bja20n2w6umryb1bcfbbcm3h2ysn)
5. install an older version of utils3d by 'pip install git+git://github.com/Steve-Tod/utils3d.git@bbd72687404436b37c90230a572891075aa8a53b' because the Pyrenderer in the newest located at a different path and will cause error when executing in my env.
6. Then I directly run all the cells in demo_depth_map.ipynb, and get the following results (from different viewpoints)

The prismatic joint axis looks different from the demo and meshes of both digital twins from my result seem to be incomplete.

Below are the pic from demo.

Hello , this error comes when I do the Training , Is there any solution

File "C:\Users\Labor\anaconda3\envs\Ditto\lib\runpy.py", line 234, in _get_code_from_file with io.open_code(decoded_path) as f: FileNotFoundError: [Errno 2] No such file or directory: 'C:\Users\Labor\Digital-Twin\Ditto\logs\runs\2022-05-19\Ditto_s2m-10-04-35\run.py'