Comments (4)
champ use SMPL to generate depth, normal and semantic map image.
from champ.
could you please share your custom node
from champ.
The node is just an experiment, normal/depth preprocs can work if the source resembles the SMPL mesh, but the normal map background should be removed which is missing from the initial test workflow. You can get some sort of results using only DWpose as well with some inputs.
from champ.
Hi there, we have now released the rendering & SMPL code. There are some gap on the rendered conditions, especially for Semantic_map
. You can follow the instructions on README.md
. Let me know if it solve your problem.
from champ.
Related Issues (20)
- memory usage
- FileNotFoundError: [Errno 2] No such file or directory:
- semantic map from SMPL
- Train & Test Data Split HOT 1
- basicModel_neutral_lbs_10_207_0_v1.0.0.pkl HOT 5
- Improving results with anime characters HOT 1
- Hardware and data requirements for model training. HOT 3
- How to avoid distortion of facial and hand features in generated videos HOT 4
- Free guidance: IndexError: The shape of the mask [0] at index 0 does not match the shape of the indexed tensor [1, 9216, 320] at index 0 HOT 3
- Organization of training data per the README causes errors HOT 6
- cuda out of memory HOT 2
- when i test my video, i have error HOT 3
- A problem about scaled_focal_length during motion datas producing HOT 1
- Transfer SMPL HOT 2
- [MISSING FILE] SMPL_NEUTRAL.pkl
- raise ValueError('Invalid device ID ({})'.format(device_id, len(devices))), ValueError: Invalid device ID (0) HOT 1
- High memory usage for inference HOT 1
- reference image HOT 6
- how can I get "--reference_path reference_imgs/smpl_results/your_ref_img_A.npy"? HOT 1
- Have you try to use SDXL for training?If chang from SD1.5 to SDXL will further to improve performance?
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from champ.