HRN
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Cmd command takes 25 sec while modelscope takes 1 sec
Hi. Im new in python. Below command takes 25 sec to producing results. 100% 1/1 [00:26<00:00, 26.75s/it]
CUDA_VISIBLE_DEVICES=0 python demo.py --input_type single_view --input_root ./assets/examples/single_view_image --output_root ./assets/examples/single_view_image_results
But with the modelscope you provided in googlecolab in homepage, it takes 1 sec to producing results.
face_reconstruction = pipeline(Tasks.face_reconstruction, model='damo/cv_resnet50_face-reconstruction', model_revision='v2.0.0-HRN')
result = face_reconstruction('first_frame.jpg')
Neither was the first run.
- Why does it take so long to run with the first method?
- First method also accepts multiple_view, while second method accepts only one image. Is there any way to give multiple images?
- First method creates both mid and high-frequency mesh while second method creates only mid-frequency mesh. Is there a high-frequency mesh generation method in the second method? Any code changes?
- My nose is crooked. HRN does not represent correctly high curved things like my nose from front view. I know the faces in the dataset it was trained on were shapely faces, but wouldn't it adequately represent people with facial paralysis?
- What I wrote in item 4 was for photographs taken from the front view. In side view If the nose is arched, the reprensentation does not fit properly.
Thanks.