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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.
The text was updated successfully, but these errors were encountered:
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.
Neither was the first run.
Thanks.
The text was updated successfully, but these errors were encountered: