Comments (4)
Welche Option ist hierfür bitte besser?
usage: inference.py [-h] [--driven_audio DRIVEN_AUDIO] [--source_image SOURCE_IMAGE] [--ref_eyeblink REF_EYEBLINK] [--ref_pose REF_POSE] [--checkpoint_dir CHECKPOINT_DIR] [--result_dir RESULT_DIR] [--pose_style POSE_STYLE] [--batch_size BATCH_SIZE] [--size SIZE] [--expression_scale EXPRESSION_SCALE] [--input_yaw INPUT_YAW [INPUT_YAW ...]] [--input_pitch INPUT_PITCH [INPUT_PITCH ...]] [--input_roll INPUT_ROLL [INPUT_ROLL ...]] [--enhancer ENHANCER] [--background_enhancer BACKGROUND_ENHANCER] [--cpu] [--face3dvis] [--still] [--preprocess {crop,extcrop,resize,full,extfull}] [--verbose] [--old_version] [--net_recon {resnet18,resnet34,resnet50}] [--init_path INIT_PATH] [--use_last_fc USE_LAST_FC] [--bfm_folder BFM_FOLDER] [--bfm_model BFM_MODEL] [--focal FOCAL] [--center CENTER] [--camera_d CAMERA_D] [--z_near Z_NEAR] [--z_far Z_FAR]
Option 1: Using --size
for fixed sizes
img = 'examples/source_image/{}.png'.format(default_head_name.value)
!python3.8 inference.py --driven_audio ./examples/driven_audio/audio_profile.mp3 \
--source_image {img} \
--result_dir ./results --still --preprocess full --enhancer gfpgan --size 1080,1920
Option 2: Using --preprocess resize
for aspect ratio adjustment
img = 'examples/source_image/{}.png'.format(default_head_name.value)
!python3.8 inference.py --driven_audio ./examples/driven_audio/audio_profile.mp3 \
--source_image {img} \
--result_dir ./results --still --preprocess resize --enhancer gfpgan
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Which option is better to this please ?
usage: inference.py [-h] [--driven_audio DRIVEN_AUDIO] [--source_image SOURCE_IMAGE]
[--ref_eyeblink REF_EYEBLINK] [--ref_pose REF_POSE]
[--checkpoint_dir CHECKPOINT_DIR] [--result_dir RESULT_DIR]
[--pose_style POSE_STYLE] [--batch_size BATCH_SIZE] [--size SIZE]
[--expression_scale EXPRESSION_SCALE] [--input_yaw INPUT_YAW [INPUT_YAW ...]]
[--input_pitch INPUT_PITCH [INPUT_PITCH ...]]
[--input_roll INPUT_ROLL [INPUT_ROLL ...]] [--enhancer ENHANCER]
[--background_enhancer BACKGROUND_ENHANCER] [--cpu] [--face3dvis] [--still]
[--preprocess {crop,extcrop,resize,full,extfull}] [--verbose] [--old_version]
[--net_recon {resnet18,resnet34,resnet50}] [--init_path INIT_PATH]
[--use_last_fc USE_LAST_FC] [--bfm_folder BFM_FOLDER] [--bfm_model BFM_MODEL]
[--focal FOCAL] [--center CENTER] [--camera_d CAMERA_D] [--z_near Z_NEAR]
[--z_far Z_FAR]
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Hello, i am confused with this problem too. I am working woth an image size of 2000*2000. By adding --size 2000 2000 at the end of my command (Option 1) , i got an error :unrecognized arguments: 2000. Then, I added merely --size 2000. The error turned into: FileNotFoundError: No such file or directory: "./checkpoints\SadTalker_V0.0.2_2000.safetensors". Do you know how to solve this issue? Many thanks
from sadtalker.
Hello, i am confused with this problem too. I am working woth an image size of 2000*2000. By adding --size 2000 2000 at the end of my command (Option 1) , i got an error :unrecognized arguments: 2000. Then, I added merely --size 2000. The error turned into: FileNotFoundError: No such file or directory: "./checkpoints\SadTalker_V0.0.2_2000.safetensors". Do you know how to solve this issue? Many thanks
Hey @Zeelyne,
I noticed that you're facing some issues with running the SadTalker inference script. I've identified a couple of potential issues with your command and have provided a solution below:
Fix for Unrecognized Arguments and FileNotFoundError
-
Size Argument Format:
The--size
argument should be in a comma-separated format like--size 2000,2000
instead of--size 2000 2000
. -
Checkpoint File:
Ensure that the checkpoint fileSadTalker_V0.0.2_2000.safetensors
is present in the./checkpoints
directory.
Updated Command
Here's the updated command:
img = 'examples/source_image/{}.png'.format(default_head_name.value)
!python3.8 inference.py --driven_audio ./examples/driven_audio/audio_profile.mp3 \
--source_image {img} \
--result_dir ./results --still --preprocess full --enhancer gfpgan --size 2000,2000
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