It will compress the image size and the picture quality will become unclear

[Song367]

No description provided.

[AricGamma]

Can you show your cases? let me know what's the problem

[Song367]

Original image: 3466 ✖ 1942 . Output video: 512 ✖512

[Song367]

Can you show your cases? let me know what's the problem

The parameters are default, and the final output video resolution is 512 × 512.

[AricGamma]

You can modify data.source_image.width and data.source_image.height in the inference config to generate higher resolution videos. However, please be mindful of your VRAM usage.

[AricGamma]

Original image: 3466 ✖ 1942 . Output video: 512 ✖512

BTW, please use square images.

[Song367]

You can modify data.source_image.width and data.source_image.height in the inference config to generate higher resolution videos. However, please be mindful of your VRAM usage.

pipeline_output = pipeline(
ref_image=pixel_values_ref_img,
audio_tensor=audio_tensor,
face_emb=source_image_face_emb,
face_mask=source_image_face_region,
pixel_values_full_mask=source_image_full_mask,
pixel_values_face_mask=source_image_face_mask,
pixel_values_lip_mask=source_image_lip_mask,
width=1024,
height=1024,
video_length=clip_length,
num_inference_steps=config.inference_steps,
guidance_scale=config.cfg_scale,
generator=generator,
motion_scale=motion_scale,
)

change:
width=1024
height=1024

Traceback (most recent call last):
File "F:\workplace\hallo-webui\scripts\inference.py", line 424, in
inference_process(
File "F:\workplace\hallo-webui\scripts\inference.py", line 364, in inference_process
pipeline_output = pipeline(
File "F:\workplace\hallo-webui\venv\lib\site-packages\torch\utils_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "F:\workplace\hallo-webui\hallo\animate\face_animate.py", line 401, in call
noise_pred = self.denoising_unet(
File "F:\workplace\hallo-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1511, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "F:\workplace\hallo-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1520, in _call_impl
return forward_call(*args, **kwargs)
File "F:\workplace\hallo-webui\hallo\models\unet_3d.py", line 605, in forward
sample = sample + mask_cond_fea
RuntimeError: The size of tensor a (128) must match the size of tensor b (64) at non-singleton dimension 4

[AricGamma]

You can modify data.source_image.width and data.source_image.height in the inference config to generate higher resolution videos. However, please be mindful of your VRAM usage.

pipeline_output = pipeline( ref_image=pixel_values_ref_img, audio_tensor=audio_tensor, face_emb=source_image_face_emb, face_mask=source_image_face_region, pixel_values_full_mask=source_image_full_mask, pixel_values_face_mask=source_image_face_mask, pixel_values_lip_mask=source_image_lip_mask, width=1024, height=1024, video_length=clip_length, num_inference_steps=config.inference_steps, guidance_scale=config.cfg_scale, generator=generator, motion_scale=motion_scale, )

change: width=1024 height=1024

Traceback (most recent call last): File "F:\workplace\hallo-webui\scripts\inference.py", line 424, in inference_process( File "F:\workplace\hallo-webui\scripts\inference.py", line 364, in inference_process pipeline_output = pipeline( File "F:\workplace\hallo-webui\venv\lib\site-packages\torch\utils_contextlib.py", line 115, in decorate_context return func(*args, **kwargs) File "F:\workplace\hallo-webui\hallo\animate\face_animate.py", line 401, in call noise_pred = self.denoising_unet( File "F:\workplace\hallo-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1511, in _wrapped_call_impl return self._call_impl(*args, **kwargs) File "F:\workplace\hallo-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1520, in _call_impl return forward_call(*args, **kwargs) File "F:\workplace\hallo-webui\hallo\models\unet_3d.py", line 605, in forward sample = sample + mask_cond_fea RuntimeError: The size of tensor a (128) must match the size of tensor b (64) at non-singleton dimension 4

Do not modify the code. Just modify the data.source_image.width and data.source_image.height in configs/inference/default.yaml.

[Song367]

您可以在推理配置中修改 data.source_image.width 和 data.source_image.height 以生成更高分辨率的视频。但是，请注意 VRAM 的使用情况。

pipeline_output = pipeline(ref_image=pixel_values_ref_img, audio_tensor=audio_tensor, face_emb=source_image_face_emb, face_mask=source_image_face_region, pixel_values_full_mask=source_image_full_mask, pixel_values_face_mask=source_image_face_mask, pixel_values_lip_mask=source_image_lip_mask, width=1024, height=1024, video_length=clip_length, num_inference_steps=config.inference_steps, guide_scale=config.cfg_scale, generator=generator, motion_scale=motion_scale, )
更改：宽度=1024 高度=1024
回溯（最近一次调用最后一次）：文件“F:\workplace\hallo-webui\scripts\inference.py”，第 424 行，在 inference_process 中（文件“F:\workplace\hallo-webui\scripts\inference.py”，第 364 行，在 inference_process 中pipeline_output = pipeline（文件“F:\workplace\hallo-webui\venv\lib\site-packages\torch\utils_contextlib.py”，第 115 行，在 decorate_context return func（args，kwargs）文件“F:\workplace\hallo-webui\hallo\animate\face_animate.py”，第 401 行，在call* noise_pred = self.denoising_unet（文件“F:\workplace\hallo-webui\venv\lib\site-packages\torch\nn\modules\module.py”，第 1511 行，在 _wrapped_call_impl return self._call_impl(*args，**kwargs) 文件“F:\workplace\hallo-webui\venv\lib\site-packages\torch\nn\modules\module.py”，第 1520 行，在 _call_impl 中返回 forward_call(*args，**kwargs) 文件“F:\workplace\hallo-webui\hallo\models\unet_3d.py”，第 605 行，在正向样本 = 样本 + mask_cond_fea RuntimeError：张量 a (128) 的大小必须与非单例维度 4 处的张量 b (64) 的大小匹配

不要修改代码。只需修改中的data.source_image.width和。data.source_image.height``configs/inference/default.yaml

I'll try

[abdur75648]

@Song367 Did it work?
Were you able to generate 1024 x 1024 frames?
Also, how was the quality? Is it just 512 x 512 resized or what?