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remove unnecessary scripts and update output to multiple images

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This commit is contained in:
Denis Kochetov
2025-06-02 21:07:17 +00:00
parent 5311a5f0d5
commit 626a5ee60d
41 changed files with 41 additions and 8413 deletions
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nodes.py
+15 -15
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@@ -108,7 +108,6 @@ from Stable3DGen.pipeline_builders import StableGenPipelineBuilder
from MV_Adapter.mvadapter_node_utils import (
prepare_pipeline as mvadapter_prepare_pipeline,
run_pipeline as mvadapter_run_pipeline,
create_bg_remover,
prepare_t2mv_pipeline as mvadapter_prepare_t2mv_pipeline,
run_t2mv_pipeline as mvadapter_run_t2mv_pipeline
)
@@ -4886,10 +4885,6 @@ class MVAdapter_Image_To_MultiView:
if not mesh_path or not os.path.exists(mesh_path):
raise ValueError(f"Mesh path does not exist: {mesh_path}")
remove_bg_fn = None
if remove_background:
remove_bg_fn = create_bg_remover(DEVICE_STR)
num_views = 6
images, pos_images, normal_images, processed_ref_image = mvadapter_run_pipeline(
pipe=mvadapter_pipe,
@@ -4902,19 +4897,22 @@ class MVAdapter_Image_To_MultiView:
num_inference_steps=num_inference_steps,
guidance_scale=guidance_scale,
seed=seed,
remove_bg_fn=remove_bg_fn,
reference_conditioning_scale=reference_conditioning_scale,
negative_prompt=negative_prompt,
lora_scale=lora_scale,
device=DEVICE_STR,
)
grid_image = make_image_grid(images, rows=1)
# grid_image = make_image_grid(images, rows=1)
grid_tensor = pils_to_torch_imgs([grid_image], device=DEVICE_STR)
# grid_tensor = pils_to_torch_imgs([grid_image], device=DEVICE_STR)
print(f"Generated multiview images: {grid_tensor.shape}")
return (grid_tensor,)
# print(f"Generated multiview images: {grid_tensor.shape}")
# return (grid_tensor,)
# return images
return_images = pils_to_torch_imgs(images, device=DEVICE_STR)
return (return_images,)
class Load_MVAdapter_T2MV_Pipeline:
@@ -5033,11 +5031,13 @@ class MVAdapter_Text_To_MultiView:
)
# Create image grid
grid_image = make_image_grid(images, rows=1)
# grid_image = make_image_grid(images, rows=1)
# Convert PIL image to torch tensor using shared utils
grid_tensor = pils_to_torch_imgs([grid_image], device=DEVICE_STR)
# # Convert PIL image to torch tensor using shared utils
# grid_tensor = pils_to_torch_imgs([grid_image], device=DEVICE_STR)
print(f"Generated T2MV multiview images: {grid_tensor.shape}")
return (grid_tensor,)
# print(f"Generated T2MV multiview images: {grid_tensor.shape}")
# return (grid_tensor,)
return_images = pils_to_torch_imgs(images, device=DEVICE_STR)
return (return_images,)