Use ResizeHandleRow for z123 and svd (#168)
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@ -7,6 +7,7 @@ import modules.infotext_utils as parameters_copypaste
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from modules import script_callbacks
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from modules import script_callbacks
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from modules.paths import models_path
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from modules.paths import models_path
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from modules.ui_common import ToolButton, refresh_symbol
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from modules.ui_common import ToolButton, refresh_symbol
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from modules.ui_components import ResizeHandleRow
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from modules import shared
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from modules import shared
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from modules_forge.forge_util import numpy_to_pytorch, pytorch_to_numpy, write_images_to_mp4
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from modules_forge.forge_util import numpy_to_pytorch, pytorch_to_numpy, write_images_to_mp4
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@ -59,7 +60,7 @@ def predict(filename, width, height, video_frames, motion_bucket_id, fps, augmen
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def on_ui_tabs():
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def on_ui_tabs():
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with gr.Blocks() as svd_block:
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with gr.Blocks() as svd_block:
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with gr.Row():
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with ResizeHandleRow():
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with gr.Column():
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with gr.Column():
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input_image = gr.Image(label='Input Image', source='upload', type='numpy', height=400)
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input_image = gr.Image(label='Input Image', source='upload', type='numpy', height=400)
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@ -6,6 +6,7 @@ import pathlib
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from modules import script_callbacks
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from modules import script_callbacks
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from modules.paths import models_path
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from modules.paths import models_path
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from modules.ui_common import ToolButton, refresh_symbol
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from modules.ui_common import ToolButton, refresh_symbol
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from modules.ui_components import ResizeHandleRow
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from modules import shared
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from modules import shared
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from modules_forge.forge_util import numpy_to_pytorch, pytorch_to_numpy
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from modules_forge.forge_util import numpy_to_pytorch, pytorch_to_numpy
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@ -52,7 +53,7 @@ def predict(filename, width, height, batch_size, elevation, azimuth,
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def on_ui_tabs():
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def on_ui_tabs():
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with gr.Blocks() as model_block:
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with gr.Blocks() as model_block:
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with gr.Row():
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with ResizeHandleRow():
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with gr.Column():
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with gr.Column():
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input_image = gr.Image(label='Input Image', source='upload', type='numpy', height=400)
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input_image = gr.Image(label='Input Image', source='upload', type='numpy', height=400)
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