nodes/banodoco-steerable-motion
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Updated to new IPAdapter + fixes

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IDGallagher
2024-05-13 17:22:15 +01:00
parent 5e207a8c7c
commit 2a4768b32f
8 changed files with 2467 additions and 471 deletions
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SteerableMotion.py
+2 -2
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@@ -565,11 +565,11 @@ class BatchCreativeInterpolationNode:
for i, bin in enumerate(bins):
ipadapter_application = IPAdapterBatchImport()
negative_noise = torch.cat(bin.noiseBatch, dim=0) if len(bin.noiseBatch) > 0 else None
model, = ipadapter_application.apply_ipadapter(model=model, ipadapter=ipadapter, image=torch.cat(bin.imageBatch, dim=0), weight=[x * base_ipa_advanced_settings["ipa_weight"] for x in bin.weight_schedule], weight_type=base_ipa_advanced_settings["ipa_weight_type"], start_at=base_ipa_advanced_settings["ipa_starts_at"], end_at=base_ipa_advanced_settings["ipa_ends_at"], clip_vision=clip_vision,image_negative=negative_noise,embeds_scaling=base_ipa_advanced_settings["ipa_embeds_scaling"], image_schedule=bin.image_schedule)
model, *_ = ipadapter_application.apply_ipadapter(model=model, ipadapter=ipadapter, image=torch.cat(bin.imageBatch, dim=0), weight=[x * base_ipa_advanced_settings["ipa_weight"] for x in bin.weight_schedule], weight_type=base_ipa_advanced_settings["ipa_weight_type"], start_at=base_ipa_advanced_settings["ipa_starts_at"], end_at=base_ipa_advanced_settings["ipa_ends_at"], clip_vision=clip_vision,image_negative=negative_noise,embeds_scaling=base_ipa_advanced_settings["ipa_embeds_scaling"], encode_batch_size=1, image_schedule=bin.image_schedule)
if high_detail_mode:
tiled_ipa_application = IPAdapterTiledBatchImport()
negative_noise = torch.cat(bin.bigNoiseBatch, dim=0) if len(bin.bigNoiseBatch) > 0 else None
model, *_ = tiled_ipa_application.apply_tiled(model=model, ipadapter=ipadapter, image=torch.cat(bin.bigImageBatch, dim=0), weight=[x * detail_ipa_advanced_settings["ipa_weight"] for x in bin.weight_schedule], weight_type=detail_ipa_advanced_settings["ipa_weight_type"], start_at=detail_ipa_advanced_settings["ipa_starts_at"], end_at=detail_ipa_advanced_settings["ipa_ends_at"], clip_vision=clip_vision,sharpening=0.1,image_negative=negative_noise,embeds_scaling=detail_ipa_advanced_settings["ipa_embeds_scaling"], image_schedule=bin.image_schedule)
model, *_ = tiled_ipa_application.apply_tiled(model=model, ipadapter=ipadapter, image=torch.cat(bin.bigImageBatch, dim=0), weight=[x * detail_ipa_advanced_settings["ipa_weight"] for x in bin.weight_schedule], weight_type=detail_ipa_advanced_settings["ipa_weight_type"], start_at=detail_ipa_advanced_settings["ipa_starts_at"], end_at=detail_ipa_advanced_settings["ipa_ends_at"], clip_vision=clip_vision,sharpening=0.1,image_negative=negative_noise,embeds_scaling=detail_ipa_advanced_settings["ipa_embeds_scaling"], encode_batch_size=1, image_schedule=bin.image_schedule)
comparison_diagram, = plot_weight_comparison(all_cn_frame_numbers, all_cn_weights, all_ipa_frame_numbers, all_ipa_weights, buffer)
return comparison_diagram, positive, negative, model, sparse_indexes, last_key_frame_position, buffer