Update deformes4D_engine.py
Browse files- deformes4D_engine.py +4 -1
deformes4D_engine.py
CHANGED
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@@ -141,15 +141,18 @@ class Deformes4DEngine:
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conditioning_items = []
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if eco_latent_for_next_loop is None:
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img_start = self._preprocess_image_for_latent_conversion(Image.open(start_keyframe_path).convert("RGB"), target_resolution_tuple)
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conditioning_items.append(LatentConditioningItem(self.pil_to_latent(img_start), 0, 1.0))
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else:
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conditioning_items.append(LatentConditioningItem(eco_latent_for_next_loop, 0, 1.0))
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conditioning_items.append(LatentConditioningItem(dejavu_latent_for_next_loop, DEJAVU_FRAME_TARGET, handler_strength))
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img_dest = self._preprocess_image_for_latent_conversion(Image.open(destination_keyframe_path).convert("RGB"), target_resolution_tuple)
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conditioning_items.append(LatentConditioningItem(self.pil_to_latent(img_dest), DESTINATION_FRAME_TARGET, destination_convergence_strength))
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-
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current_ltx_params = {**base_ltx_params, "motion_prompt": motion_prompt}
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latents_brutos = self._generate_latent_tensor_internal(conditioning_items, current_ltx_params, target_resolution_tuple, total_frames_brutos)
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conditioning_items = []
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if eco_latent_for_next_loop is None:
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logger.info(" - Primeiro fragmento: Usando Keyframe inicial como 芒ncora de partida.")
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img_start = self._preprocess_image_for_latent_conversion(Image.open(start_keyframe_path).convert("RGB"), target_resolution_tuple)
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conditioning_items.append(LatentConditioningItem(self.pil_to_latent(img_start), 0, 1.0))
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else:
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logger.info(" - 脗ncora 1: Eco Causal (C) - Heran莽a do passado.")
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conditioning_items.append(LatentConditioningItem(eco_latent_for_next_loop, 0, 1.0))
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logger.info(" - 脗ncora 2: D茅j脿-Vu (D) - Mem贸ria de um futuro idealizado.")
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conditioning_items.append(LatentConditioningItem(dejavu_latent_for_next_loop, DEJAVU_FRAME_TARGET, handler_strength))
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img_dest = self._preprocess_image_for_latent_conversion(Image.open(destination_keyframe_path).convert("RGB"), target_resolution_tuple)
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conditioning_items.append(LatentConditioningItem(self.pil_to_latent(img_dest), DESTINATION_FRAME_TARGET, destination_convergence_strength))
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current_ltx_params = {**base_ltx_params, "motion_prompt": motion_prompt}
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latents_brutos = self._generate_latent_tensor_internal(conditioning_items, current_ltx_params, target_resolution_tuple, total_frames_brutos)
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