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@ -696,7 +696,7 @@ def install_modules(self):
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# resemble-enhance: |
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subprocess.call([pybin, "-m", "pip", "install", "git+https://github.com/daswer123/resemble-enhance-windows.git", "--no-dependencies", "--upgrade"]) |
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deep_path = os.path.join(os.path.dirname(os.path.abspath(__file__)),"deepspeed/deepspeed-0.12.4+unknown-py3-none-any.whl") |
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print(deep_speed) |
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print("deep_speed_path: "+deep_path) |
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import_module(self, "deepspeed", deep_path) |
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import_module(self, "librosa", "librosa") |
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import_module(self, "celluloid", "celluloid") |
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@ -1431,6 +1431,9 @@ def get_render_strip(self, context, strip):
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# Store current frame for later |
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bpy.context.scene.frame_current = int(strip.frame_start) |
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# if strip.type == "SCENE": |
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# bpy.data.scenes["Scene"].name |
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# make_meta to keep transforms |
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bpy.ops.sequencer.meta_make() |
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@ -1490,6 +1493,9 @@ def get_render_strip(self, context, strip):
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int(new_strip.frame_final_start + new_strip.frame_final_duration) - 1 |
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) |
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# Set the render settings for rendering animation with FFmpeg and MP4 with sound |
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bpy.context.scene.render.image_settings.file_format = "FFMPEG" |
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bpy.context.scene.render.ffmpeg.format = "MPEG4" |
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@ -3574,10 +3580,18 @@ class SEQUENCER_OT_generate_image(Operator):
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# dreamshaper-xl-lightning |
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elif do_convert == False and image_model_card == "Lykon/dreamshaper-xl-lightning": |
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from diffusers import AutoPipelineForText2Image |
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from diffusers import AutoPipelineForText2Image, AutoencoderKL |
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from diffusers import DPMSolverMultistepScheduler |
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pipe = AutoPipelineForText2Image.from_pretrained('Lykon/dreamshaper-xl-lightning', torch_dtype=torch.float16, variant="fp16") |
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vae = AutoencoderKL.from_pretrained( |
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"madebyollin/sdxl-vae-fp16-fix", |
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torch_dtype=torch.float16, |
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local_files_only=local_files_only, |
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) |
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#from diffusers import EulerAncestralDiscreteScheduler |
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pipe = AutoPipelineForText2Image.from_pretrained('Lykon/dreamshaper-xl-lightning', torch_dtype=torch.float16, variant="fp16", vae=vae) |
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pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config) |
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#pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config) |
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pipe = pipe.to(gfx_device) |
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# Wuerstchen |
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@ -4161,7 +4175,7 @@ class SEQUENCER_OT_generate_image(Operator):
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# DreamShaper |
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elif image_model_card == "Lykon/dreamshaper-8" and do_convert == False: |
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elif image_model_card == "Lykon/dreamshaper-8": |
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image = pipe( |
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prompt=prompt, |
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negative_prompt=negative_prompt, |
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@ -4175,17 +4189,17 @@ class SEQUENCER_OT_generate_image(Operator):
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).images[0] |
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# dreamshaper-xl-lightning |
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elif image_model_card == "Lykon/dreamshaper-xl-lightning" and do_convert == False: |
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elif image_model_card == "Lykon/dreamshaper-xl-lightning": |
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image = pipe( |
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prompt=prompt, |
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negative_prompt=negative_prompt, |
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num_inference_steps=4, |
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guidance_scale=2, |
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guidance_scale=image_num_guidance, |
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height=y, |
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width=x, |
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generator=generator, |
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output_type="pil", |
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).images[0] |
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#output_type="pil", |
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).images[0] |
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# OpenPose |
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elif image_model_card == "lllyasviel/sd-controlnet-openpose": |
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@ -4967,11 +4981,11 @@ class SEQUENCER_OT_strip_to_generatorAI(Operator):
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if type == "image": |
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sequencer.generate_image() |
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context.scene.generate_movie_prompt = prompt |
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scene.generate_movie_negative_prompt = negative_prompt |
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#context.scene.generate_movie_prompt = prompt |
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#scene.generate_movie_negative_prompt = negative_prompt |
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context.scene.movie_use_random = use_random |
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context.scene.movie_num_seed = seed |
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scene.generate_movie_prompt = prompt |
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#scene.generate_movie_prompt = prompt |
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scene.generate_movie_negative_prompt = negative_prompt |
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if use_strip_data: |
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