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app.py
CHANGED
@@ -25,7 +25,7 @@ from lxml.html import fromstring
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from diffusers.utils import export_to_video, load_image
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from huggingface_hub import hf_hub_download
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from safetensors.torch import load_file, save_file
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from diffusers import FluxPipeline,
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from PIL import Image, ImageDraw, ImageFont
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# logging
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@@ -43,10 +43,8 @@ root.addHandler(handler)
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if torch.cuda.is_available():
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device = "cuda"
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dtype = torch.bfloat16
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else:
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device = "cpu"
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dtype = torch.bfloat16
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base = "black-forest-labs/FLUX.1-schnell"
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@@ -57,13 +55,13 @@ additional_image = None
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# precision data
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seq=512
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fps=
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width=768
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height=
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image_steps=8
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video_steps=50
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img_accu=9
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vid_accu=
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# ui data
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@@ -126,10 +124,13 @@ function custom(){
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# torch pipes
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image_pipe = FluxPipeline.from_pretrained(base, torch_dtype=
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torch_dtype=
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).to(device)
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video_pipe.vae.enable_tiling()
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@@ -246,12 +247,12 @@ def handle_generate(*_inp):
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if len(inp[2]) >= 2:
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inp[2] = "," + inp[2].strip(",").strip(" ")
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inp[2] = f"textual
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if len(inp[1]) >= 2:
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inp[1] = "," + inp[1].strip(",").strip(" ")
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inp[1] = f'
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print(f"""
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from diffusers.utils import export_to_video, load_image
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from huggingface_hub import hf_hub_download
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from safetensors.torch import load_file, save_file
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from diffusers import FluxPipeline, HunyuanVideoPipeline, HunyuanVideoTransformer3DModel
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from PIL import Image, ImageDraw, ImageFont
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# logging
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if torch.cuda.is_available():
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device = "cuda"
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else:
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device = "cpu"
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base = "black-forest-labs/FLUX.1-schnell"
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# precision data
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seq=512
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fps=15
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width=768
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height=512
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image_steps=8
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video_steps=50
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img_accu=9
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vid_accu=7
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# ui data
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# torch pipes
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image_pipe = FluxPipeline.from_pretrained(base, torch_dtype=torch.float32).to(device)
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transformer = HunyuanVideoTransformer3DModel.from_pretrained(
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"hunyuanvideo-community/HunyuanVideo", subfolder="transformer", torch_dtype=torch.bfloat16
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)
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video_pipe = HunyuanVideoPipeline.from_pretrained(
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"hunyuanvideo-community/HunyuanVideo", transformer=transformer, torch_dtype=torch.bfloat16
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).to(device)
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video_pipe.vae.enable_tiling()
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if len(inp[2]) >= 2:
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inp[2] = "," + inp[2].strip(",").strip(" ")
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inp[2] = f"textual,labeled,divined,distorted,discontinuous,ugly,blurry,low resolution,motionless,static,wrong body anatomy{inp[2]}"
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if len(inp[1]) >= 2:
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inp[1] = "," + inp[1].strip(",").strip(" ")
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inp[1] = f'realistic,natural,genuine,reasonable,highly detailed{inp[1]}'
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print(f"""
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