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https://github.com/modelscope/DiffSynth-Studio.git
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update z-image-i2L examples
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@@ -38,9 +38,9 @@ pipe = ZImagePipeline.from_pretrained(
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snapshot_download(
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model_id="DiffSynth-Studio/Z-Image-i2L",
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allow_file_pattern="assets/style/*",
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local_dir="data/style_input"
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local_dir="data/Z-Image-i2L_style_input"
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)
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images = [Image.open(f"data/style_input/assets/style/1/{i}.jpg") for i in range(6)]
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images = [Image.open(f"data/Z-Image-i2L_style_input/assets/style/1/{i}.jpg") for i in range(4)]
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# Image to LoRA
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with torch.no_grad():
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@@ -54,7 +54,7 @@ negative_prompt = "泛黄,发绿,模糊,低分辨率,低质量图像,
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image = pipe(
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prompt=prompt,
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negative_prompt=negative_prompt,
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seed=0, cfg_scale=7, num_inference_steps=50,
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seed=0, cfg_scale=4, num_inference_steps=50,
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positive_only_lora=lora,
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sigma_shift=8
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)
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@@ -38,9 +38,9 @@ pipe = ZImagePipeline.from_pretrained(
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snapshot_download(
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model_id="DiffSynth-Studio/Z-Image-i2L",
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allow_file_pattern="assets/style/*",
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local_dir="data/style_input"
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local_dir="data/Z-Image-i2L_style_input"
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)
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images = [Image.open(f"data/style_input/assets/style/1/{i}.jpg") for i in range(6)]
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images = [Image.open(f"data/Z-Image-i2L_style_input/assets/style/1/{i}.jpg") for i in range(4)]
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# Image to LoRA
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with torch.no_grad():
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@@ -54,7 +54,7 @@ negative_prompt = "泛黄,发绿,模糊,低分辨率,低质量图像,
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image = pipe(
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prompt=prompt,
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negative_prompt=negative_prompt,
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seed=0, cfg_scale=7, num_inference_steps=50,
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seed=0, cfg_scale=4, num_inference_steps=50,
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positive_only_lora=lora,
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sigma_shift=8
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)
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