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update z-image-i2L examples

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Artiprocher
2026-01-27 12:16:48 +08:00
parent d12bf71bcc
commit 3f4de2cc7f
2 changed files with 6 additions and 6 deletions
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6
examples/z_image/model_inference/Z-Image-i2L.py
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@@ -38,9 +38,9 @@ pipe = ZImagePipeline.from_pretrained(
snapshot_download( snapshot_download(
model_id="DiffSynth-Studio/Z-Image-i2L", model_id="DiffSynth-Studio/Z-Image-i2L",
allow_file_pattern="assets/style/*", allow_file_pattern="assets/style/*",
local_dir="data/style_input" local_dir="data/Z-Image-i2L_style_input"
) )
images = [Image.open(f"data/style_input/assets/style/1/{i}.jpg") for i in range(6)] images = [Image.open(f"data/Z-Image-i2L_style_input/assets/style/1/{i}.jpg") for i in range(4)]
# Image to LoRA # Image to LoRA
with torch.no_grad(): with torch.no_grad():
@@ -54,7 +54,7 @@ negative_prompt = "泛黄，发绿，模糊，低分辨率，低质量图像，
image = pipe( image = pipe(
prompt=prompt, prompt=prompt,
negative_prompt=negative_prompt, negative_prompt=negative_prompt,
seed=0, cfg_scale=7, num_inference_steps=50, seed=0, cfg_scale=4, num_inference_steps=50,
positive_only_lora=lora, positive_only_lora=lora,
sigma_shift=8 sigma_shift=8
) )

6
examples/z_image/model_inference_low_vram/Z-Image-i2L.py
View File

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