HelloSun commited on
Commit
3d65110
1 Parent(s): 0d9dabb

Update app.py

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Files changed (1) hide show
  1. app.py +7 -2
app.py CHANGED
@@ -2,6 +2,9 @@ import gradio as gr
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  import numpy as np
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  from optimum.intel import OVStableDiffusionPipeline, OVStableDiffusionXLPipeline, OVLatentConsistencyModelPipeline
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  from diffusers.pipelines.stable_diffusion import StableDiffusionSafetyChecker
 
 
 
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  # model_id = "echarlaix/sdxl-turbo-openvino-int8"
@@ -12,17 +15,19 @@ from diffusers.pipelines.stable_diffusion import StableDiffusionSafetyChecker
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  model_id = "OpenVINO/LCM_Dreamshaper_v7-int8-ov"
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  #pipeline = OVLatentConsistencyModelPipeline.from_pretrained(model_id, compile=False, safety_checker=safety_checker)
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  pipeline = OVLatentConsistencyModelPipeline.from_pretrained(model_id, compile=False)
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-
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  batch_size, num_images, height, width = 1, 1, 512, 512
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  pipeline.reshape(batch_size=batch_size, height=height, width=width, num_images_per_prompt=num_images)
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  pipeline.compile()
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  def infer(prompt, num_inference_steps):
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  image = pipeline(
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  prompt = prompt,
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- #negative_prompt = negative_prompt, #no negative_prompt keyword in LatentConsistencyPipelineMixin
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  # guidance_scale = guidance_scale,
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  num_inference_steps = num_inference_steps,
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  width = width,
 
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  import numpy as np
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  from optimum.intel import OVStableDiffusionPipeline, OVStableDiffusionXLPipeline, OVLatentConsistencyModelPipeline
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  from diffusers.pipelines.stable_diffusion import StableDiffusionSafetyChecker
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+ from diffusers import DiffusionPipeline
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+
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+
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  # model_id = "echarlaix/sdxl-turbo-openvino-int8"
 
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  model_id = "OpenVINO/LCM_Dreamshaper_v7-int8-ov"
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  #pipeline = OVLatentConsistencyModelPipeline.from_pretrained(model_id, compile=False, safety_checker=safety_checker)
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  pipeline = OVLatentConsistencyModelPipeline.from_pretrained(model_id, compile=False)
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+ pipeline.load_lora_weights("EvilEngine/easynegative")
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  batch_size, num_images, height, width = 1, 1, 512, 512
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  pipeline.reshape(batch_size=batch_size, height=height, width=width, num_images_per_prompt=num_images)
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  pipeline.compile()
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+ negative_prompt="easynegative"
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+
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  def infer(prompt, num_inference_steps):
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  image = pipeline(
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  prompt = prompt,
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+ negative_prompt = negative_prompt, #no negative_prompt keyword in LatentConsistencyPipelineMixin
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  # guidance_scale = guidance_scale,
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  num_inference_steps = num_inference_steps,
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  width = width,