Update app.py

app.py

@@ -1,58 +1,18 @@
 import gradio as gr
-import numpy as np
-from optimum.intel import OVStableDiffusionPipeline, OVStableDiffusionXLPipeline, OVLatentConsistencyModelPipeline
-from optimum.intel.openvino.modeling_diffusion import OVModelVaeDecoder, OVBaseModel
-from diffusers.pipelines.stable_diffusion import StableDiffusionSafetyChecker
-from diffusers import DiffusionPipeline
-from diffusers.schedulers import EulerDiscreteScheduler
-import openvino.runtime as ov
-from typing import Optional, Dict
-from huggingface_hub import snapshot_download
+from optimum.intel import OVStableDiffusionPipeline
 
-#model_id = "echarlaix/sdxl-turbo-openvino-int8"
-#model_id = "echarlaix/LCM_Dreamshaper_v7-openvino"
-#model_id = "OpenVINO/LCM_Dreamshaper_v7-int8-ov"
 model_id = "yujiepan/dreamshaper-8-lcm-openvino-w8a8"
-
-#safety_checker = StableDiffusionSafetyChecker.from_pretrained("CompVis/stable-diffusion-safety-checker")
-
-
-#pipeline = OVLatentConsistencyModelPipeline.from_pretrained(model_id, compile=False, safety_checker=safety_checker)
-#pipeline = OVLatentConsistencyModelPipeline.from_pretrained(model_id, compile=False, device='CPU',)
-pipeline = OVStableDiffusionPipeline.from_pretrained(model_id, device='CPU',)
-#batch_size, num_images, height, width = 1, 1, 512, 512
-#pipeline.reshape(batch_size=batch_size, height=height, width=width, num_images_per_prompt=num_images)
-
-#不可用lora
-#pipeline.load_lora_weights("nerijs/pixel-art-xl", weight_name="pixel-art-xl.safetensors", adapter_name="pixel")
-#pipeline.set_adapters("pixel")
-
-
-# 选择采样方法（调度器） 可以新增但是跑就死
-#scheduler = EulerDiscreteScheduler()
-#pipeline.scheduler = scheduler
-
-#badhandv4
-#pipeline.load_textual_inversion("./badhandv4.pt", "badhandv4")
-#hiten1
-#pipeline.load_textual_inversion("./hiten1.pt", "hiten1")
-#pipeline.compile()
-
-#TypeError: LatentConsistencyPipelineMixin.__call__() got an unexpected keyword argument 'negative_prompt'
-#negative_prompt="easynegative,bad anatomy, bad hands, missing fingers, extra fingers, three hands, three legs, bad arms, missing legs, missing arms, poorly drawn face, bad face, fused face, cloned face, three crus, fused feet, fused thigh, extra crus, ugly fingers, horn, cartoon, cg, 3d, unreal, animate, amputation, disconnected limbs, nsfw, nude, censored,  "
+pipeline = OVStableDiffusionPipeline.from_pretrained(model_id, device='CPU')
 
 def infer(prompt, num_inference_steps):
-
     image = pipeline(
-        prompt = prompt, 
-        #negative_prompt = negative_prompt,
-        guidance_scale = 1.0,
-        num_inference_steps = num_inference_steps, 
-        width = 512,
-        height = 512,
+        prompt=prompt,
+        guidance_scale=1.0,
+        num_inference_steps=num_inference_steps,
+        width=512,
+        height=512,
         num_images_per_prompt=1,
     ).images[0]
-    
     return image
 
 examples = [
@@ -61,62 +21,45 @@ examples = [
     "A delicious ceviche cheesecake slice",
 ]
 
-css="""
+css = """
 #col-container {
     margin: 0 auto;
     max-width: 520px;
 }
 """
 
-
 with gr.Blocks(css=css) as demo:
-    
     with gr.Column(elem_id="col-container"):
-        gr.Markdown(f"""
-        # Demo : yujiepan/dreamshaper-8-lcm-openvino-w8a8 ⚡
-        """)
+        gr.Markdown("# Demo : yujiepan/dreamshaper-8-lcm-openvino-w8a8 ⚡")
 
-        with gr.Row():
-            
-            prompt = gr.Text(
-                label="Prompt",
-                show_label=False,
-                max_lines=1,
-                placeholder="Enter your prompt",
-                container=False,
-            )
-            
-            run_button = gr.Button("Run", scale=0)
+        prompt = gr.Text(
+            label="Prompt",
+            show_label=False,
+            placeholder="Enter your prompt",
+            container=False,
+        )
         
+        run_button = gr.Button("Run", scale=0)
         result = gr.Image(label="Result", show_label=False)
 
         with gr.Accordion("Advanced Settings", open=False):
-            #with gr.Row():
-            # negative_prompt = gr.Text(
-            #     label="Negative prompt",
-            #     max_lines=1,
-            #     placeholder="Enter a negative prompt",
-            # )
-            
-            with gr.Row():
-                
-                num_inference_steps = gr.Slider(
-                    label="Number of inference steps",
-                    minimum=1,
-                    maximum=50,
-                    step=1,
-                    value=8,
-                )
-        
+            num_inference_steps = gr.Slider(
+                label="Number of inference steps",
+                minimum=1,
+                maximum=50,
+                step=1,
+                value=8,
+            )
+
         gr.Examples(
-            examples = examples,
-            inputs = [prompt]
+            examples=examples,
+            inputs=[prompt]
         )
 
     run_button.click(
-        fn = infer,
-        inputs = [prompt, num_inference_steps],
-        outputs = [result]
+        fn=infer,
+        inputs=[prompt, num_inference_steps],
+        outputs=[result]
     )
 
-demo.queue().launch(share=True)
+demo.queue().launch(share=True)