Update app.py

app.py

@@ -1,78 +1,44 @@
 import gradio as gr
-import numpy as np
-import random
-from diffusers import DiffusionPipeline
-from optimum.intel.openvino.modeling_diffusion import OVModelVaeDecoder, OVBaseModel, OVStableDiffusionPipeline
 import torch
-from huggingface_hub import snapshot_download
-import openvino.runtime as ov
-from typing import Optional, Dict
-#from diffusers import EulerAncestralDiscreteScheduler, LCMScheduler
-
-#LCMScheduler 產生垃圾
-#EulerDiscreteScheduler 尚可
-#EulerAncestralDiscreteScheduler 很不錯chatgpt推薦
-
+from optimum.intel.openvino.modeling_diffusion import OVStableDiffusionPipeline
 
 model_id = "hsuwill000/Fluently-v4-LCM-openvino"
 
-#model_id = "spamsoms/LCM-anything-v5-openvino2"
-#adapter_id = "latent-consistency/lcm-lora-sdv1-5"
-
-#512*512 好 太大會變形
-HIGH=1024
-WIDTH=512
+HIGH = 1024
+WIDTH = 512
 
 batch_size = -1
 
 pipe = OVStableDiffusionPipeline.from_pretrained(
-        model_id, 
-        compile = False, 
-        ov_config = {"CACHE_DIR":""},
-        torch_dtype=torch.int8, #快
-        #torch_dtype=torch.bfloat16, #中
-        #variant="fp16", 
-        #torch_dtype=torch.IntTensor, #慢,
-        safety_checker=None,
-        use_safetensors=False,
-        )
+    model_id,
+    compile=False,
+    ov_config={"CACHE_DIR": ""},
+    torch_dtype=torch.int8,  # fast
+    safety_checker=None,
+    use_safetensors=False,
+)
 print(pipe.scheduler.compatibles)
-#pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
-#pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config)
-
-#pipe.load_lora_weights(adapter_id)
-#pipe.fuse_lora()
-
-
-pipe.reshape( batch_size=-1, height=HIGH, width=WIDTH, num_images_per_prompt=1)
-#pipe.load_textual_inversion("./badhandv4.pt", "badhandv4")
-#pipe.load_textual_inversion("./Konpeto.pt", "Konpeto")
-#<shigure-ui-style>
-#pipe.load_textual_inversion("sd-concepts-library/shigure-ui-style")
-#pipe.load_textual_inversion("sd-concepts-library/ruan-jia")
-#pipe.load_textual_inversion("sd-concepts-library/agm-style-nao")
 
+pipe.reshape(batch_size=-1, height=HIGH, width=WIDTH, num_images_per_prompt=1)
 
 pipe.compile()
 
-prompt=""
-negative_prompt="EasyNegative, "
-
-def infer(prompt,negative_prompt):
+prompt = ""
+negative_prompt = "EasyNegative, "
 
+def infer(prompt, negative_prompt, num_inference_steps):
     image = pipe(
-        prompt = prompt, 
-        negative_prompt = negative_prompt,
-        width = WIDTH, 
-        height = HIGH,
+        prompt=prompt,
+        negative_prompt=negative_prompt,
+        width=WIDTH,
+        height=HIGH,
         guidance_scale=1.0,
-        num_inference_steps=8,
+        num_inference_steps=num_inference_steps,
         num_images_per_prompt=1,
-    ).images[0] 
+    ).images[0]
     
     return image
 
-
 examples = [
     "(Digital art, highres, best quality, 8K, masterpiece, anime screencap, perfect eyes:1.4, ultra detailed:1.5),1girl,flat chest,short messy pink hair,blue eyes,tall,thick thighs,light blue hoodie,collar,light blue shirt,black sport shorts,bulge,black thigh highs,femboy,okoto no ko,smiling,blushing,looking at viewer,inside,livingroom,sitting on couch,nighttime,dark,hand_to_mouth,",
     "1girl, silver hair, symbol-shaped pupils, yellow eyes, smiling, light particles, light rays, wallpaper, star guardian, serious face, red inner hair, power aura, grandmaster1, golden and white clothes",
@@ -80,14 +46,13 @@ examples = [
     "((colofrul:1.7)),((best quality)), ((masterpiece)), ((ultra-detailed)), (illustration), (detailed light), (an extremely delicate and beautiful),incredibly_absurdres,(glowing),(1girl:1.7),solo,a beautiful girl,(((cowboy shot))),standding,((Hosiery)),((beautiful off-shoulder lace-trimmed layered strapless dress+white stocking):1.25),((Belts)),(leg loops),((Hosiery)),((flower headdress)),((long white hair)),(((beautiful eyes))),BREAK,((english text)),(flower:1.35),(garden),(((border:1.75))),",
 ]
 
-css="""
+css = """
 #col-container {
     margin: 0 auto;
     max-width: 520px;
 }
 """
 
-
 power_device = "CPU"
 
 with gr.Blocks(css=css) as demo:
@@ -108,19 +73,28 @@ with gr.Blocks(css=css) as demo:
             )         
             run_button = gr.Button("Run", scale=0)
         
+        # Slider for num_inference_steps
+        num_inference_steps_slider = gr.Slider(
+            minimum=1,
+            maximum=30,
+            step=1,
+            value=4,
+            label="Number of Inference Steps"
+        )
+
         result = gr.Image(label="Result", show_label=False)
 
         gr.Examples(
-            examples = examples,
-            fn = infer,
-            inputs = [prompt],
-            outputs = [result]
+            examples=examples,
+            fn=infer,
+            inputs=[prompt, num_inference_steps_slider],
+            outputs=[result]
         )
 
     run_button.click(
-        fn = infer,
-        inputs = [prompt],
-        outputs = [result]
+        fn=infer,
+        inputs=[prompt, num_inference_steps_slider],
+        outputs=[result]
     )
 
-demo.queue().launch()
+demo.queue().launch()