Update app.py

app.py

@@ -10,7 +10,7 @@ from diffusers import DiffusionPipeline, StableDiffusionXLPipeline, EDMEulerSche
 from huggingface_hub import hf_hub_download, InferenceClient
 
 vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16)
-pipe = StableDiffusionXLPipeline.from_pretrained("SG161222/RealVisXL_V4.0", torch_dtype=torch.float16, vae=vae)
+pipe = StableDiffusionXLPipeline.from_pretrained("fluently/Fluently-XL-Final", torch_dtype=torch.float16, vae=vae)
 pipe.load_lora_weights("KingNish/Better-Image-XL-Lora", weight_name="example-03.safetensors", adapter_name="lora")
 pipe.set_adapters("lora")
 pipe.to("cuda")
@@ -18,7 +18,9 @@ pipe.to("cuda")
 refiner = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-1.0", vae=vae, torch_dtype=torch.float16, use_safetensors=True, variant="fp16")
 refiner.to("cuda")
 
-pipe_fast = StableDiffusionXLPipeline.from_pretrained("SG161222/RealVisXL_V3.0_Turbo", torch_dtype=torch.float16, use_safetensors=True, variant="fp16")
+pipe_fast = StableDiffusionXLPipeline.from_pretrained("SG161222/RealVisXL_V3.0_Turbo", torch_dtype=torch.float16, vae=vae, use_safetensors=True, variant="fp16")
+pipe_fast.load_lora_weights("KingNish/Better-Image-XL-Lora", weight_name="example-03.safetensors", adapter_name="lora")
+pipe_fast.set_adapters("lora")
 pipe_fast.to("cuda")
 
 help_text = """
@@ -56,12 +58,13 @@ pipe_edit.to("cuda")
 def king(type ,
         input_image ,
         instruction: str ,
+        negative_prompt: str,
         steps: int = 25,
         randomize_seed: bool = False,
         seed: int = 2404,
         width: int = 1024,
         height: int = 1024,
-        guidance_scale: float = 7,
+        guidance_scale: float = 6,
         fast=True,
         use_resolution_binning: bool = True,
         progress=gr.Progress(track_tqdm=True),
@@ -72,7 +75,7 @@ def king(type ,
             seed = random.randint(0, 999999)
         generator = torch.manual_seed(seed)
         output_image = pipe_edit(
-            instruction, image=raw_image,
+            instruction, negative_prompt=negative_prompt, image=raw_image,
             guidance_scale=guidance_scale, image_guidance_scale=1.5,
             num_inference_steps=steps, generator=generator, output_type="latent",
         ).images
@@ -90,11 +93,12 @@ def king(type ,
         generator = torch.Generator().manual_seed(seed)
         if fast:
             pipes=pipe_fast
-            steps=int(steps/2)
+            steps=int(steps/3)
             guidance_scale=(guidance_scale/3)
         else:
             pipes=pipe
         image = pipes( prompt = instruction,
+            negative_prompt=negative_prompt,
             guidance_scale = guidance_scale, 
             num_inference_steps = steps, 
             width = width, height = height,
@@ -102,8 +106,9 @@ def king(type ,
         ).images         
 
         refine = refiner( prompt=instruction,
-            guidance_scale=guidance_scale,
-            num_inference_steps=steps,
+            negative_prompt = negative_prompt,
+            guidance_scale = guidance_scale,
+            num_inference_steps=  steps,
             image=image, generator=generator,
         ).images[0]        
         return seed, refine
@@ -173,14 +178,12 @@ examples=[
 with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
     gr.Markdown("# Image Generator Pro")
     with gr.Row():
-        with gr.Column(scale=2):
-            instruction = gr.Textbox(lines=1, label="Instruction", interactive=True)
-        with gr.Column(scale=1):
-            generate_button = gr.Button("Generate")
+        instruction = gr.Textbox(lines=1, label="Instruction", interactive=True)
+        generate_button = gr.Button("Run", scale=0)
     with gr.Row():
         type = gr.Dropdown(["Image Generation","Image Editing"], label="Task", value="Image Generation",interactive=True)
-        enhance_prompt = gr.Checkbox(label="Enhance prompt", value = True)
-        fast = gr.Checkbox(label="FAST Generation", value=True)
+        enhance_prompt = gr.Checkbox(label="Enhance prompt", value = True, scale=0)
+        fast = gr.Checkbox(label="FAST Gen", value=True, scale=0)
 
     with gr.Row():
         input_image = gr.Image(label="Image", type='filepath', interactive=True)
@@ -191,16 +194,11 @@ with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
 
     with gr.Accordion("Advanced options", open=False):
         with gr.Row():
-            with gr.Column(scale=1):
-                use_negative_prompt = gr.Checkbox(label="Use negative prompt", value=True, visible=True)
-            with gr.Column(scale=2):
-                negative_prompt = gr.Text(
+            negative_prompt = gr.Text(
                     label="Negative prompt",
                     max_lines=1,
-                    placeholder="Enter a negative prompt",
                     value="(deformed iris, deformed pupils, semi-realistic, cropped, out of frame, worst quality, low quality, jpeg artifacts, ugly, duplicate, extra fingers, poorly drawn hands, poorly drawn face, deformed, dehydrated, bad anatomy, bad proportions, extra limbs, cloned face, disfigured, gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck, (deformed, distorted, disfigured:1.3), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, (mutated hands and fingers:1.4), disconnected limbs, ugly, disgusting,",
-                    visible=True,
-                )
+                    visible=True)
         with gr.Row():
             width =  gr.Slider( label="Width", minimum=256, maximum=2048, step=64, value=1024)
             height =  gr.Slider( label="Height", minimum=256, maximum=2048, step=64, value=1024)
@@ -238,6 +236,7 @@ with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
             inputs=[type,
                 input_image,
                 instruction,
+                negative_prompt,
                 steps,
                 randomize_seed,
                 seed,