Update app1.py

app1.py

@@ -5,34 +5,8 @@ import modin.pandas as pd
 from PIL import Image
 from diffusers import DiffusionPipeline, StableDiffusionLatentUpscalePipeline
 
-css = """
-  <style>
-  .finetuned-diffusion-div {
-      text-align: center;
-      max-width: 700px;
-      margin: 0 auto;
-    }
-    .finetuned-diffusion-div div {
-      display: inline-flex;
-      align-items: center;
-      gap: 0.8rem;
-      font-size: 1.75rem;
-    }
-    .finetuned-diffusion-div div h1 {
-      font-weight: 900;
-      margin-bottom: 7px;
-    }
-    .finetuned-diffusion-div p {
-      margin-bottom: 10px;
-      font-size: 94%;
-    }
-    .finetuned-diffusion-div p a {
-      text-decoration: underline;
-    }
-  </style>
-
 device = "cuda" if torch.cuda.is_available() else "cpu"
-pipe = DiffusionPipeline.from_pretrained("dreamlike-art/dreamlike-photoreal-2.0", torch_dtype=torch.float16, safety_checker=None)
+pipe = DiffusionPipeline.from_pretrained("dreamlike-art/dreamlike-photoreal-2.0", torch_dtype=torch.float16, safety_checker=None, use_safetensors=False)
 upscaler = StableDiffusionLatentUpscalePipeline.from_pretrained("stabilityai/sd-x2-latent-upscaler", torch_dtype=torch.float16)
 upscaler = upscaler.to(device)
 pipe = pipe.to(device)
@@ -46,21 +20,21 @@ def genie (Prompt, negative_prompt, height, width, scale, steps, seed, upscale,
         image = pipe(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale, generator=generator).images[0]
     return image
     
-gr.Interface(theme='HaleyCH/HaleyCH_Theme', fn=genie, inputs=[gr.Textbox(label='Input field right under here(Prompt)'), 
+gr.Interface(theme='ParityError/Anime', fn=genie, inputs=[gr.Textbox(label='Input field right under here(Prompt)'), 
                                gr.Textbox(label='What You dont want (Negative Prompt)'),
                                gr.Slider(512, 1024, 768, step=128, label='Height'),
                                gr.Slider(512, 1024, 768, step=128, label='Width'),
                                gr.Slider(1, maximum=15, value=10, step=.25), 
                                gr.Slider(25, maximum=100, value=50, step=25), 
                                gr.Slider(minimum=1, step=1, maximum=9999999999999999, randomize=True), 
-                               gr.Radio(["Yes", "No"], label='Upscale?'),
-                               gr.Textbox(label='Upscaler Prompt: Optional'),
-                               gr.Textbox(label='Upscaler Negative Prompt: Both Optional And Experimental'),
-                               gr.Slider(minimum=0, maximum=15, value=0, step=1, label='Upscale Guidance Scale'),
-                               gr.Slider(minimum=5, maximum=25, value=5, step=5, label='Upscaler Iterations')
+                              # gr.Radio(["Yes", "No"], label='Upscale?'),
+                               #gr.Textbox(label='Upscaler Prompt: Optional'),
+                               #gr.Textbox(label='Upscaler Negative Prompt: Both Optional And Experimental'),
+                               #gr.Slider(minimum=0, maximum=15, value=0, step=1, label='Upscale Guidance Scale'),
+                               #gr.Slider(minimum=5, maximum=25, value=5, step=5, label='Upscaler Iterations')
              
                               ],
              outputs=gr.Image(label='Generated Image'), 
-             title="Our Free Image Creator", 
-             description="<br><br><b/> TIPS:<br>To get the best result read the instructions undeneath the App.<br> This Free App is slow producing Images.<br> Join us , And get access to this App and many more. They work faster and have more advanced features", 
-             article = "Online App: <a href=\"https://www.aichatbot.ai\">www.aichatbot.ai</a>").launch(debug=True, max_threads=True)
+             title="Dream Art (SD) ", 
+             description="<br> <h4> <div style='width:100%'> Info:Dream Art (SD) <br> This App is our favorite now and shows how Stable diffusion works i a good way !</h4> </div>", 
+             ).launch(debug=True, max_threads=True)