Update app.py

app.py

@@ -72,10 +72,25 @@ def genie (Model, Prompt, negative_prompt, height, width, scale, steps, seed, up
         else:
             image = story(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale).images[0]
             torch.cuda.empty_cache()
+            return image
+
+    if Model == "Semi":
+        semi = DiffusionPipeline.from_pretrained("circulus/canvers-semi-v3.8.1", torch_dtype=torch.float16, safety_checker=None) if torch.cuda.is_available() else DiffusionPipeline.from_pretrained("circulus/canvers-semi-v3.8.1")
+        semi = semi.to(device)
+        semi.enable_xformers_memory_efficient_attention()
+        torch.cuda.empty_cache()
+        if upscale == "Yes":
+            int_image = semi(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale).images
+            image = refiner(Prompt, negative_prompt=negative_prompt, image=int_image, denoising_start=high_noise_frac).images[0]
+            torch.cuda.empty_cache()
+            return image
+        else:
+            image = semi(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale).images[0]
+            torch.cuda.empty_cache()
             
     return image
     
-gr.Interface(fn=genie, inputs=[gr.Radio(['Real', 'Anime', 'Disney', 'Story'], value='Real', label='Choose Canvers Model'),
+gr.Interface(fn=genie, inputs=[gr.Radio(['Real', 'Anime', 'Disney', 'Story', 'Semi'], value='Real', label='Choose Canvers Model'),
                                gr.Textbox(label='What you want the AI to generate. 77 Token Limit.'), 
                                gr.Textbox(label='What you Do Not want the AI to generate. 77 Token Limit'),
                                gr.Slider(512, 1024, 768, step=128, label='Height'),
@@ -86,6 +101,6 @@ gr.Interface(fn=genie, inputs=[gr.Radio(['Real', 'Anime', 'Disney', 'Story'], va
                                gr.Radio(["Yes", "No"], label='SDXL 1.0 Refiner: Use if the Image has too much Noise', value='No'),
                                gr.Slider(minimum=.9, maximum=.99, value=.95, step=.01, label='Refiner Denoise Start %')],
              outputs=gr.Image(label='Generated Image'), 
-             title="PhotoReal V3.8.1 with SDXL 1.0 Refiner - GPU", 
+             title="Canvers Dream Booth V3.8.1 with SDXL 1.0 Refiner - GPU", 
              description="<br><br><b/>Warning: This Demo is capable of producing NSFW content.", 
              article = "If You Enjoyed this Demo and would like to Donate, you can send to any of these Wallets. <br>BTC: bc1qzdm9j73mj8ucwwtsjx4x4ylyfvr6kp7svzjn84 <br>3LWRoKYx6bCLnUrKEdnPo3FCSPQUSFDjFP <br>DOGE: DK6LRc4gfefdCTRk9xPD239N31jh9GjKez <br>SHIB (BEP20): 0xbE8f2f3B71DFEB84E5F7E3aae1909d60658aB891 <br>PayPal: https://www.paypal.me/ManjushriBodhisattva <br>ETH: 0xbE8f2f3B71DFEB84E5F7E3aae1909d60658aB891 <br>Code Monkey: <a href=\"https://huggingface.co/Manjushri\">Manjushri</a>").launch(debug=True, max_threads=80)