Update app.py

app.py

@@ -350,9 +350,6 @@ def genie (Model, Prompt, negative_prompt, height, width, scale, steps, seed, re
                torch.cuda.empty_cache()
                return image
     if Model == 'SDXL-Turbo':
-        #from diffusers import AutoPipelineForText2Image
-        #pipe = AutoPipelineForText2Image.from_pretrained("stabilityai/sdxl-turbo", torch_dtype=torch.float16, variant="fp16")
-        #pipe.to("cuda")
         torch.cuda.empty_cache()
         pipe = DiffusionPipeline.from_pretrained("stabilityai/sdxl-turbo", torch_dtype=torch.float16, variant="fp16")
         pipe.enable_xformers_memory_efficient_attention()
@@ -365,7 +362,16 @@ def genie (Model, Prompt, negative_prompt, height, width, scale, steps, seed, re
             torch.cuda.empty_cache()
             refined = refiner(Prompt, negative_prompt=negative_prompt, image=image, denoising_start=high_noise_frac).images[0]
             torch.cuda.empty_cache()
-            return refined
+            if upscale == 'Yes':
+                upscaler = DiffusionPipeline.from_pretrained("stabilityai/sd-x2-latent-upscaler", torch_dtype=torch.float16, use_safetensors=True)
+                upscaler.enable_xformers_memory_efficient_attention()
+                upscaler = upscaler.to(device)
+                torch.cuda.empty_cache()
+                upscaled = upscaler(prompt=Prompt, negative_prompt=negative_prompt, image=refined, num_inference_steps=5, guidance_scale=0).images[0]
+                torch.cuda.empty_cache()
+                return upscaled
+            else:     
+                return refined
     return image
     
 gr.Interface(fn=genie, inputs=[gr.Radio(['PhotoReal', 'Anime', 'Disney', 'StoryBook', 'SemiReal', 'Animagine XL 3.0', 'SDXL 1.0', 'FusionXL', 'SDXL-Turbo'], value='PhotoReal', label='Choose Model'),