Update app.py

Added H/W Res slider

app.py

@@ -21,14 +21,16 @@ else:
     refiner = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-1.0", use_safetensors=True)
     refiner = refiner.to(device)
 
-def genie (prompt, negative_prompt, scale, steps, seed):
+def genie (prompt, negative_prompt, height, width, scale, steps, seed):
     generator = torch.Generator(device=device).manual_seed(seed)
-    int_image = pipe(prompt, negative_prompt=negative_prompt, num_inference_steps=steps, guidance_scale=scale, num_images_per_prompt=1, generator=generator, width=768, height=768, output_type="latent").images 
+    int_image = pipe(prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale, num_images_per_prompt=1, generator=generator, width=768, height=768, output_type="latent").images 
     image = refiner(prompt=prompt, negative_prompt=negative_prompt, image=int_image).images[0]
     return image
     
 gr.Interface(fn=genie, inputs=[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.'), 
+    gr.Slider(512, 1024, 768, step=128, label='Height'),
+    gr.Slider(512, 1024, 768, step=128, label='Width'),
     gr.Slider(1, 15, 10, label='Guidance Scale'), 
     gr.Slider(25, maximum=50, value=25, step=1, label='Number of Iterations'), 
     gr.Slider(minimum=1, step=1, maximum=999999999999999999, randomize=True)],