Update app.py

app.py

@@ -62,6 +62,7 @@ def generate(prompt,
              steps=3, 
              interm_steps=33, 
              guidance_scale=3.5,
+             use_slerp=True,
              x_concept_1="", x_concept_2="", 
              avg_diff_x=None, 
              total_images=[],
@@ -93,7 +94,12 @@ def generate(prompt,
                                      width=768,
                                      height=768,
                                      guidance_scale=guidance_scale, 
-                                     scale=cur_scale,  seed=seed, num_inference_steps=steps, avg_diff=avg_diff) 
+                                     scale=cur_scale,
+                                     seed=seed,
+                                     num_inference_steps=steps,
+                                     avg_diff=avg_diff,
+                                     use_slerp=use_slerp,
+                                     max_strength_for_slerp_endpoint=scale) 
         images.append(image)
         #hack for cache examples
         counter+=1
@@ -201,7 +207,7 @@ with gr.Blocks(css=css) as demo:
             with gr.Column():
                 randomize_seed = gr.Checkbox(True, label="Randomize seed")
                 seed = gr.Slider(minimum=0, maximum=MAX_SEED, step=1, label="Seed", interactive=True, randomize=True)
-
+        use_slerp_checkbox = gr.Checkbox(label="Use Spherical Linear Interpolation (Slerp)", value=True)
     examples_gradio = gr.Examples(
         examples=examples,
         inputs=[prompt, concept_1, concept_2, x],
@@ -212,7 +218,7 @@ with gr.Blocks(css=css) as demo:
 
     submit.click(
         fn=generate,
-        inputs=[prompt, concept_1, concept_2, x, randomize_seed, seed, recalc_directions, iterations, steps, interm_steps, guidance_scale, x_concept_1, x_concept_2, avg_diff_x, total_images],
+        inputs=[prompt, concept_1, concept_2, x, randomize_seed, seed, recalc_directions, iterations, steps, interm_steps, guidance_scale, use_slerp_checkbox, x_concept_1, x_concept_2, avg_diff_x, total_images],
         outputs=[x_concept_1, x_concept_2, avg_diff_x, output_image, image_seq, total_images, post_generation_image, post_generation_slider, seed]
     )
     iterations.change(