Upload app.py

app.py

@@ -96,12 +96,12 @@ def latents_to_pil(latents):
     return pil_images
 
 
-def generate_with_embs(text_embeddings, text_input, seed):
+def generate_with_embs(text_embeddings, text_input, seed,num_inference_steps,guidance_scale):
 
     height = 512                        # default height of Stable Diffusion
     width = 512                         # default width of Stable Diffusion
-    num_inference_steps = 10            # Number of denoising steps
-    guidance_scale = 7.5                # Scale for classifier-free guidance
+    num_inference_steps = num_inference_steps # 10            # Number of denoising steps
+    guidance_scale = guidance_scale # 7.5                # Scale for classifier-free guidance
     generator = torch.manual_seed(seed)   # Seed generator to create the inital latent noise
     batch_size = 1
 
@@ -291,12 +291,14 @@ dict_styles = {
     'Oil Painting':'styles/learned_embeds_oil.bin',  
 }
 
-def inference(prompt, style,seed): 
+def inference(prompt, seed, style): 
     
     if prompt is not None and style is not None and seed is not None: 
         style = dict_styles[style]
         torch.manual_seed(seed)
-        result = generate_with_prompt_style_guidance(prompt, style,seed)
+        num_inference_steps =10
+        guidance_scale =7.5
+        result = generate_with_prompt_style_guidance(prompt, style,seed,num_inference_steps,guidance_scale)
         return np.array(result)
     else:
         return None