Update handler.py

handler.py

@@ -96,7 +96,7 @@ class EndpointHandler():
         self.pipe.enable_xformers_memory_efficient_attention()
         
         # run inference pipeline
-        out = self.pipe(prompt=prompt, negative_prompt=negative_prompt, image=image, mask_image=mask_image)
+        out = self.pipe(prompt=prompt, negative_prompt=negative_prompt, image=image, mask_image=mask_image, strength=0.99)
 
         print("1st pipeline part successful!")
 
@@ -111,9 +111,9 @@ class EndpointHandler():
             negative_prompt=negative_prompt,
             image=image,
             mask_image=mask_image,
-            guidance_scale=8.0, #8.0
-            num_inference_steps=100, #100
-            strength=0.2, #0.2
+            guidance_scale=guidance_scale, #8.0
+            num_inference_steps=num_inference_steps, #100
+            strength=strength, #0.2
             output_type="latent",  # let's keep in latent to save some VRAM
         ).images[0]
 
@@ -124,9 +124,9 @@ class EndpointHandler():
         image2 = self.pipe3(
             prompt=prompt,
             image=image,
-            guidance_scale=8.0, #8.0
-            num_inference_steps=100, #100
-            strength=0.2, #0.2
+            guidance_scale=guidance_scale, #8.0
+            num_inference_steps=num_inference_steps, #100
+            strength=strength, #0.2
         ).images[0]
 
         print("3rd pipeline part successful!")