Update handler.py

handler.py

@@ -116,14 +116,14 @@ class EndpointHandler():
         #pipe = AutoPipelineForInpainting.from_pretrained("diffusers/stable-diffusion-xl-1.0-inpainting-0.1", torch_dtype=torch.float16, variant="fp16").to("cuda")
         
         # 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, num_inference_steps=num_inference_steps, guidance_scale=guidance_scale)
 
         print("1st pipeline part successful!")
 
         image = out.images[0].resize((1024, 1024))
 
         print("image resizing successful!")
-
+        """
         image = self.pipe2(
             prompt=prompt,
             negative_prompt=negative_prompt,
@@ -146,9 +146,10 @@ class EndpointHandler():
         ).images[0]
 
         print("3rd pipeline part successful!")
+        """
             
         # return first generate PIL image
-        return image2
+        return image
         
         """
         control_image = self.make_inpaint_condition(image, mask_image)