a

handler.py

@@ -6,7 +6,7 @@ from io import BytesIO
 from PIL import Image
 from diffusers import StableDiffusionXLImg2ImgPipeline
 from diffusers.utils import load_image
-
+import numpy as np
 
 
 class EndpointHandler():
@@ -41,17 +41,16 @@ class EndpointHandler():
         
         # process image
         if encoded_image is not None:
-            image = self.decode_base64_image(encoded_image)            
+            image = self.decode_base64_image(encoded_image)
             print("Image is getting loaded")
         else:
             print("Image is None")
             image = None
 
-        imgLen = len(image)
             
         print(f"Prompt: {inputs}, strength: {strength}, inf steps: {num_inference_steps}, denoise start: {denoising_start}, denoise_end: {denoising_end}")
         print(f"Imgs per prompt: {num_images_per_prompt}, aesthetic_score: {aesthetic_score}, guidance_scale: {guidance_scale}, negative_prompt: {negative_prompt}")
-        print(f"Image size: {imgLen}")
+
         # run inference pipeline
         out = self.pipe(inputs, 
                         image=image,             
@@ -71,6 +70,7 @@ class EndpointHandler():
     # helper to decode input image
     def decode_base64_image(self, image_string):
         base64_image = base64.b64decode(image_string)
-        buffer = BytesIO(base64_image)
+        buffer = io.BytesIO(base64_image)
         image = Image.open(buffer)
-        return image
+        pil_image = Image.fromarray(np.array(image))
+        return pil_image