a

handler.py

@@ -38,16 +38,20 @@ class EndpointHandler():
         denoising_end = data.pop("denoising_end_step", 1)
         num_images_per_prompt = data.pop("num_images_per_prompt", 1)
         aesthetic_score = data.pop("aesthetic_score", 0.6)
-
         
         # process image
         if encoded_image is not None:
             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,