resize back 32

app.py

@@ -58,9 +58,9 @@ def process_images(image,prompt="a girl",strength=0.75,seed=0,inference_step=4,p
         generators = []
         generator = torch.Generator(device).manual_seed(seed)
         generators.append(generator)
-        width,height = convert_to_fit_size(image.size)
+        fit_width,fit_height = convert_to_fit_size(image.size)
         #print(f"fit {width}x{height}")
-        width,height = adjust_to_multiple_of_32(width,height)
+        width,height = adjust_to_multiple_of_32(fit_width,fit_height)
         #print(f"multiple {width}x{height}")
         image = image.resize((width, height), Image.LANCZOS)
         #mask_image = mask_image.resize((width, height), Image.NEAREST)
@@ -70,8 +70,15 @@ def process_images(image,prompt="a girl",strength=0.75,seed=0,inference_step=4,p
         output = pipe(prompt=prompt, image=image,generator=generator,strength=strength,width=width,height=height
                     ,guidance_scale=0,num_inference_steps=num_inference_steps,max_sequence_length=256)
 
-        # TODO support mask
-        return output.images[0]
+        pil_image = Image.fromarray(output.images[0])
+        new_width,new_height = pil_image.size
+
+        # resize back multiple of 32
+        if (new_width!=fit_width) or (new_height!=fit_height):
+            resized_image= pil_image.resize(fit_width,fit_height,Image.LANCZOS)
+            return resized_image
+        
+        return pil_image
 
     output = process_img2img(image,prompt,strength,seed,inference_step)