add numpy

model.py

@@ -4,6 +4,7 @@ import matplotlib.patches as mpatches
 from matplotlib import cm
 
 from PIL import Image
+import numpy as np
 
 import torch
 from transformers import AutoImageProcessor, UperNetForSemanticSegmentation
@@ -108,9 +109,6 @@ class VirtualStagingToolV2():
         init_image = init_image.resize((512, 512)).convert("RGB")
         mask_image = mask_image.resize((512, 512)).convert("RGB")
 
-        display(init_image)
-        display(mask_image)
-
         output_images = self.diffution_pipeline(
             prompt=prompt, image=init_image, mask_image=mask_image,
             # width=width, height=height,
@@ -141,7 +139,6 @@ class VirtualStagingToolV2():
 
         final_output_images = []
         for output_image in output_images:
-            display(output_image)
             output_image = output_image.resize(init_image.size)
             final_output_images.append(output_image)
         return final_output_images, transparent_mask_image

requirements.txt

@@ -3,4 +3,5 @@ torch==1.11.0
 diffusers==0.16.1
 accelerate==0.19.0
 matplotlib==3.6.2
-pillow==9.2.0
+pillow==9.2.0
+numpy==1.23.2