fix zero

app.py

@@ -1,12 +1,13 @@
 import spaces
-
+import os
 import gradio as gr
 import torch
 import numpy as np
 import torch
 from pytorch_lightning import seed_everything
 from model_lib.utils import parse_args
-import os
+from llava.mm_utils import process_image
+
 os.environ["CUDA_VISIBLE_DEVICES"]="0"
 
 title = "MoMA"
@@ -17,6 +18,9 @@ args = parse_args()
 
 model = None
 
+def my_process_image(a, b, c):
+    return process_image(a, b, c)
+
 @spaces.GPU
 def inference(rgb, subject, prompt, strength, seed):
     seed = int(seed) if seed else 0

dataset_lib/dataset_eval_MoMA.py

@@ -2,7 +2,7 @@ from PIL import Image
 import numpy as np
 import torch
 from torchvision import transforms
-from llava.mm_utils import process_images
+from ..app import my_process_image
 from rembg import remove
 
 def create_binary_mask(image):
@@ -38,7 +38,7 @@ def Dataset_evaluate_MoMA(image_pil, prompt,subject, moMA_main_modal):
     image_wb = image * mask + torch.ones_like(image)* (1-mask)*255
     image_pil = Image.fromarray(image_wb.permute(1,2,0).numpy().astype(np.uint8))
 
-    res['llava_processed'] = process_images([image_pil], LLaVa_processor, llava_config)
+    res['llava_processed'] = my_process_image([image_pil], LLaVa_processor, llava_config)
     res['label'] = [subject]
     return res