randomize seed

app.py

@@ -121,10 +121,10 @@ def execute(image, prompt, debug=False):
   #pipe.load_lora_weights("XLabs-AI/flux-RealismLora", weight_name='lora.safetensors')
   response = []
 
-  seed_slicer = random.randint(0, MAX_SEED)
-  generator = torch.Generator().manual_seed(seed_slicer)
-
   for image in range(len(imgs)):
+    seed_slicer = random.randint(0, MAX_SEED)
+    generator = torch.Generator().manual_seed(seed_slicer)
+
     current_img = imgs[image]
     cv2.imwrite('base_image.jpg', current_img)
     cv2.imwrite("mask.jpg", maskHead('base_image.jpg'))