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nodes/FV_IfImageValid.py

@@ -1,5 +1,5 @@
-from PIL import Image
 import numpy as np
+import torch
 
 class IfImageValid:
     def __init__(self):
@@ -25,9 +25,10 @@ class IfImageValid:
         elif else_Image is not None:
             return (else_Image,)
         else:
-            return (Image.fromarray(np.zeros((512, 512, 3), dtype=np.uint8)),)         
+            black_image = torch.zeros((1, 32, 32, 3), dtype=torch.uint8) 
+            return (black_image,)
 
 # Mapping de la classe
 NODE_CLASS_MAPPINGS = {
     "If Image Valid": IfImageValid,
-}
+}

nodes/FV_IsValid.py

@@ -0,0 +1,25 @@
+class IsImageValid:
+    def __init__(self):
+        pass
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "optional": {
+                "image": ("IMAGE",),  # Type d'entrée défini comme IMAGE
+            },
+        }
+
+    RETURN_TYPES = ("BOOL",)
+    RETURN_NAMES = ("is_valid",)
+    FUNCTION = "check_is_valid"
+    CATEGORY = "Fictiverse"
+
+    def check_is_valid(self, image=None):
+        # Retourne False si l'image est None, sinon True
+        return (image is not None,)
+
+# Mapping de la classe
+NODE_CLASS_MAPPINGS = {
+    "Is Image Valid ?": IsImageValid,
+}

nodes/FV_NoneIfSameImage.py

@@ -0,0 +1,41 @@
+import torch
+import numpy as np
+
+class NoneIfSameImage:
+    def __init__(self):
+        pass
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "optional": {  
+                "image": ("IMAGE",),
+                "compare": ("IMAGE",),
+            },
+        }
+
+    RETURN_TYPES = ("IMAGE", "BOOL",)
+    RETURN_NAMES = ("IMAGE", "is_same",)
+    FUNCTION = "checkIfSameImage"
+    CATEGORY = "Fictiverse"
+
+    def checkIfSameImage(self, image=None, compare=None):
+        if image is None and compare is None:
+            black_image = torch.zeros((1, 32, 32, 3), dtype=torch.uint8) 
+            return (black_image, False)
+
+        if image is None:
+            return (compare, False)
+
+        if compare is None:
+            return (image, False)
+
+        if torch.equal(image, compare):
+            black_image = torch.zeros((1, 32, 32, 3), dtype=torch.uint8) 
+            return (black_image, True)
+
+        return (image, False)
+
+NODE_CLASS_MAPPINGS = {
+    "None if same Image": NoneIfSameImage,
+}