commit 56e932e99709f6babb7b580b54169402fdc749db
Author: var1ableX <raj.kotecha@gmail.com>
Date:   Fri Jul 26 20:59:47 2024 -0400

    initial commit

diff --git a/__init__.py b/__init__.py
new file mode 100644
index 0000000..56f4019
--- /dev/null
+++ b/__init__.py
@@ -0,0 +1,11 @@
+from .maskToCrop import GetMaskDimensions
+
+# Node class mappings
+NODE_CLASS_MAPPINGS = {
+    "GetMaskDimensions": GetMaskDimensions,
+}
+
+# Node display name mappings
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "GetMaskDimensions": "Get Mask Dimensions",
+}
\ No newline at end of file
diff --git a/maskToCrop.py b/maskToCrop.py
new file mode 100644
index 0000000..665495b
--- /dev/null
+++ b/maskToCrop.py
@@ -0,0 +1,53 @@
+import torch
+
+class GetMaskDimensions:
+    def __init__(self):
+        pass
+    
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "mask": ("MASK",),
+            }
+        }
+
+    RETURN_TYPES = ("INT", "INT", "INT", "INT",)
+    RETURN_NAMES = ("width", "height", "x", "y",)
+    FUNCTION = "execute"
+    CATEGORY = "image"
+
+    def execute(self, mask):
+        def get_mask_dimensions(mask):
+            # Assuming mask_tensor is of shape (1, H, W)
+            mask_array = mask[0]
+
+            # Find all coordinates where the mask is non-zero
+            coordinates = torch.nonzero(mask_array, as_tuple=False)
+
+            if coordinates.numel() == 0:
+                # If there are no non-zero coordinates, return a zero-sized rectangle
+                return 0, 0, 0, 0
+
+            # Get the minimum and maximum x and y coordinates
+            min_coords = torch.min(coordinates, dim=0)[0]
+            max_coords = torch.max(coordinates, dim=0)[0]
+
+            # Extract bounding box coordinates
+            top_left_x = min_coords[1].item()
+            top_left_y = min_coords[0].item()
+            bottom_right_x = max_coords[1].item()
+            bottom_right_y = max_coords[0].item()
+
+            # Calculate width and height
+            width = bottom_right_x - top_left_x + 1
+            height = bottom_right_y - top_left_y + 1
+
+            return width, height, top_left_x, top_left_y
+
+        # Process the mask tensor to find cropping dimensions
+        width, height, top_left_x, top_left_y = get_mask_dimensions(mask)
+
+        # Return the results as node outputs
+        return width, height, top_left_x, top_left_y
+