Upload canvas_crop.py

canvas_crop.py

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+import torch
+
+class Canvas_Crop:
+    """
+    Reduce the canvas of an image by cropping pixels from each side.
+
+    Inputs
+    ------
+    image : IMAGE
+        Torch tensor [B, H, W, C], C=3 (RGB) or C=4 (RGBA), values in [0, 1].
+        If RGB is provided, it will be converted to RGBA by appending an opaque alpha channel.
+
+    left, right, up, down : INT
+        Number of pixels to remove from the corresponding side.
+
+    Output
+    ------
+    image : IMAGE
+        Torch tensor [B, H - (up+down), W - (left+right), 4] (RGBA).
+    """
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "image": ("IMAGE",),
+                "left":  ("INT", {"default": 0, "min": 0, "max": 16384, "step": 1}),
+                "right": ("INT", {"default": 0, "min": 0, "max": 16384, "step": 1}),
+                "up":    ("INT", {"default": 0, "min": 0, "max": 16384, "step": 1}),
+                "down":  ("INT", {"default": 0, "min": 0, "max": 16384, "step": 1}),
+            }
+        }
+
+    RETURN_TYPES = ("IMAGE",)
+    RETURN_NAMES = ("image",)
+    FUNCTION = "crop"
+    CATEGORY = "image/canvas"
+
+    def _ensure_rgba(self, img: torch.Tensor) -> torch.Tensor:
+        # Expect [B, H, W, C]
+        if img.dim() != 4:
+            raise ValueError(f"Expected image tensor [B, H, W, C], got shape {tuple(img.shape)}")
+
+        c = img.shape[-1]
+        if c == 4:
+            return img
+        elif c == 3:
+            # Add opaque alpha if only RGB provided
+            alpha = torch.ones((*img.shape[:-1], 1), dtype=img.dtype, device=img.device)
+            return torch.cat([img, alpha], dim=-1)
+        elif c > 4:
+            # If extra channels exist, keep the first 4 (RGBA)
+            return img[..., :4]
+        else:
+            raise ValueError("Expected RGB or RGBA image with 3 or 4 channels.")
+
+    def crop(self, image: torch.Tensor, left: int, right: int, up: int, down: int):
+        rgba = self._ensure_rgba(image)  # [B, H, W, 4]
+        b, h, w, _ = rgba.shape
+
+        # Sanitize
+        left  = max(0, int(left))
+        right = max(0, int(right))
+        up    = max(0, int(up))
+        down  = max(0, int(down))
+
+        # Validate that the requested crop is possible
+        if left + right >= w:
+            raise ValueError(
+                f"Crop too wide: left({left}) + right({right}) >= image width({w})."
+            )
+        if up + down >= h:
+            raise ValueError(
+                f"Crop too tall: up({up}) + down({down}) >= image height({h})."
+            )
+
+        # Compute crop window
+        y0 = up
+        y1 = h - down
+        x0 = left
+        x1 = w - right
+
+        # Perform crop
+        out = rgba[:, y0:y1, x0:x1, :]
+        return (out,)
+
+
+# Required mappings for ComfyUI to discover the node
+NODE_CLASS_MAPPINGS = {
+    "Canvas_Crop": Canvas_Crop
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "Canvas_Crop": "Canvas_Crop (Salia)",
+}