Upload Batch_Remove_Img_At.py

Batch_Remove_Img_At.py

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+# ComfyUI Custom Node: Remove (Exclude) Image @ Index from a Batch
+# Save as:
+#   ComfyUI/custom_nodes/batch_remove_index/__init__.py
+# Restart ComfyUI, then find it under category: "Batch/Index"
+
+import torch
+
+
+def _clamp_index(index: int, batch_size: int) -> int:
+    """Clamp index into [0, batch_size-1]."""
+    if batch_size <= 0:
+        raise ValueError("Input batch is empty (batch_size <= 0).")
+    if index < 0 or index >= batch_size:
+        print(
+            f"[BatchRemoveIndex] index {index} out of range for batch_size {batch_size}; "
+            f"clamping to valid range."
+        )
+        index = max(0, min(index, batch_size - 1))
+    return index
+
+
+class BatchRemoveImageAtIndex:
+    """
+    Takes an IMAGE batch and an integer index (0-based),
+    outputs the batch WITHOUT the image at that index.
+
+    Example:
+      images = [img0,img1,img2,img3], index=2
+      output = [img0,img1,img3]
+    """
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "images": ("IMAGE",),
+                "index": ("INT", {"default": 0, "min": 0, "max": 10**9}),
+            }
+        }
+
+    RETURN_TYPES = ("IMAGE",)
+    RETURN_NAMES = ("images",)
+    FUNCTION = "remove"
+    CATEGORY = "Batch/Index"
+
+    def remove(self, images, index):
+        if not torch.is_tensor(images):
+            raise TypeError("Expected 'images' to be a torch Tensor (ComfyUI IMAGE type).")
+        if images.ndim != 4:
+            raise ValueError(f"Expected 'images' with shape [B,H,W,C], got ndim={images.ndim}.")
+
+        b = images.shape[0]
+        if b <= 1:
+            # Producing an empty IMAGE batch often breaks downstream nodes.
+            raise ValueError(
+                f"Cannot remove an item from a batch of size {b} (would produce an empty batch)."
+            )
+
+        idx = _clamp_index(int(index), b)
+
+        # Concatenate everything except the excluded index
+        out = torch.cat([images[:idx], images[idx + 1 :]], dim=0)
+        return (out,)
+
+
+NODE_CLASS_MAPPINGS = {
+    "BatchRemoveImageAtIndex": BatchRemoveImageAtIndex,
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "BatchRemoveImageAtIndex": "Batch: Remove Image @ Index",
+}