Upload Batch_Img_Remove_At_13.py

Batch_Img_Remove_At_13.py

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+# ComfyUI Custom Node: Remove up to 13 images from a batch "at once"
+# - Takes a batch (IMAGE)
+# - Takes 13 index inputs
+# - Removes all specified indices simultaneously (no shifting issues)
+# - Index = -1 means "do not remove anything" (ignored)
+#
+# Save as:
+#   ComfyUI/custom_nodes/batch_remove_13_indices/__init__.py
+# Restart ComfyUI, then find under: "Batch/Index"
+
+import torch
+
+
+class BatchRemoveImagesAt13Indices:
+    """
+    Remove multiple images from a batch at once.
+
+    Notes:
+      - Indices are 0-based.
+      - Any index == -1 is ignored (meaning: remove nothing for that slot).
+      - Out-of-range indices are ignored (with a console warning).
+      - Duplicate indices are fine (removed once).
+      - If removal would produce an empty batch, this node raises an error.
+    """
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        # 13 separate INT inputs, defaulting to -1
+        idx_cfg = {"default": -1, "min": -1, "max": 10**9}
+        return {
+            "required": {
+                "images": ("IMAGE",),
+
+                "remove_index_01": ("INT", idx_cfg),
+                "remove_index_02": ("INT", idx_cfg),
+                "remove_index_03": ("INT", idx_cfg),
+                "remove_index_04": ("INT", idx_cfg),
+                "remove_index_05": ("INT", idx_cfg),
+                "remove_index_06": ("INT", idx_cfg),
+                "remove_index_07": ("INT", idx_cfg),
+                "remove_index_08": ("INT", idx_cfg),
+                "remove_index_09": ("INT", idx_cfg),
+                "remove_index_10": ("INT", idx_cfg),
+                "remove_index_11": ("INT", idx_cfg),
+                "remove_index_12": ("INT", idx_cfg),
+                "remove_index_13": ("INT", idx_cfg),
+            }
+        }
+
+    RETURN_TYPES = ("IMAGE",)
+    RETURN_NAMES = ("images",)
+    FUNCTION = "remove"
+    CATEGORY = "Batch/Index"
+
+    def remove(
+        self,
+        images,
+        remove_index_01,
+        remove_index_02,
+        remove_index_03,
+        remove_index_04,
+        remove_index_05,
+        remove_index_06,
+        remove_index_07,
+        remove_index_08,
+        remove_index_09,
+        remove_index_10,
+        remove_index_11,
+        remove_index_12,
+        remove_index_13,
+    ):
+        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 = int(images.shape[0])
+        if b <= 0:
+            raise ValueError("Input batch is empty.")
+
+        raw_indices = [
+            remove_index_01, remove_index_02, remove_index_03, remove_index_04, remove_index_05,
+            remove_index_06, remove_index_07, remove_index_08, remove_index_09, remove_index_10,
+            remove_index_11, remove_index_12, remove_index_13,
+        ]
+
+        # Build a set of indices to remove (simultaneous removal)
+        remove_set = set()
+        for idx in raw_indices:
+            idx = int(idx)
+
+            # Sentinel: -1 means "do not remove"
+            if idx == -1:
+                continue
+
+            # Disallow other negative indices (since -1 is reserved)
+            if idx < -1:
+                print(f"[BatchRemove13] Ignoring invalid negative index {idx} (only -1 is allowed).")
+                continue
+
+            # Ignore out-of-range indices rather than clamping (clamping could remove the wrong image)
+            if idx < 0 or idx >= b:
+                print(f"[BatchRemove13] Ignoring out-of-range index {idx} for batch size {b}.")
+                continue
+
+            remove_set.add(idx)
+
+        # If nothing to remove, return original batch unchanged
+        if not remove_set:
+            return (images,)
+
+        if len(remove_set) >= b:
+            raise ValueError(
+                f"Removal would produce an empty batch (batch size {b}, requested removals {len(remove_set)})."
+            )
+
+        # Keep mask (True = keep, False = remove)
+        keep_mask = torch.ones((b,), dtype=torch.bool, device=images.device)
+        remove_idx = torch.tensor(sorted(remove_set), dtype=torch.long, device=images.device)
+        keep_mask[remove_idx] = False
+
+        out = images[keep_mask]
+        return (out,)
+
+
+NODE_CLASS_MAPPINGS = {
+    "BatchRemoveImagesAt13Indices": BatchRemoveImagesAt13Indices,
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "BatchRemoveImagesAt13Indices": "Batch: Remove 13 Indices (At Once)",
+}