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feat: add upper-triangle artist matrix + naming

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- Add matrix_mode to XY Matrix (full/upper_triangle/diagonal_only)
- XY Plot can render triangular inputs as full NxN with lower triangle masked
- Add XY Cell Prefix node to name per-cell outputs (aligns with matrix_mode)
- Update ArtistBlendXYPlot_Test workflow
This commit is contained in:
Nakano Kenji
2026-02-02 19:41:04 +08:00
parent 0b1a30bee0
commit 324fe2a7ef
6 changed files with 351 additions and 20 deletions
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__init__.py
+3
View File
@@ -24,6 +24,7 @@ from .nodes import (
SimpleChatImageGrid,
SimpleChatAnimaPromptXYMatrix,
SimpleChatXYPlot,
SimpleChatXYCellPrefix,
)
# Register API routes
@@ -51,6 +52,7 @@ NODE_CLASS_MAPPINGS = {
"SimpleChatImageGrid": SimpleChatImageGrid,
"SimpleChatAnimaPromptXYMatrix": SimpleChatAnimaPromptXYMatrix,
"SimpleChatXYPlot": SimpleChatXYPlot,
"SimpleChatXYCellPrefix": SimpleChatXYCellPrefix,
}
# Display names for the UI
@@ -74,6 +76,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
"SimpleChatImageGrid": "Image Grid (Batch)",
"SimpleChatAnimaPromptXYMatrix": "Anima XY Matrix (JSON List)",
"SimpleChatXYPlot": "XY Plot (Labels)",
"SimpleChatXYCellPrefix": "XY Cell Prefix (Batch)",
}
# Expose web directory for JS extensions
assets/ArtistBlendXYPlot_Test.json
+28 -5
View File
@@ -1,8 +1,8 @@
{
"id": "simplechat-artist-blend-xyplot-test",
"revision": 0,
"last_node_id": 13,
"last_link_id": 20,
"last_node_id": 14,
"last_link_id": 23,
"nodes": [
{
"id": 1,
@@ -68,7 +68,8 @@
"combine",
"newline",
"\\n",
true
true,
"upper_triangle"
]
},
{
@@ -197,12 +198,31 @@
"order": 9,
"mode": 0,
"inputs": [
{ "name": "images", "type": "IMAGE", "link": 14 }
{ "name": "images", "type": "IMAGE", "link": 14 },
{ "name": "filename_prefix", "type": "STRING", "link": 23 }
],
"outputs": [],
"properties": { "Node name for S&R": "SaveImage" },
"widgets_values": ["artist_blend_each"]
},
{
"id": 14,
"type": "SimpleChatXYCellPrefix",
"pos": [1460, 1020],
"size": [420, 220],
"flags": {},
"order": 10,
"mode": 0,
"inputs": [
{ "name": "x_labels", "type": "STRING", "link": 21 },
{ "name": "y_labels", "type": "STRING", "link": 22 }
],
"outputs": [
{ "name": "filename_prefix", "type": "STRING", "links": [23] }
],
"properties": { "aux_id": "Moeblack/ComfyUI-SimpleChat", "Node name for S&R": "SimpleChatXYCellPrefix" },
"widgets_values": ["+", true, "", true, "upper_triangle"]
},
{
"id": 10,
"type": "SimpleChatXYPlot",
@@ -273,7 +293,10 @@
[17, 3, 3, 10, 3, "STRING"],
[18, 9, 0, 10, 0, "IMAGE"],
[19, 10, 0, 11, 0, "IMAGE"],
[20, 10, 0, 12, 0, "IMAGE"]
[20, 10, 0, 12, 0, "IMAGE"],
[21, 3, 2, 14, 0, "STRING"],
[22, 3, 3, 14, 1, "STRING"],
[23, 14, 0, 13, 1, "STRING"]
],
"groups": [],
"config": {},
nodes/__init__.py
+2
View File
@@ -20,6 +20,7 @@ from .anima_prompt_router import SimpleChatAnimaPromptRouter
from .anima_prompt_xy_matrix import SimpleChatAnimaPromptXYMatrix
from .image_grid import SimpleChatImageGrid
from .image_xy_plot import SimpleChatXYPlot
from .xy_cell_prefix import SimpleChatXYCellPrefix
__all__ = [
"SimpleChatConfig",
@@ -41,4 +42,5 @@ __all__ = [
"SimpleChatAnimaPromptXYMatrix",
"SimpleChatImageGrid",
"SimpleChatXYPlot",
"SimpleChatXYCellPrefix",
]
nodes/anima_prompt_xy_matrix.py
+31 -3
View File
@@ -204,6 +204,14 @@ class SimpleChatAnimaPromptXYMatrix:
"pair_join": (["newline", "comma", "space", "custom"], {"default": "newline"}),
"custom_join": ("STRING", {"default": "\\n", "tooltip": "Used when pair_join=custom. Use \\n for newline."}),
"diagonal_single": ("BOOLEAN", {"default": True, "tooltip": "When X==Y, use single value on diagonal (recommended)."}),
# Keep this as the last widget for backward compatibility with older workflows.
"matrix_mode": (
["full", "upper_triangle", "diagonal_only"],
{
"default": "full",
"tooltip": "When x_field==y_field (e.g. artist x artist), choose full matrix or run fewer cells.",
},
),
}
}
@@ -233,6 +241,7 @@ class SimpleChatAnimaPromptXYMatrix:
pair_join: str = "newline",
custom_join: str = "\\n",
diagonal_single: bool = True,
matrix_mode: str = "full",
):
raw = _strip_code_fence(json_text) if strip_code_fence else json_text
base = _try_parse_json(raw) if isinstance(raw, str) else raw
@@ -311,11 +320,30 @@ class SimpleChatAnimaPromptXYMatrix:
return json.dumps(obj, ensure_ascii=False, indent=2)
same_axis = (x_key and y_key and x_key == y_key) or (x_field == y_field)
# Row-major (y rows)
out_list: List[str] = []
for yv in ys:
for xv in xs:
out_list.append(_build_one(xv, yv))
if matrix_mode != "full" and same_axis and len(xs) == len(ys):
n = len(xs)
if matrix_mode == "upper_triangle":
for r in range(n):
yv = ys[r]
for c in range(r, n):
xv = xs[c]
out_list.append(_build_one(xv, yv))
elif matrix_mode == "diagonal_only":
for i in range(n):
out_list.append(_build_one(xs[i], ys[i]))
else:
# Unknown mode -> fallback
for yv in ys:
for xv in xs:
out_list.append(_build_one(xv, yv))
else:
for yv in ys:
for xv in xs:
out_list.append(_build_one(xv, yv))
columns = len(xs)
x_labels = "\n".join(xs)
nodes/image_xy_plot.py
+133 -12
View File
@@ -8,13 +8,56 @@ This is meant for fast artist/background testing.
from __future__ import annotations
import math
from typing import List, Tuple
from typing import Any, List, Tuple
import numpy as np
import torch
from PIL import Image, ImageDraw, ImageFont
def _first(v: Any, default: Any = None) -> Any:
if isinstance(v, (list, tuple)):
return v[0] if len(v) > 0 else default
return v
def _flatten_images(images: Any) -> torch.Tensor:
"""
Accept either:
- torch.Tensor: (B,H,W,C) or (H,W,C)
- list/tuple of torch.Tensor batches (common when upstream is OUTPUT_IS_LIST)
Return a single torch.Tensor (B,H,W,C).
"""
if isinstance(images, torch.Tensor):
t = images
if t.dim() == 3:
t = t.unsqueeze(0)
return t
if isinstance(images, (list, tuple)):
batches: list[torch.Tensor] = []
for item in images:
if item is None:
continue
if isinstance(item, torch.Tensor):
t = item
if t.dim() == 3:
t = t.unsqueeze(0)
if t.dim() != 4:
raise ValueError(f"Expected IMAGE tensor with 4 dims (B,H,W,C), got shape={tuple(t.shape)}")
batches.append(t)
continue
if isinstance(item, (list, tuple)):
batches.append(_flatten_images(item))
continue
raise ValueError(f"Unsupported images list element type: {type(item)}")
if not batches:
raise ValueError("images list is empty.")
return torch.cat(batches, dim=0)
raise ValueError(f"Unsupported images type: {type(images)}")
def _split_labels(text: str) -> List[str]:
if not isinstance(text, str):
return []
@@ -43,6 +86,9 @@ def _to_tensor(img: Image.Image) -> torch.Tensor:
class SimpleChatXYPlot:
# If upstream provides a list (from OUTPUT_IS_LIST), run ONCE with the whole list.
INPUT_IS_LIST = True
@classmethod
def INPUT_TYPES(cls):
return {
@@ -70,7 +116,7 @@ class SimpleChatXYPlot:
def plot(
self,
images: torch.Tensor,
images: Any,
columns: int = 4,
x_labels: str = "",
y_labels: str = "",
@@ -80,26 +126,61 @@ class SimpleChatXYPlot:
text_color: str = "white",
title: str = "",
):
# When INPUT_IS_LIST=True, many inputs may arrive as lists; pick the first.
columns = _first(columns, 4)
x_labels = _first(x_labels, "") or ""
y_labels = _first(y_labels, "") or ""
padding = _first(padding, 8)
label_padding = _first(label_padding, 8)
bg_color = _first(bg_color, "black")
text_color = _first(text_color, "white")
title = _first(title, "") or ""
images = _flatten_images(images)
if images is None or not isinstance(images, torch.Tensor):
raise ValueError("images must be a torch Tensor (ComfyUI IMAGE).")
raise ValueError("images must be a torch Tensor (ComfyUI IMAGE) or a list of IMAGE tensors.")
if images.dim() != 4:
raise ValueError(f"Expected IMAGE tensor with 4 dims (B,H,W,C), got shape={tuple(images.shape)}")
b, h, w, c = images.shape
columns = max(1, int(columns))
rows = int(math.ceil(b / columns)) if b > 0 else 1
padding = max(0, int(padding))
label_padding = max(0, int(label_padding))
xs = _split_labels(x_labels)
ys = _split_labels(y_labels)
has_x_labels = len(xs) > 0
has_y_labels = len(ys) > 0
# Try to align labels length with grid
# Prefer labels to define grid shape (scientific-style XY plots).
if has_x_labels:
columns = max(1, len(xs))
rows = int(math.ceil(b / columns)) if b > 0 else 1
if has_y_labels:
rows = max(1, len(ys))
# Ensure grid is large enough to hold all images.
if b > rows * columns:
rows = int(math.ceil(b / columns))
# Pad labels if too short.
if len(xs) < columns:
xs = xs + [""] * (columns - len(xs))
if len(ys) < rows:
ys = ys + [""] * (rows - len(ys))
# Detect triangular inputs for square grids:
# - upper_triangle: N(N+1)/2 images (row-major over cells where col>=row)
# - diagonal_only: N images (row-major over diag cells)
triangle_mode = None # "upper_triangle" | "diagonal_only"
if has_x_labels and has_y_labels and rows == columns:
n = columns
if b == (n * (n + 1)) // 2:
triangle_mode = "upper_triangle"
elif b == n:
triangle_mode = "diagonal_only"
# Font
font = ImageFont.load_default()
@@ -149,13 +230,53 @@ class SimpleChatXYPlot:
draw.text((x0, y_cursor), label, fill=fg, font=font)
y_cursor += x_h + label_padding
# Paste images + Y labels
for idx in range(b):
r = idx // columns
col = idx % columns
x = left_margin + col * (w + padding)
y = y_cursor + r * (h + padding)
canvas.paste(_to_pil(images[idx]), (x, y))
# Paste images (+ fill masked cells for triangular layouts)
# Use a mid-gray mask for the unused half (common in scientific matrices).
mask_color = (64, 64, 64) if bg_color == "black" else (220, 220, 220)
mask = Image.new("RGB", (w, h), color=mask_color)
if triangle_mode == "upper_triangle":
idx = 0
for r in range(rows):
for col in range(columns):
x = left_margin + col * (w + padding)
y = y_cursor + r * (h + padding)
if col < r:
canvas.paste(mask, (x, y))
continue
if idx < b:
canvas.paste(_to_pil(images[idx]), (x, y))
idx += 1
else:
canvas.paste(mask, (x, y))
elif triangle_mode == "diagonal_only":
idx = 0
for r in range(rows):
for col in range(columns):
x = left_margin + col * (w + padding)
y = y_cursor + r * (h + padding)
if col == r and idx < b:
canvas.paste(_to_pil(images[idx]), (x, y))
idx += 1
else:
canvas.paste(mask, (x, y))
else:
# Standard row-major fill
max_cells = rows * columns
for idx in range(min(b, max_cells)):
r = idx // columns
col = idx % columns
x = left_margin + col * (w + padding)
y = y_cursor + r * (h + padding)
canvas.paste(_to_pil(images[idx]), (x, y))
# Fill remaining cells (if any) for a tidy grid.
if b < max_cells:
for idx in range(b, max_cells):
r = idx // columns
col = idx % columns
x = left_margin + col * (w + padding)
y = y_cursor + r * (h + padding)
canvas.paste(mask, (x, y))
if y_w > 0:
for r in range(rows):
nodes/xy_cell_prefix.py
+154
View File
@@ -0,0 +1,154 @@
"""
XY Cell Prefix (Batch)
Generate a filename_prefix list for each XY cell (row-major),
without changing the prompt itself.
Typical use:
- Connect x_labels/y_labels from `Anima XY Matrix (JSON List)`
- Connect output `filename_prefix` to `SaveImage.filename_prefix`
"""
from __future__ import annotations
import re
from typing import Any, List
_ILLEGAL_FS_CHARS_RE = re.compile(r'[<>:"/\\\\|?*]+')
_WS_RE = re.compile(r"\s+")
def _first(v: Any, default: Any = None) -> Any:
if isinstance(v, (list, tuple)):
return v[0] if len(v) > 0 else default
return v
def _split_labels(text: str) -> List[str]:
if not isinstance(text, str):
return []
raw = text.replace("\r\n", "\n").replace("\r", "\n")
out: List[str] = []
for line in raw.split("\n"):
s = (line or "").strip()
if not s:
continue
if s.startswith("#") or s.startswith("//"):
continue
out.append(s)
return out
def _sanitize_prefix(s: str, max_len: int = 120) -> str:
s = (s or "").strip()
if not s:
return ""
s = _ILLEGAL_FS_CHARS_RE.sub("_", s)
s = s.replace("\n", "_").replace("\r", "_").replace("\t", "_")
s = _WS_RE.sub("_", s)
s = s.strip(" .") # Windows doesn't allow trailing dot/space
if len(s) > max_len:
s = s[:max_len].rstrip(" .")
return s
class SimpleChatXYCellPrefix:
"""
Build per-cell filename prefixes from x/y labels.
- Row-major order (y rows, then x columns), matching `SimpleChatAnimaPromptXYMatrix`.
- Diagonal can be single name when x==y.
- Default joiner for display is '+' (purely for naming; doesn't affect prompts).
"""
# In list pipelines, run ONCE with the whole list (avoid N-times expansion).
INPUT_IS_LIST = True
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"x_labels": ("STRING", {"multiline": True, "default": "", "forceInput": True}),
"y_labels": ("STRING", {"multiline": True, "default": "", "forceInput": True}),
},
"optional": {
"joiner": ("STRING", {"default": "+"}),
"diagonal_single": ("BOOLEAN", {"default": True}),
"base_prefix": ("STRING", {"default": ""}),
"sanitize": ("BOOLEAN", {"default": True}),
# Keep this as the last widget for future backward compatibility.
"matrix_mode": (["full", "upper_triangle", "diagonal_only"], {"default": "full"}),
},
}
RETURN_TYPES = ("STRING",)
RETURN_NAMES = ("filename_prefix",)
OUTPUT_IS_LIST = (True,)
FUNCTION = "build"
CATEGORY = "SimpleChat/Utils"
DESCRIPTION = "Build per-cell filename_prefix list from x/y labels (row-major), for SaveImage."
def build(
self,
x_labels: Any,
y_labels: Any,
joiner: Any = "+",
diagonal_single: Any = True,
base_prefix: Any = "",
sanitize: Any = True,
matrix_mode: Any = "full",
):
x_labels = _first(x_labels, "") or ""
y_labels = _first(y_labels, "") or ""
joiner = str(_first(joiner, "+") or "+")
diagonal_single = bool(_first(diagonal_single, True))
base_prefix = str(_first(base_prefix, "") or "")
sanitize = bool(_first(sanitize, True))
matrix_mode = str(_first(matrix_mode, "full") or "full")
xs = _split_labels(x_labels)
ys = _split_labels(y_labels)
if not xs:
xs = [""]
if not ys:
ys = [""]
def _one(x: str, y: str) -> str:
xa = (x or "").strip()
ya = (y or "").strip()
if diagonal_single and xa and ya and xa == ya:
name = xa
else:
if xa and ya:
name = f"{xa}{joiner}{ya}"
else:
name = xa or ya or ""
if base_prefix:
name = f"{base_prefix}{name}"
if sanitize:
name = _sanitize_prefix(name)
return name or "cell"
out: List[str] = []
if matrix_mode != "full" and len(xs) == len(ys):
n = len(xs)
if matrix_mode == "upper_triangle":
for r in range(n):
for c in range(r, n):
out.append(_one(xs[c], ys[r]))
elif matrix_mode == "diagonal_only":
for i in range(n):
out.append(_one(xs[i], ys[i]))
else:
for y in ys:
for x in xs:
out.append(_one(x, y))
else:
for y in ys:
for x in xs:
out.append(_one(x, y))
return (out,)