header cleanup, variable cleanup, license for comfyui.org

.gitattributes

@@ -0,0 +1,2 @@
+# Auto detect text files and perform LF normalization
+* text=auto

.gitignore

@@ -1,10 +1,15 @@
-# Byte-compiled / optimized / DLL files
-__pycache__/
+__pycache__
 *.py[cod]
 *$py.class
 _*
 *.code-workspace
-.vscode/
+.vscode
 config.json
 ignore.txt
-.env
+.env
+.DS_Store
+*.egg-info
+*.bak
+checkpoints
+results
+backup

__init__.py

@@ -8,36 +8,22 @@
               Animation, Image Compositing & Procedural Creation
                     http://www.github.com/amorano/jovimetrix
 
-                    Copyright Alexander G. Morano (Joviex)
-
-Permission is hereby granted, free of charge, to any person obtaining a copy
-of this software and associated documentation files (the "Software"), to deal
-in the Software without restriction, including without limitation the rights
-to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-copies of the Software, and to permit persons to whom the Software is
-furnished to do so, subject to the following conditions:
-
-The above copyright notice and this permission notice shall be included in all
-copies or substantial portions of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-SOFTWARE.
-
-GO NUTS; JUST TRY NOT TO DO IT IN YOUR HEAD.
-
 @title: Jovimetrix
 @author: amorano
 @category: Compositing
 @reference: https://github.com/Amorano/Jovimetrix
-@tags: adjust, animate, compose, compositing, composition, device, flow, video, mask, shape, webcam, animation, logic
-@description: Integrates Webcam, MIDI, Spout and GLSL shader support. Animation via tick. Parameter manipulation with wave generator. Math operations with Unary and Binary support. Value converstion for all major types (int, string, list, dict, Image, Mask). Shape mask generation, image stacking and channel ops, batch splitting, merging and randomizing, load images and video from anywhere, dynamic bus routing with a single node, export support for GIPHY, save output anywhere! flatten, crop, transform; check colorblindness, make stereogram or stereoscopic images, or liner interpolate values and more.
+@tags: adjust, animate, compose, compositing, composition, device, flow, video,
+mask, shape, webcam, animation, logic
+@description: Integrates Webcam, MIDI, Spout and GLSL shader support. Animation
+via tick. Parameter manipulation with wave generator. Math operations with Unary
+and Binary support. Value converstion for all major types (int, string, list,
+dict, Image, Mask). Shape mask generation, image stacking and channel ops, batch
+splitting, merging and randomizing, load images and video from anywhere, dynamic
+bus routing with a single node, export support for GIPHY, save output anywhere!
+flatten, crop, transform; check colorblindness, make stereogram or stereoscopic
+images, or liner interpolate values and more.
 @node list:
-    ConstantNode, ConstantNode, ShapeNode, StereogramNode, StereoscopicNode, TextNode, WaveGraphNode,
+    ConstantNode, GLSLNode, ShapeNode, StereogramNode, StereoscopicNode, TextNode, WaveGraphNode,
     AdjustNode, ColorBlindNode, ColorMatchNode, FilterMaskNode, ThresholdNode,
     BlendNode, ColorTheoryNode, CropNode, FlattenNode, PixelMergeNode, PixelSplitNode,
     PixelSwapNode, StackNode, TransformNode
@@ -48,7 +34,7 @@
     StreamReaderNode, StreamWriterNode, SpoutWriter,
     AkashicNode, ArrayNode, BatchLoadNode, DynamicNode, ValueGraphNode, ExportNode, QueueNode,
     RouteNode, SaveOutputNode
-@version: 1.2.0
+@version: 1.2.6
 """
 
 import os

core/utility.py

@@ -129,7 +129,7 @@ class ArrayNode(JOVBaseNode):
     NAME = "ARRAY (JOV) 📚"
     CATEGORY = f"JOVIMETRIX 🔺🟩🔵/{JOV_CATEGORY}"
     RETURN_TYPES = (JOV_TYPE_ANY, JOV_TYPE_ANY, "INT")
-    RETURN_NAMES = (Lexicon.ANY_OUT, Lexicon.LIST, Lexicon.VALUE)
+    RETURN_NAMES = (Lexicon.ANY_OUT, Lexicon.LIST, Lexicon.LENGTH)
     SORT = 50
     DESCRIPTION = """
 Processes a batch of data based on the selected mode, such as merging, picking, slicing, random selection, or indexing. Allows for flipping the order of processed items and dividing the data into chunks.
@@ -145,14 +145,14 @@ def INPUT_TYPES(cls) -> dict:
                 Lexicon.RANGE: ("VEC3", {"default": (0, 0, 1), "min": 0, "step": 1}),
                 Lexicon.STRING: ("STRING", {"default": "", "tooltip":"Comma separated list of indicies to export"}),
                 Lexicon.SEED: ("INT", {"default": 0, "min": 0, "max": sys.maxsize, "step": 1}),
-                Lexicon.COUNT: ("INT", {"default": 1, "min": 1, "max": sys.maxsize, "step": 1, "tooltip":"How many items to return"}),
+                Lexicon.COUNT: ("INT", {"default": 0, "min": 0, "max": sys.maxsize, "step": 1, "tooltip":"How many items to return"}),
                 Lexicon.FLIP: ("BOOLEAN", {"default": False, "tooltip":"invert the calculated output list"}),
                 Lexicon.BATCH_CHUNK: ("INT", {"default": 0, "min": 0, "step": 1}),
             },
             "outputs": {
                 0: (Lexicon.ANY_OUT, {"tooltip":"Output list from selected operation"}),
                 1: (Lexicon.LIST, {"tooltip":"Full list"}),
-                2: (Lexicon.VALUE, {"tooltip":"Length of output list"}),
+                2: (Lexicon.LENGTH, {"tooltip":"Length of output list"}),
             }
         })
         return Lexicon._parse(d, cls)
@@ -175,7 +175,7 @@ def run(self, **kw) -> Tuple[int, list]:
         slice_range = parse_param(kw, Lexicon.RANGE, EnumConvertType.VEC3INT, [(0, 0, 1)])
         indices = parse_param(kw, Lexicon.STRING, EnumConvertType.STRING, "")
         seed = parse_param(kw, Lexicon.SEED, EnumConvertType.INT, 0)
-        count = parse_param(kw, Lexicon.COUNT, EnumConvertType.INT, 1, 1)
+        count = parse_param(kw, Lexicon.COUNT, EnumConvertType.INT, 0, 0)
         flip = parse_param(kw, Lexicon.FLIP, EnumConvertType.BOOLEAN, False)
         batch_chunk = parse_param(kw, Lexicon.BATCH_CHUNK, EnumConvertType.INT, 0, 0)
         extract = []
@@ -206,6 +206,7 @@ def run(self, **kw) -> Tuple[int, list]:
         pbar = ProgressBar(len(params))
         for idx, (mode, index, slice_range, indices, seed, flip, batch_chunk, count) in enumerate(params):
             loop_extract = extract.copy()
+
             if len(loop_extract) == 0:
                 results.append([None, None, 0])
                 pbar.update_absolute(idx)
@@ -217,7 +218,7 @@ def run(self, **kw) -> Tuple[int, list]:
             mode = EnumBatchMode[mode]
             if mode == EnumBatchMode.PICK:
                 index = index if index < len(loop_extract) else -1
-                loop_extract = loop_extract[index]
+                loop_extract = [loop_extract[index]]
             elif mode == EnumBatchMode.SLICE:
                 start, end, step = slice_range
                 end = len(loop_extract) if end == 0 else end
@@ -226,11 +227,9 @@ def run(self, **kw) -> Tuple[int, list]:
                 if self.__seed is None or self.__seed != seed:
                     random.seed(seed)
                     self.__seed = seed
-                val = []
-                for i in range(count):
-                    index = random.randrange(0, len(loop_extract))
-                    val.append(loop_extract[index])
-                loop_extract = val
+                if count == 0:
+                    count = len(loop_extract)
+                loop_extract = random.sample(loop_extract, k=count)
             elif mode == EnumBatchMode.INDEX_LIST:
                 junk = []
                 for x in indices.strip().split(','):
@@ -248,24 +247,23 @@ def run(self, **kw) -> Tuple[int, list]:
             elif mode == EnumBatchMode.CARTESIAN:
                 logger.warning("NOT IMPLEMENTED - CARTESIAN")
 
-            if not isinstance(loop_extract, (list,)):
-                loop_extract = [loop_extract]
-
             if len(loop_extract) == 0:
                 loop_extract = extract.copy()
 
             if batch_chunk > 0:
                 loop_extract = self.batched(loop_extract, batch_chunk)
+
             if not output_is_image:
                 results.append([*loop_extract, loop_extract, len(loop_extract)])
             else:
                 img.extend(loop_extract)
+                print(len(img))
                 results.append([loop_extract, len(loop_extract)])
             pbar.update_absolute(idx)
         if not output_is_image:
             return list(zip(*results))
         ret = torch.stack(img, dim=0)
-        return ret, *results
+        return ret, list(zip(*results))
 
 class ExportNode(JOVBaseNode):
     NAME = "EXPORT (JOV) 📽"

pyproject.toml

@@ -1,8 +1,8 @@
 [project]
 name = "jovimetrix"
 description = "Integrates Webcam, MIDI, Spout and GLSL shader support. Animation via tick. Parameter manipulation with wave generator. Math operations with Unary and Binary support. Value conversion for all major types (int, string, list, dict, Image, Mask). Shape mask generation, image stacking and channel ops, batch splitting, merging and randomizing, load images and video from anywhere, dynamic bus routing with a single node, export support for GIPHY, save output anywhere! flatten, crop, transform; check colorblindness, make stereogram or stereoscopic images, or liner interpolate values and more."
-version = "1.2.5"
-license = "MIT"
+version = "1.2.6"
+license = { file = "LICENSE" }
 dependencies = [
     "aenum>=3.1.15, <4",
     "blendmodes>=2024.1.1",

sup/lexicon.py

@@ -131,6 +131,7 @@ class Lexicon(metaclass=LexiconMeta):
     KEY = '🔑', "Key"
     LACUNARITY = 'LACUNARITY', "LACUNARITY"
     LEFT = '◀️', "Left"
+    LENGTH = 'LENGTH', "Length"
     LETTER = 'LETTER', "If each letter be generated and output in a batch"
     LINEAR = '🛟', "Linear"
     LIST = '🧾', "List"