rename of types.py to dreamtypes.py

Allows to output name of frame file

__init__.py

@@ -5,12 +5,16 @@ from .base import *
 from .colors import *
 from .curves import *
 from .image_processing import *
+from .inputfields import *
 from .loaders import *
 from .noise import *
 from .output import *
+from .prompting import *
 from .seq_processing import *
+from .switches import *
 from .utility import *
-from .inputfields import *
+from .calculate import *
+from .laboratory import *
 
 _NODE_CLASSES: List[Type] = [DreamSineWave, DreamLinear, DreamCSVCurve, DreamBeatCurve, DreamFrameDimensions,
                              DreamImageMotion, DreamNoiseFromPalette, DreamAnalyzePalette, DreamColorShift,
@@ -19,12 +23,19 @@ _NODE_CLASSES: List[Type] = [DreamSineWave, DreamLinear, DreamCSVCurve, DreamBea
                              DreamImageSequenceOutput, DreamCSVGenerator, DreamImageAreaSampler,
                              DreamVideoEncoder, DreamSequenceTweening, DreamSequenceBlend, DreamColorAlign,
                              DreamImageSampler, DreamNoiseFromAreaPalettes, DreamVideoEncoderMpegCoder,
-                             DreamInputString, DreamInputFloat, DreamInputInt, DreamInputText]
+                             DreamInputString, DreamInputFloat, DreamInputInt, DreamInputText, DreamBigLatentSwitch,
+                             DreamFrameCountCalculator, DreamBigImageSwitch, DreamBigTextSwitch, DreamBigFloatSwitch,
+                             DreamBigIntSwitch, DreamBigPaletteSwitch, DreamWeightedPromptBuilder, DreamPromptFinalizer,
+                             DreamFrameCounterInfo, DreamBoolToFloat, DreamBoolToInt, DreamSawWave, DreamTriangleWave,
+                             DreamTriangleEvent, DreamSmoothEvent, DreamCalculation, DreamImageColorShift,
+                             DreamComparePalette, DreamImageContrast, DreamImageBrightness, DreamLogFile,
+                             DreamLaboratory, DreamStringToLog, DreamIntToLog, DreamFloatToLog, DreamJoinLog,
+                             DreamStringTokenizer, DreamWavCurve, DreamFrameCounterTimeOffset]
 _SIGNATURE_SUFFIX = " [Dream]"
 
 MANIFEST = {
     "name": "Dream Project Animation",
-    "version": (3, 0, 1),
+    "version": (4, 3, 1),
     "author": "Dream Project",
     "project": "https://github.com/alt-key-project/comfyui-dream-project",
     "description": "Various utility nodes for creating animations with ComfyUI",

base.py

@@ -3,7 +3,38 @@ import glob
 
 from .categories import NodeCategories
 from .shared import *
-from .types import *
+from .dreamtypes import *
+
+
+class DreamFrameCounterInfo:
+    NODE_NAME = "Frame Counter Info"
+    ICON = "⚋"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": SharedTypes.frame_counter
+        }
+
+    CATEGORY = NodeCategories.ANIMATION
+    RETURN_TYPES = ("INT", "INT", "BOOLEAN", "BOOLEAN", "FLOAT", "FLOAT", "FLOAT", "FLOAT")
+    RETURN_NAMES = ("frames_completed", "total_frames", "first_frame", "last_frame",
+                    "elapsed_seconds", "remaining_seconds", "total_seconds", "completion")
+    FUNCTION = "result"
+
+    @classmethod
+    def IS_CHANGED(cls, *v):
+        return ALWAYS_CHANGED_FLAG
+
+    def result(self, frame_counter: FrameCounter):
+        return (frame_counter.current_frame,
+                frame_counter.total_frames,
+                frame_counter.is_first_frame,
+                frame_counter.is_final_frame,
+                frame_counter.current_time_in_seconds,
+                frame_counter.remaining_time_in_seconds,
+                frame_counter.total_time_in_seconds,
+                frame_counter.current_time_in_seconds / max(0.01, frame_counter.total_time_in_seconds))
 
 
 class DreamDirectoryFileCount:
@@ -35,7 +66,7 @@ class DreamDirectoryFileCount:
         for pattern in patterns.split("|"):
             files = list(glob.glob(pattern, root_dir=directory_path))
             total += len(files)
-        print("total "+str(total))
+        print("total " + str(total))
         return (total,)
 
 
@@ -64,6 +95,32 @@ class DreamFrameCounterOffset:
     def result(self, frame_counter: FrameCounter, offset):
         return (frame_counter.incremented(offset),)
 
+class DreamFrameCounterTimeOffset:
+    NODE_NAME = "Frame Counter Time Offset"
+
+    ICON = "±"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": SharedTypes.frame_counter | {
+                "offset_seconds": ("FLOAT", {"default": 0.0}),
+            },
+        }
+
+    CATEGORY = NodeCategories.ANIMATION
+    RETURN_TYPES = (FrameCounter.ID,)
+    RETURN_NAMES = ("frame_counter",)
+    FUNCTION = "result"
+
+    @classmethod
+    def IS_CHANGED(cls, frame_counter, offset):
+        return hashed_as_strings(frame_counter, offset)
+
+    def result(self, frame_counter: FrameCounter, offset_seconds):
+        offset = offset_seconds * frame_counter.frames_per_second
+        return (frame_counter.incremented(offset),)
+
 
 class DreamSimpleFrameCounter:
     NODE_NAME = "Frame Counter (Simple)"
@@ -105,7 +162,7 @@ class DreamDirectoryBackedFrameCounter:
                 "pattern": ("STRING", {"default": '*', "multiline": False}),
                 "indexing": (["numeric", "alphabetic order"],),
                 "total_frames": ("INT", {"default": 100, "min": 2, "max": 24 * 3600 * 60}),
-                "frames_per_second": ("INT", {"min": 1, "default": 25}),
+                "frames_per_second": ("INT", {"min": 1, "default": 30}),
             },
         }
 
@@ -124,3 +181,33 @@ class DreamDirectoryBackedFrameCounter:
             return (FrameCounter(0, total_frames, frames_per_second),)
         n = max(results.keys()) + 1
         return (FrameCounter(n, total_frames, frames_per_second),)
+
+
+class DreamFrameCountCalculator:
+    NODE_NAME = "Frame Count Calculator"
+    ICON = "⌛"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "hours": ("INT", {"min": 0, "default": 0, "max": 23}),
+                "minutes": ("INT", {"min": 0, "default": 0, "max": 59}),
+                "seconds": ("INT", {"min": 0, "default": 10, "max": 59}),
+                "milliseconds": ("INT", {"min": 0, "default": 0, "max": 59}),
+                "frames_per_second": ("INT", {"min": 1, "default": 30})
+            },
+        }
+
+    CATEGORY = NodeCategories.ANIMATION
+    RETURN_TYPES = ("INT",)
+    RETURN_NAMES = ("TOTAL",)
+    FUNCTION = "result"
+
+    @classmethod
+    def IS_CHANGED(cls, *v):
+        return ALWAYS_CHANGED_FLAG
+
+    def result(self, hours, minutes, seconds, milliseconds, frames_per_second):
+        total_s = seconds + 0.001 * milliseconds + minutes * 60 + hours * 3600
+        return (round(total_s * frames_per_second),)

calculate.py

@@ -0,0 +1,99 @@
+# -*- coding: utf-8 -*-
+import math
+
+from evalidate import Expr, EvalException, base_eval_model
+
+from .categories import *
+from .err import on_error
+from .shared import hashed_as_strings
+
+
+class DreamCalculation:
+    NODE_NAME = "Calculation"
+    ICON = "🖩"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "expression": ("STRING", {"default": "a + b + c - (r * s * t)", "multiline": True})
+            },
+            "optional": {
+                "a_int": ("INT", {"default": 0, "multiline": False}),
+                "b_int": ("INT", {"default": 0, "multiline": False}),
+                "c_int": ("INT", {"default": 0, "multiline": False}),
+                "r_float": ("FLOAT", {"default": 0.0, "multiline": False}),
+                "s_float": ("FLOAT", {"default": 0.0, "multiline": False}),
+                "t_float": ("FLOAT", {"default": 0.0, "multiline": False})
+            }
+        }
+
+    CATEGORY = NodeCategories.UTILS
+    RETURN_TYPES = ("FLOAT", "INT")
+    RETURN_NAMES = ("FLOAT", "INT")
+    FUNCTION = "result"
+
+    @classmethod
+    def IS_CHANGED(cls, *values):
+        return hashed_as_strings(*values)
+
+    def _make_model(self):
+        funcs = self._make_functions()
+        m = base_eval_model.clone()
+        m.nodes.append('Mult')
+        m.nodes.append('Call')
+        for funname in funcs.keys():
+            m.allowed_functions.append(funname)
+        return (m, funcs)
+
+    def _make_functions(self):
+        return {
+            "round": round,
+            "float": float,
+            "int": int,
+            "abs": abs,
+            "min": min,
+            "max": max,
+            "tan": math.tan,
+            "tanh": math.tanh,
+            "sin": math.sin,
+            "sinh": math.sinh,
+            "cos": math.cos,
+            "cosh": math.cosh,
+            "pow": math.pow,
+            "sqrt": math.sqrt,
+            "ceil": math.ceil,
+            "floor": math.floor,
+            "pi": math.pi,
+            "log": math.log,
+            "log2": math.log2,
+            "acos": math.acos,
+            "asin": math.asin,
+            "acosh": math.acosh,
+            "asinh": math.asinh,
+            "atan": math.atan,
+            "atanh": math.atanh,
+            "exp": math.exp,
+            "fmod": math.fmod,
+            "factorial": math.factorial,
+            "dist": math.dist,
+            "atan2": math.atan2,
+            "log10": math.log10
+        }
+
+    def result(self, expression, **values):
+        model, funcs = self._make_model()
+        vars = funcs
+        for key in ("a_int", "b_int", "c_int", "r_float", "s_float", "t_float"):
+            nm = key.split("_")[0]
+            v = values.get(key, None)
+            if v is not None:
+                vars[nm] = v
+        try:
+            data = Expr(expression, model=model).eval(vars)
+            if isinstance(data, (int, float)):
+                return float(data), int(round(data))
+            else:
+                return 0.0, 0
+        except EvalException as e:
+            on_error(DreamCalculation, str(e))

categories.py

@@ -5,9 +5,11 @@ class NodeCategories:
     ANIMATION_POSTPROCESSING = ANIMATION + "/postprocessing"
     ANIMATION_TRANSFORMS = ANIMATION + "/transforms"
     ANIMATION_CURVES = "animation/curves"
+    CONDITIONING = "conditioning"
     IMAGE_POSTPROCESSING = "image/postprocessing"
     IMAGE_ANIMATION = "image/animation"
     IMAGE_COLORS = "image/color"
     IMAGE_GENERATE = "image/generate"
     IMAGE = "image"
-    UTILS = "utils"
+    UTILS = "utils"
+    UTILS_SWITCHES = "utils/switches"

colors.py

@@ -1,7 +1,8 @@
 # -*- coding: utf-8 -*-
+
 from .categories import NodeCategories
 from .shared import *
-from .types import *
+from .dreamtypes import *
 
 
 class DreamImageAreaSampler:
@@ -128,7 +129,7 @@ class DreamColorAlign:
     def INPUT_TYPES(cls):
         return {
             "required": SharedTypes.palette | {
-                "target_align": (RGBPalette.ID, ),
+                "target_align": (RGBPalette.ID,),
                 "alignment_factor": ("FLOAT", {"default": 0.5, "min": 0.0, "max": 10.0, "step": 0.1}),
             }
         }
@@ -151,8 +152,8 @@ class DreamColorAlign:
         for i in range(len(palette)):
             p = palette[i]
             t = target_align[i]
-            (_, r1, g1, b1) = p.analyze()
-            (_, r2, g2, b2) = t.analyze()
+            (_, _, r1, g1, b1) = p.analyze()
+            (_, _, r2, g2, b2) = t.analyze()
 
             dr = (r2 - r1) * alignment_factor
             dg = (g2 - g1) * alignment_factor
@@ -214,9 +215,150 @@ class DreamColorShift:
         return (tuple(results),)
 
 
+class DreamImageColorShift:
+    NODE_NAME = "Image Color Shift"
+    ICON = "🖼"
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {"image": ("IMAGE",),
+                         "red_multiplier": ("FLOAT", {"default": 1.0, "min": 0.0}),
+                         "green_multiplier": ("FLOAT", {"default": 1.0, "min": 0.0}),
+                         "blue_multiplier": ("FLOAT", {"default": 1.0, "min": 0.0}),
+                         },
+
+        }
+
+    CATEGORY = NodeCategories.IMAGE_COLORS
+    RETURN_TYPES = ("IMAGE",)
+    RETURN_NAMES = ("image",)
+    FUNCTION = "result"
+
+    @classmethod
+    def IS_CHANGED(cls, *values):
+        return ALWAYS_CHANGED_FLAG
+
+    def result(self, image, red_multiplier, green_multiplier, blue_multiplier):
+        proc = DreamImageProcessor(inputs=image)
+
+        def recolor(im: DreamImage, *a, **args):
+            return (im.adjust_colors(red_multiplier, green_multiplier, blue_multiplier),)
+
+        return proc.process(recolor)
+
+
+class DreamImageBrightness:
+    NODE_NAME = "Image Brightness Adjustment"
+    ICON = "☼"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {"image": ("IMAGE",),
+                         "factor": ("FLOAT", {"default": 1.0, "min": 0.0}),
+                         },
+
+        }
+
+    CATEGORY = NodeCategories.IMAGE_COLORS
+    RETURN_TYPES = ("IMAGE",)
+    RETURN_NAMES = ("image",)
+    FUNCTION = "result"
+
+    @classmethod
+    def IS_CHANGED(cls, *values):
+        return ALWAYS_CHANGED_FLAG
+
+    def result(self, image, factor):
+        proc = DreamImageProcessor(inputs=image)
+
+        def change(im: DreamImage, *a, **args):
+            return (im.change_brightness(factor),)
+
+        return proc.process(change)
+
+
+class DreamImageContrast:
+    NODE_NAME = "Image Contrast Adjustment"
+    ICON = "◐"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {"image": ("IMAGE",),
+                         "factor": ("FLOAT", {"default": 1.0, "min": 0.0}),
+                         },
+
+        }
+
+    CATEGORY = NodeCategories.IMAGE_COLORS
+    RETURN_TYPES = ("IMAGE",)
+    RETURN_NAMES = ("image",)
+    FUNCTION = "result"
+
+    @classmethod
+    def IS_CHANGED(cls, *values):
+        return ALWAYS_CHANGED_FLAG
+
+    def result(self, image, factor):
+        proc = DreamImageProcessor(inputs=image)
+
+        def change(im: DreamImage, *a, **args):
+            return (im.change_contrast(factor),)
+
+        return proc.process(change)
+
+
+class DreamComparePalette:
+    NODE_NAME = "Compare Palettes"
+    ICON = "📊"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "a": (RGBPalette.ID,),
+                "b": (RGBPalette.ID,),
+            },
+        }
+
+    CATEGORY = NodeCategories.IMAGE_COLORS
+    RETURN_TYPES = ("FLOAT", "FLOAT", "FLOAT", "FLOAT")
+    RETURN_NAMES = (
+        "brightness_multiplier", "contrast_multiplier", "red_multiplier", "green_multiplier", "blue_multiplier")
+    FUNCTION = "result"
+
+    @classmethod
+    def IS_CHANGED(cls, *values):
+        return ALWAYS_CHANGED_FLAG
+
+    def result(self, a, b):
+        MIN_VALUE = 1 / 255.0
+
+        brightness = list()
+        contrasts = list()
+        reds = list()
+        greens = list()
+        blues = list()
+
+        for i in range(min(len(a), len(b))):
+            (bright, ctr, red, green, blue) = a[i].analyze()
+            (bright2, ctr2, red2, green2, blue2) = b[i].analyze()
+            brightness.append(bright2 / max(MIN_VALUE, bright))
+            contrasts.append(ctr2 / max(MIN_VALUE, ctr))
+            reds.append(red2 / max(MIN_VALUE, red))
+            greens.append(green2 / max(MIN_VALUE, green))
+            blues.append(blue2 / max(MIN_VALUE, blue))
+
+        n = len(brightness)
+
+        return (sum(brightness) / n, sum(contrasts) / n, sum(reds) / n,
+                sum(greens) / n, sum(blues) / n)
+
+
 class DreamAnalyzePalette:
     NODE_NAME = "Analyze Palette"
-    NODE = "📊"
+    ICON = "📊"
 
     @classmethod
     def INPUT_TYPES(cls):
@@ -226,8 +368,8 @@ class DreamAnalyzePalette:
         }
 
     CATEGORY = NodeCategories.IMAGE_COLORS
-    RETURN_TYPES = ("FLOAT", "FLOAT", "FLOAT", "FLOAT")
-    RETURN_NAMES = ("brightness", "redness", "greenness", "blueness")
+    RETURN_TYPES = ("FLOAT", "FLOAT", "FLOAT", "FLOAT", "FLOAT")
+    RETURN_NAMES = ("brightness", "contrast", "redness", "greenness", "blueness")
     FUNCTION = "result"
 
     @classmethod
@@ -236,12 +378,13 @@ class DreamAnalyzePalette:
 
     def result(self, palette):
         f = 1.0 / len(palette)
-        (w, r, g, b) = (0, 0, 0, 0)
+        (w, c, r, g, b) = (0, 0, 0, 0, 0)
         for p in palette:
-            (brightness, red, green, blue) = p.analyze()
+            (brightness, contrast, red, green, blue) = p.analyze()
             w += brightness
+            c += contrast
             r += red
             g += green
             b += blue
 
-        return w * f, r * f, g * f, b * f
+        return w * f, c * f, r * f, g * f, b * f

curves.py

@@ -1,10 +1,28 @@
 # -*- coding: utf-8 -*-
 import csv
+import functools
 import math
+import os
+
+from scipy.io.wavfile import read as wav_read
 
 from .categories import NodeCategories
 from .shared import hashed_as_strings
-from .types import SharedTypes, FrameCounter
+from .dreamtypes import SharedTypes, FrameCounter
+
+
+def _linear_value_calc(x, x_start, x_end, y_start, y_end):
+    if x <= x_start:
+        return y_start
+    if x >= x_end:
+        return y_end
+    dx = max(x_end - x_start, 0.0001)
+    n = (x - x_start) / dx
+    return (y_end - y_start) * n + y_start
+
+
+def _curve_result(f: float):
+    return (f, int(round(f)))
 
 
 class DreamSineWave:
@@ -37,7 +55,213 @@ class DreamSineWave:
         b = 2 * math.pi / periodicity_seconds
         d = (max_value + min_value) / 2
         y = a * math.sin(b * (x + c)) + d
-        return (y, int(round(y)))
+        return _curve_result(y)
+
+
+class DreamSawWave:
+    NODE_NAME = "Saw Curve"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": SharedTypes.frame_counter | {
+                "max_value": ("FLOAT", {"default": 1.0, "multiline": False}),
+                "min_value": ("FLOAT", {"default": 0.0, "multiline": False}),
+                "periodicity_seconds": ("FLOAT", {"default": 10.0, "multiline": False, "min": 0.01}),
+                "phase": ("FLOAT", {"default": 0.0, "multiline": False, "min": -1, "max": 1}),
+            },
+        }
+
+    CATEGORY = NodeCategories.ANIMATION_CURVES
+    RETURN_TYPES = ("FLOAT", "INT")
+    RETURN_NAMES = ("FLOAT", "INT")
+    FUNCTION = "result"
+
+    @classmethod
+    def IS_CHANGED(cls, *values):
+        return hashed_as_strings(*values)
+
+    def result(self, frame_counter: FrameCounter, max_value, min_value, periodicity_seconds, phase):
+        x = frame_counter.current_time_in_seconds
+        x = ((x + periodicity_seconds * phase) % periodicity_seconds) / periodicity_seconds
+        y = x * (max_value - min_value) + min_value
+        return _curve_result(y)
+
+
+class DreamTriangleWave:
+    NODE_NAME = "Triangle Curve"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": SharedTypes.frame_counter | {
+                "max_value": ("FLOAT", {"default": 1.0, "multiline": False}),
+                "min_value": ("FLOAT", {"default": 0.0, "multiline": False}),
+                "periodicity_seconds": ("FLOAT", {"default": 10.0, "multiline": False, "min": 0.01}),
+                "phase": ("FLOAT", {"default": 0.0, "multiline": False, "min": -1, "max": 1}),
+            },
+        }
+
+    CATEGORY = NodeCategories.ANIMATION_CURVES
+    RETURN_TYPES = ("FLOAT", "INT")
+    RETURN_NAMES = ("FLOAT", "INT")
+    FUNCTION = "result"
+
+    @classmethod
+    def IS_CHANGED(cls, *values):
+        return hashed_as_strings(*values)
+
+    def result(self, frame_counter: FrameCounter, max_value, min_value, periodicity_seconds, phase):
+        x = frame_counter.current_time_in_seconds
+        x = ((x + periodicity_seconds * phase) % periodicity_seconds) / periodicity_seconds
+        if x <= 0.5:
+            x *= 2
+            y = x * (max_value - min_value) + min_value
+        else:
+            x = (x - 0.5) * 2
+            y = max_value - x * (max_value - min_value)
+        return _curve_result(y)
+
+
+class WavData:
+    def __init__(self, sampling_rate: float, single_channel_samples, fps: float):
+        self._length_in_seconds = len(single_channel_samples) / sampling_rate
+        self._num_buckets = round(self._length_in_seconds * fps * 3)
+        self._bucket_size = len(single_channel_samples) / float(self._num_buckets)
+        self._buckets = list()
+        self._rate = sampling_rate
+        self._max_bucket_value = 0
+        for i in range(self._num_buckets):
+            start_index = round(i * self._bucket_size)
+            end_index = round((i + 1) * self._bucket_size) - 1
+            samples = list(map(lambda n: abs(n), single_channel_samples[start_index:end_index]))
+            bucket_total = sum(samples)
+            self._buckets.append(bucket_total)
+            self._max_bucket_value=max(bucket_total, self._max_bucket_value)
+
+        for i in range(self._num_buckets):
+            self._buckets[i] = float(self._buckets[i]) / self._max_bucket_value
+
+    def value_at_time(self, second: float) -> float:
+        if second < 0.0 or second > self._length_in_seconds:
+            return 0.0
+        nsample = second * self._rate
+        nbucket = min(max(0, round(nsample / self._bucket_size)), self._num_buckets - 1)
+        return self._buckets[nbucket]
+
+
+@functools.lru_cache(4)
+def _wav_loader(filepath, fps):
+    sampling_rate, samples = wav_read(filepath)
+    single_channel = samples[:, 0]
+    return WavData(sampling_rate, single_channel, fps)
+
+
+class DreamWavCurve:
+    NODE_NAME = "WAV Curve"
+    CATEGORY = NodeCategories.ANIMATION_CURVES
+    RETURN_TYPES = ("FLOAT", "INT")
+    RETURN_NAMES = ("FLOAT", "INT")
+    FUNCTION = "result"
+    ICON = "∿"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": SharedTypes.frame_counter | {
+                "wav_path": ("STRING", {"default": "audio.wav"}),
+                "scale": ("FLOAT", {"default": 1.0, "multiline": False})
+            },
+        }
+
+    @classmethod
+    def IS_CHANGED(cls, *values):
+        return hashed_as_strings(*values)
+
+    def result(self, frame_counter: FrameCounter, wav_path, scale):
+        if not os.path.isfile(wav_path):
+            return (0.0, 0)
+        data = _wav_loader(wav_path, frame_counter.frames_per_second)
+        frame_counter.current_time_in_seconds
+        v = data.value_at_time(frame_counter.current_time_in_seconds)
+        return (v * scale, round(v * scale))
+
+
+class DreamTriangleEvent:
+    NODE_NAME = "Triangle Event Curve"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": SharedTypes.frame_counter | {
+                "max_value": ("FLOAT", {"default": 1.0, "multiline": False}),
+                "min_value": ("FLOAT", {"default": 0.0, "multiline": False}),
+                "width_seconds": ("FLOAT", {"default": 1.0, "multiline": False, "min": 0.1}),
+                "center_seconds": ("FLOAT", {"default": 10.0, "multiline": False, "min": 0.0}),
+            },
+        }
+
+    CATEGORY = NodeCategories.ANIMATION_CURVES
+    RETURN_TYPES = ("FLOAT", "INT")
+    RETURN_NAMES = ("FLOAT", "INT")
+    FUNCTION = "result"
+
+    @classmethod
+    def IS_CHANGED(cls, *values):
+        return hashed_as_strings(*values)
+
+    def result(self, frame_counter: FrameCounter, max_value, min_value, width_seconds, center_seconds):
+        x = frame_counter.current_time_in_seconds
+        start = center_seconds - width_seconds * 0.5
+        end = center_seconds + width_seconds * 0.5
+        if start <= x <= center_seconds:
+            y = _linear_value_calc(x, start, center_seconds, min_value, max_value)
+        elif center_seconds < x <= end:
+            y = _linear_value_calc(x, center_seconds, end, max_value, min_value)
+        else:
+            y = min_value
+        return _curve_result(y)
+
+
+class DreamSmoothEvent:
+    NODE_NAME = "Smooth Event Curve"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": SharedTypes.frame_counter | {
+                "max_value": ("FLOAT", {"default": 1.0, "multiline": False}),
+                "min_value": ("FLOAT", {"default": 0.0, "multiline": False}),
+                "width_seconds": ("FLOAT", {"default": 1.0, "multiline": False, "min": 0.1}),
+                "center_seconds": ("FLOAT", {"default": 10.0, "multiline": False, "min": 0.0}),
+            },
+        }
+
+    CATEGORY = NodeCategories.ANIMATION_CURVES
+    RETURN_TYPES = ("FLOAT", "INT")
+    RETURN_NAMES = ("FLOAT", "INT")
+    FUNCTION = "result"
+
+    @classmethod
+    def IS_CHANGED(cls, *values):
+        return hashed_as_strings(*values)
+
+    def result(self, frame_counter: FrameCounter, max_value, min_value, width_seconds, center_seconds):
+        x = frame_counter.current_time_in_seconds
+        start = center_seconds - width_seconds * 0.5
+        end = center_seconds + width_seconds * 0.5
+        if start <= x <= center_seconds:
+            y = _linear_value_calc(x, start, center_seconds, 0.0, 1.0)
+        elif center_seconds < x <= end:
+            y = _linear_value_calc(x, center_seconds, end, 1.0, 0.0)
+        else:
+            y = 0.0
+        if y < 0.5:
+            y = ((y + y) * (y + y)) * 0.5
+        else:
+            a = (y - 0.5) * 2
+            y = math.pow(a, 0.25) * 0.5 + 0.5
+        return _curve_result(y * (max_value - min_value) + min_value)
 
 
 class DreamBeatCurve:
@@ -96,7 +320,7 @@ class DreamBeatCurve:
             v = 1.0 - v
 
         r = low_value + v * (high_value - low_value)
-        return (r, int(round(r)))
+        return _curve_result(r)
 
 
 class DreamLinear:

dreamtypes.py

@@ -2,7 +2,7 @@
 import random
 import time
 
-from typing import List, Dict
+from typing import List, Dict, Tuple
 
 from .shared import DreamImage
 
@@ -26,6 +26,24 @@ class RGBPalette:
             for c in colors:
                 self._colors.append(_fix_tuple(c))
 
+    def _calculate_channel_contrast(self, c):
+        hist = list(map(lambda _: 0, range(16)))
+        for pixel in self._colors:
+            hist[pixel[c] // 16] += 1
+        s = 0
+        max_possible = (15 - 0) * (len(self) // 2) * (len(self) // 2)
+        for i in range(16):
+            for j in range(i):
+                if i != j:
+                    s += abs(i - j) * hist[i] * hist[j]
+        return s / max_possible
+
+    def _calculate_combined_contrast(self):
+        s = 0
+        for c in range(3):
+            s += self._calculate_channel_contrast(c)
+        return s / 3
+
     def analyze(self):
         total_red = 0
         total_blue = 0
@@ -38,7 +56,7 @@ class RGBPalette:
         r = float(total_red) / (255 * n)
         g = float(total_green) / (255 * n)
         b = float(total_blue) / (255 * n)
-        return ((r + g + b) / 3.0, r, g, b)
+        return ((r + g + b) / 3.0, self._calculate_combined_contrast(), r, g, b)
 
     def __len__(self):
         return len(self._colors)
@@ -64,6 +82,86 @@ class RGBPalette:
         return _ColorIterator()
 
 
+class PartialPrompt:
+    ID = "PARTIAL_PROMPT"
+
+    def __init__(self):
+        self._data = {}
+
+    def add(self, text: str, weight: float):
+        output = PartialPrompt()
+        output._data = dict(self._data)
+        for parts in text.split(","):
+            parts = parts.strip()
+            if " " in parts:
+                output._data["(" + parts + ")"] = weight
+            else:
+                output._data[parts] = weight
+        return output
+
+    def is_empty(self):
+        return not self._data
+
+    def abs_sum(self):
+        if not self._data:
+            return 0.0
+        return sum(map(abs, self._data.values()))
+
+    def abs_max(self):
+        if not self._data:
+            return 0.0
+        return max(map(abs, self._data.values()))
+
+    def scaled_by(self, f: float):
+        new_data = PartialPrompt()
+        new_data._data = dict(self._data)
+        for text, weight in new_data._data.items():
+            new_data._data[text] = weight * f
+        return new_data
+
+    def finalize(self, clamp: float):
+        items = self._data.items()
+        items = sorted(items, key=lambda pair: (pair[1], pair[0]))
+        pos = list()
+        neg = list()
+        for text, w in sorted(items, key=lambda pair: (-pair[1], pair[0])):
+            if w >= 0.0001:
+                pos.append("({}:{:.3f})".format(text, min(clamp, w)))
+        for text, w in sorted(items, key=lambda pair: (pair[1], pair[0])):
+            if w <= -0.0001:
+                neg.append("({}:{:.3f})".format(text, min(clamp, -w)))
+        return ", ".join(pos), ", ".join(neg)
+
+
+class LogEntry:
+    ID = "LOG_ENTRY"
+
+    @classmethod
+    def new(cls, text):
+        return LogEntry([(time.time(), text)])
+
+    def __init__(self, data: List[Tuple[float, str]] = None):
+        if data is None:
+            self._data = list()
+        else:
+            self._data = list(data)
+
+    def add(self, text: str):
+        new_data = list(self._data)
+        new_data.append((time.time(), text))
+        return LogEntry(new_data)
+
+    def merge(self, log_entry):
+        new_data = list(self._data)
+        new_data.extend(log_entry._data)
+        return LogEntry(new_data)
+
+    def get_filtered_entries(self, t: float):
+        for d in sorted(self._data):
+            if d[0] > t:
+                yield d
+
+
 class FrameCounter:
     ID = "FRAME_COUNTER"
 
@@ -91,6 +189,14 @@ class FrameCounter:
     def current_time_in_seconds(self):
         return float(self.current_frame) / self.frames_per_second
 
+    @property
+    def total_time_in_seconds(self):
+        return float(self.total_frames) / self.frames_per_second
+
+    @property
+    def remaining_time_in_seconds(self):
+        return self.total_time_in_seconds - self.current_time_in_seconds
+
     @property
     def progress(self):
         return float(self.current_frame) / (max(2, self.total_frames) - 1)

embedded_config.py

@@ -0,0 +1,41 @@
+EMBEDDED_CONFIGURATION = {
+    "ffmpeg": {
+        "file_extension": "mp4",
+        "path": "ffmpeg",
+        "arguments": ["-r", "%FPS%", "-f", "concat", "-safe", "0", "-vsync",
+                      "cfr", "-i", "%FRAMES%", "-c:v", "libx264", "-pix_fmt",
+                      "yuv420p", "%OUTPUT%"]
+    },
+    "mpeg_coder": {
+        "encoding_threads": 4,
+        "bitrate_factor": 1.0,
+        "max_b_frame": 2,
+        "file_extension": "mp4",
+        "codec_name": "libx264"
+    },
+    "encoding": {
+        "jpeg_quality": 95
+    },
+    "debug": False,
+    "ui": {
+        "top_category": "Dream",
+        "prepend_icon_to_category": True,
+        "append_icon_to_category": False,
+        "prepend_icon_to_node": True,
+        "append_icon_to_node": False,
+        "category_icons": {
+            "animation": "🎥",
+            "postprocessing": "⚙",
+            "transforms": "🔀",
+            "curves": "📈",
+            "color": "🎨",
+            "generate": "⚡",
+            "utils": "🛠",
+            "image": "🌄",
+            "switches": "⭆",
+            "conditioning": "☯",
+            "Dream": "✨"
+        }
+    },
+
+}

image_processing.py

@@ -9,7 +9,7 @@ from PIL.Image import Resampling
 from .categories import *
 from .shared import ALWAYS_CHANGED_FLAG, convertTensorImageToPIL, DreamImageProcessor, \
     DreamImage, DreamMask
-from .types import SharedTypes, FrameCounter
+from .dreamtypes import SharedTypes, FrameCounter
 
 
 class DreamImageMotion:

laboratory.py

@@ -0,0 +1,100 @@
+# -*- coding: utf-8 -*-
+
+# -*- coding: utf-8 -*-
+
+import json
+
+from .categories import *
+from .shared import ALWAYS_CHANGED_FLAG, DreamStateFile
+from .dreamtypes import *
+
+_laboratory_state = DreamStateFile("laboratory")
+
+
+class DreamLaboratory:
+    NODE_NAME = "Laboratory"
+    ICON = "🧪"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": SharedTypes.frame_counter | {
+                "key": ("STRING", {"default": "Random value " + str(random.randint(0, 1000000))}),
+                "seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff}),
+                "renew_policy": (["every frame", "first frame"],),
+                "min_value": ("FLOAT", {"default": 0.0}),
+                "max_value": ("FLOAT", {"default": 1.0}),
+                "mode": (["random uniform", "random bell", "ladder", "random walk"],),
+            },
+            "optional": {
+                "step_size": ("FLOAT", {"default": 0.1}),
+            },
+        }
+
+    CATEGORY = NodeCategories.UTILS
+    RETURN_TYPES = ("FLOAT", "INT", LogEntry.ID)
+    RETURN_NAMES = ("FLOAT", "INT", "log_entry")
+    FUNCTION = "result"
+
+    @classmethod
+    def IS_CHANGED(cls, *values):
+        return ALWAYS_CHANGED_FLAG
+
+    def _generate(self, seed, last_value, min_value, max_value, mode, step_size):
+        rnd = random.Random()
+        rnd.seed(seed)
+
+        def jsonify(v: float):
+            return json.loads(json.dumps(v))
+
+        if mode == "random uniform":
+            return jsonify(self._mode_uniform(rnd, last_value, min_value, max_value, step_size))
+        elif mode == "random bell":
+            return jsonify(self._mode_bell(rnd, last_value, min_value, max_value, step_size))
+        elif mode == "ladder":
+            return jsonify(self._mode_ladder(rnd, last_value, min_value, max_value, step_size))
+        else:
+            return jsonify(self._mode_walk(rnd, last_value, min_value, max_value, step_size))
+
+    def _mode_uniform(self, rnd: random.Random, last_value: float, min_value: float, max_value: float, step_size):
+        return rnd.random() * (max_value - min_value) + min_value
+
+    def _mode_bell(self, rnd: random.Random, last_value: float, min_value: float, max_value: float, step_size):
+        s = 0.0
+        for i in range(3):
+            s += rnd.random() * (max_value - min_value) + min_value
+        return s / 3.0
+
+    def _mode_ladder(self, rnd: random.Random, last_value: float, min_value: float, max_value: float, step_size):
+        if last_value is None:
+            last_value = min_value - step_size
+        next_value = last_value + step_size
+        if next_value > max_value:
+            d = abs(max_value - min_value)
+            next_value = (next_value - min_value) % d + min_value
+        return next_value
+
+    def _mode_walk(self, rnd: random.Random, last_value: float, min_value: float, max_value: float, step_size):
+        if last_value is None:
+            last_value = (max_value - min_value) * 0.5
+        if rnd.random() >= 0.5:
+            return min(max_value, last_value + step_size)
+        else:
+            return max(min_value, last_value - step_size)
+
+    def result(self, key, frame_counter: FrameCounter, seed, renew_policy, min_value, max_value, mode, **values):
+        if min_value > max_value:
+            t = max_value
+            max_value = min_value
+            min_value = t
+        step_size = values.get("step_size", abs(max_value - min_value) * 0.1)
+        last_value = _laboratory_state.get_section("values").get(key, None)
+
+        if (last_value is None) or (renew_policy == "every frame") or frame_counter.is_first_frame:
+            v = _laboratory_state.get_section("values") \
+                .update(key, 0, lambda old: self._generate(seed, last_value, min_value, max_value, mode, step_size))
+            return v, round(v), LogEntry.new(
+                "Laboratory generated new value for '{}': {} ({})".format(key, v, round(v)))
+        else:
+            return last_value, round(last_value), LogEntry.new("Laboratory reused value for '{}': {} ({})"
+                                                               .format(key, last_value, round(last_value)))

loaders.py

@@ -1,7 +1,8 @@
 # -*- coding: utf-8 -*-
 from .categories import NodeCategories
 from .shared import ALWAYS_CHANGED_FLAG, list_images_in_directory, DreamImage
-from .types import SharedTypes, FrameCounter
+from .dreamtypes import SharedTypes, FrameCounter
+import os
 
 
 class DreamImageSequenceInputWithDefaultFallback:
@@ -22,8 +23,8 @@ class DreamImageSequenceInputWithDefaultFallback:
         }
 
     CATEGORY = NodeCategories.IMAGE_ANIMATION
-    RETURN_TYPES = ("IMAGE",)
-    RETURN_NAMES = ("image",)
+    RETURN_TYPES = ("IMAGE","STRING")
+    RETURN_NAMES = ("image","frame_name")
     FUNCTION = "result"
 
     @classmethod
@@ -37,5 +38,6 @@ class DreamImageSequenceInputWithDefaultFallback:
         if not entry:
             return (default_image, "")
         else:
+            image_names = [os.path.basename(file_path) for file_path in entry]
             images = map(lambda f: DreamImage(file_path=f), entry)
-            return (DreamImage.join_to_tensor_data(images),)
+            return (DreamImage.join_to_tensor_data(images), image_names[0]) 

node_list.json

@@ -1,30 +1,60 @@
 {
-  "Analyze Palette [Dream]": "Output brightness, red, green and blue averages of a palette",
+  "Analyze Palette [Dream]": "Output brightness, contrast, red, green and blue averages of a palette",
   "Beat Curve [Dream]": "Beat pattern curve with impulses at specified beats of a measure",
+  "Big Float Switch [Dream]": "Switch for up to 10 inputs",
+  "Big Image Switch [Dream]": "Switch for up to 10 inputs",
+  "Big Int Switch [Dream]": "Switch for up to 10 inputs",
+  "Big Latent Switch [Dream]": "Switch for up to 10 inputs",
+  "Big Palette Switch [Dream]": "Switch for up to 10 inputs",
+  "Big Text Switch [Dream]": "Switch for up to 10 inputs",
+  "Boolean To Float [Dream]": "Converts a boolean value to two different float values",
+  "Boolean To Int [Dream]": "Converts a boolean value to two different int values",
+  "Build Prompt [Dream]": "Weighted text prompt builder utility",
   "CSV Curve [Dream]": "CSV input curve where first column is frame or second and second column is value",
   "CSV Generator [Dream]": "CSV output, mainly for debugging purposes",
+  "Calculation [Dream]": "Mathematical calculation node",
   "Common Frame Dimensions [Dream]": "Utility for calculating good width/height based on common video dimensions",
+  "Compare Palettes [Dream]": "Analyses two palettes producing the factor for each color channel",
   "FFMPEG Video Encoder [Dream]": "Post processing for animation sequences calling FFMPEG to generate video file",
   "File Count [Dream]": "Finds the number of files in a directory matching specified patterns",
+  "Finalize Prompt [Dream]": "Used in conjunction with 'Build Prompt'",
   "Float Input [Dream]": "Float input (until primitive routing issues are solved)",
+  "Float to Log Entry [Dream]": "Logging for float values",
+  "Frame Count Calculator [Dream]": "Simple utility to calculate number of frames based on duration and framerate",
   "Frame Counter (Directory) [Dream]": "Directory backed frame counter, for output directories",
   "Frame Counter (Simple) [Dream]": "Integer value used as frame counter",
+  "Frame Counter Info [Dream]": "Extracts information from the frame counter",
   "Frame Counter Offset [Dream]": "Adds an offset to a frame counter",
+  "Frame Counter Time Offset [Dream]": "Adds an offset to a frame counter in seconds",
+  "Image Brightness Adjustment [Dream]": "Adjusts the brightness of an image by a factor",
+  "Image Color Shift [Dream]": "Adjust the colors (or brightness) of an image",
+  "Image Contrast Adjustment [Dream]": "Adjusts the contrast of an image by a factor",
   "Image Motion [Dream]": "Node supporting zooming in/out and translating an image",
   "Image Sequence Blend [Dream]": "Post processing for animation sequences blending frame for a smoother blurred effect",
   "Image Sequence Loader [Dream]": "Loads a frame from a directory of images",
   "Image Sequence Saver [Dream]": "Saves a frame to a directory",
   "Image Sequence Tweening [Dream]": "Post processing for animation sequences generating blended in-between frames",
   "Int Input [Dream]": "Integer input (until primitive routing issues are solved)",
+  "Int to Log Entry [Dream]": "Logging for int values",
+  "Laboratory [Dream]": "Super-charged number generator for experimenting with ComfyUI",
   "Linear Curve [Dream]": "Linear interpolation between two value over the full animation",
+  "Log Entry Joiner [Dream]": "Merges multiple log entries (reduces noodling)",
+  "Log File [Dream]": "Logging node for output to file",
   "Noise from Area Palettes [Dream]": "Generates noise based on the colors of up to nine different palettes",
   "Noise from Palette [Dream]": "Generates noise based on the colors in a palette",
   "Palette Color Align [Dream]": "Shifts the colors of one palette towards another target palette",
   "Palette Color Shift [Dream]": "Multiplies the color values in a palette",
   "Sample Image Area as Palette [Dream]": "Samples a palette from an image based on pre-defined areas",
   "Sample Image as Palette [Dream]": "Randomly samples pixel values to build a palette from an image",
+  "Saw Curve [Dream]": "Saw wave curve",
   "Sine Curve [Dream]": "Simple sine wave curve",
+  "Smooth Event Curve [Dream]": "Single event/peak curve with a slight bell-shape",
   "String Input [Dream]": "String input (until primitive routing issues are solved)",
+  "String Tokenizer [Dream]": "Extract individual words or phrases from a text as tokens",
+  "String to Log Entry [Dream]": "Use any string as a log entry",
   "Text Input [Dream]": "Multiline string input (until primitive routing issues are solved)",
-  "Video Encoder (mpegCoder) [Dream]": "Post processing for animation sequences using mpegCoder module to generate video file"
+  "Triangle Curve [Dream]": "Triangle wave curve",
+  "Triangle Event Curve [Dream]": "Single event/peak curve with triangular shape",
+  "Video Encoder (mpegCoder) [Dream]": "Post processing for animation sequences using mpegCoder module to generate video file",
+  "WAV Curve [Dream]": "WAV audio file as a curve"
 }

noise.py

@@ -3,7 +3,7 @@ import math
 
 from .categories import NodeCategories
 from .shared import *
-from .types import *
+from .dreamtypes import *
 
 
 def _generate_noise(image: DreamImage, color_function, rng: random.Random, block_size, blur_amount,

output.py

@@ -8,7 +8,7 @@ from PIL.PngImagePlugin import PngInfo
 from .categories import NodeCategories
 from .shared import hashed_as_strings, DreamImageProcessor, DreamImage, \
     list_images_in_directory, DreamConfig
-from .types import SharedTypes, FrameCounter, AnimationSequence
+from .dreamtypes import SharedTypes, FrameCounter, AnimationSequence, LogEntry
 
 CONFIG = DreamConfig()
 
@@ -42,7 +42,7 @@ class DreamImageSequenceOutput:
                 "directory_path": ("STRING", {"default": comfy_paths.output_directory, "multiline": False}),
                 "prefix": ("STRING", {"default": 'frame', "multiline": False}),
                 "digits": ("INT", {"default": 5}),
-                "at_end": (["stop output", "keep going"],),
+                "at_end": (["stop output", "raise error", "keep going"],),
                 "filetype": (['png with embedded workflow', "png", 'jpg'],),
             },
             "hidden": {
@@ -52,9 +52,9 @@ class DreamImageSequenceOutput:
         }
 
     CATEGORY = NodeCategories.IMAGE_ANIMATION
-    RETURN_TYPES = (AnimationSequence.ID,)
+    RETURN_TYPES = (AnimationSequence.ID, LogEntry.ID)
     OUTPUT_NODE = True
-    RETURN_NAMES = ("sequence",)
+    RETURN_NAMES = ("sequence", "log_entry")
     FUNCTION = "save"
 
     @classmethod
@@ -64,11 +64,16 @@ class DreamImageSequenceOutput:
     def _get_new_filename(self, current_frame, prefix, digits, filetype):
         return prefix + "_" + str(current_frame).zfill(digits) + "." + filetype.split(" ")[0]
 
-    def _save_single_image(self, dream_image: DreamImage, batch_counter, frame_counter: FrameCounter, directory_path,
-                           prefix, digits, filetype, prompt, extra_pnginfo, at_end):
+    def _save_single_image(self, dream_image: DreamImage, batch_counter, frame_counter: FrameCounter,
+                           directory_path,
+                           prefix, digits, filetype, prompt, extra_pnginfo, at_end, logger):
+
         if at_end == "stop output" and frame_counter.is_after_last_frame:
-            print("Reached end of animation - not saving output!")
+            logger("Reached end of animation - not saving output!")
             return ()
+        if at_end == "raise error" and frame_counter.is_after_last_frame:
+            logger("Reached end of animation - raising error to stop processing!")
+            raise Exception("Reached end of animation!")
         filename = self._get_new_filename(frame_counter.current_frame, prefix, digits, filetype)
         if batch_counter >= 0:
             filepath = os.path.join(directory_path, "batch_" + (str(batch_counter).zfill(4)), filename)
@@ -81,7 +86,7 @@ class DreamImageSequenceOutput:
             dream_image.save_png(filepath, filetype == 'png with embedded workflow', prompt, extra_pnginfo)
         elif filetype == "jpg":
             dream_image.save_jpg(filepath, int(CONFIG.get("encoding.jpeg_quality", 95)))
-        print("Saved {} in {}".format(filename, os.path.abspath(save_dir)))
+        logger("Saved {} in {}".format(filename, os.path.abspath(save_dir)))
         return ()
 
     def _generate_animation_sequence(self, filetype, directory_path, frame_counter):
@@ -93,13 +98,19 @@ class DreamImageSequenceOutput:
         return AnimationSequence(frame_counter, frames)
 
     def save(self, image, **args):
+        log_texts = list()
+        logger = lambda s: log_texts.append(s)
         if not args.get("directory_path", ""):
             args["directory_path"] = comfy_paths.output_directory
+        args["logger"] = logger
         proc = DreamImageProcessor(image, **args)
         proc.process(self._save_single_image)
         frame_counter: FrameCounter = args["frame_counter"]
+        log_entry = LogEntry([])
+        for text in log_texts:
+            log_entry = log_entry.add(text)
         if frame_counter.is_final_frame:
             return (self._generate_animation_sequence(args["filetype"], args["directory_path"],
-                                                      frame_counter),)
+                                                      frame_counter), log_entry)
         else:
-            return (AnimationSequence(frame_counter),)
+            return (AnimationSequence(frame_counter), log_entry)

prompting.py

@@ -0,0 +1,69 @@
+from .categories import NodeCategories
+from .shared import hashed_as_strings
+from .dreamtypes import PartialPrompt
+
+
+class DreamWeightedPromptBuilder:
+    NODE_NAME = "Build Prompt"
+    ICON = "⚖"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "optional": {
+                "partial_prompt": (PartialPrompt.ID,)
+            },
+            "required": {
+                "added_prompt": ("STRING", {"default": "", "multiline": True}),
+                "weight": ("FLOAT", {"default": 1.0}),
+            },
+        }
+
+    CATEGORY = NodeCategories.CONDITIONING
+    RETURN_TYPES = (PartialPrompt.ID,)
+    RETURN_NAMES = ("partial_prompt",)
+    FUNCTION = "result"
+
+    @classmethod
+    def IS_CHANGED(cls, *values):
+        return hashed_as_strings(*values)
+
+    def result(self, added_prompt, weight, **args):
+        input = args.get("partial_prompt", PartialPrompt())
+        p = input.add(added_prompt, weight)
+        return (p,)
+
+
+class DreamPromptFinalizer:
+    NODE_NAME = "Finalize Prompt"
+    ICON = "🗫"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "partial_prompt": (PartialPrompt.ID,),
+                "adjustment": (["raw", "by_abs_max", "by_abs_sum"],),
+                "clamp": ("FLOAT", {"default": 2.0, "min": 0.1, "step": 0.1}),
+                "adjustment_reference": ("FLOAT", {"default": 1.0, "min": 0.1}),
+            },
+        }
+
+    CATEGORY = NodeCategories.CONDITIONING
+    RETURN_TYPES = ("STRING", "STRING")
+    RETURN_NAMES = ("positive", "negative")
+    FUNCTION = "result"
+
+    @classmethod
+    def IS_CHANGED(cls, *values):
+        return hashed_as_strings(*values)
+
+    def result(self, partial_prompt: PartialPrompt, adjustment, adjustment_reference, clamp):
+        if adjustment == "raw" or partial_prompt.is_empty():
+            return partial_prompt.finalize(clamp)
+        elif adjustment == "by_abs_sum":
+            f = adjustment_reference / partial_prompt.abs_sum()
+            return partial_prompt.scaled_by(f).finalize(clamp)
+        else:
+            f = adjustment_reference / partial_prompt.abs_max()
+            return partial_prompt.scaled_by(f).finalize(clamp)

readme.md

@@ -133,6 +133,23 @@ Output brightness, red, green and blue averages of a palette. Useful to control
 ### Beat Curve [Dream]
 Beat pattern curve with impulses at specified beats of a measure.
 
+### Big *** Switch [Dream]
+Switch nodes for different type for up to ten inputs.
+
+### Boolean To Float/Int [Dream]
+Converts a boolean value to two different numeric values.
+
+### Build Prompt [Dream] (and Finalize Prompt [Dream])
+Weighted text prompt builder utility. Chain any number of these nodes and terminate with 'Finalize Prompt'.
+
+### Calculation [Dream]
+Mathematical calculation node. Exposes most of the mathematical functions in the python 
+[math module](https://docs.python.org/3/library/math.html), mathematical operators as well as round, abs, int, 
+float, max and min.
+
+### Compare Palettes [Dream]
+Analyses two palettes and produces the quotient for each individual channel (b/a) and brightness.
+
 ### CSV Curve [Dream]
 CSV input curve where first column is frame or second and second column is value.
 
@@ -152,6 +169,12 @@ Post processing for animation sequences using the python module mpegCoder with f
 ### File Count [Dream]
 Finds the number of files in a directory matching specified patterns.
 
+### Float/Int/string to Log Entry [Dream]
+Logging for float/int/string values.
+
+### Frame Count Calculator [Dream]
+Simple utility to calculate number of frames based on time and framerate.
+
 ### Frame Counter (Directory) [Dream]
 Directory backed frame counter, for output directories.
 
@@ -159,8 +182,23 @@ Directory backed frame counter, for output directories.
 Integer value used as frame counter. Useful for testing or if an auto-incrementing primitive is used as a frame 
 counter.
 
+### Frame Counter Info [Dream]
+Extracts information from the frame counter.
+
 ### Frame Counter Offset [Dream]
-Adds an offset to a frame counter.
+Adds an offset (in frames) to a frame counter.
+
+### Frame Counter Time Offset [Dream]
+Adds an offset in seconds to a frame counter.
+
+### Image Brightness Adjustment [Dream]
+Adjusts the brightness of an image by a factor.
+
+### Image Color Shift [Dream]
+Allows changing the colors of an image with a multiplier for each channel (RGB).
+
+### Image Contrast Adjustment [Dream]
+Adjusts the contrast of an image by a factor.
 
 ### Image Motion [Dream]
 Node supporting zooming in/out and translating an image.
@@ -177,6 +215,15 @@ Saves a frame to a directory.
 ### Image Sequence Tweening [Dream]
 Post processing for animation sequences generating blended in-between frames.
 
+### Laboratory [Dream]
+Super-charged number generator for experimenting with ComfyUI.
+
+### Log Entry Joiner [Dream]
+Merges multiple log entries (reduces noodling).
+
+### Log File [Dream]
+The text logging facility for the Dream Project Animation nodes.
+
 ### Linear Curve [Dream]
 Linear interpolation between two values over the full animation.
 
@@ -202,9 +249,27 @@ of equal size and each node may sample one of these.
 ### Sample Image as Palette [Dream]
 Randomly samples pixels from a source image to build a palette from it.
 
+### Saw Curve [Dream]
+Saw wave curve.
+
 ### Sine Curve [Dream]
 Simple sine wave curve.
 
+### Smooth Event Curve [Dream]
+Single event/peak curve with a slight bell-shape. 
+
+### String Tokenizer [Dream]
+Splits a text into tokens by a separator and returns one of the tokens based on a given index.
+
+### Triangle Curve [Dream]
+Triangle wave curve. 
+
+### Triangle Event Curve [Dream]
+Single event/peak curve with triangular shape.
+
+### WAV Curve [Dream]
+Use an uncompressed WAV audio file as a curve.
+
 ### Other custom nodes
 
 Many of the nodes found in 'WAS Node Suite' are useful the Dream Project Animation nodes - I suggest you install those 
@@ -230,6 +295,18 @@ This flow demonstrates sampling image areas into palettes and generating noise f
 
 [area-sampled-noise](examples/area-sampled-noise.json)
 
+### Prompt Morphing
+
+This flow demonstrates prompt building with weights based on curves and brightness and contrast control.
+
+[prompt-morphing](examples/prompt-morphing.json)
+
+### Laboratory
+
+This flow demonstrates use of the Laboratory and Logging nodes.
+
+[laboratory](examples/laboratory.json)
+
 ## Known issues
 
 ### FFMPEG

requirements.txt

@@ -4,3 +4,4 @@ scipy
 numpy<1.24>=1.18
 torchvision
 mpegCoder
+evalidate

seq_processing.py

@@ -5,19 +5,19 @@ import subprocess
 import tempfile
 from functools import lru_cache
 
-from PIL import Image
+from PIL import Image as PilImage
 
 from .categories import NodeCategories
 from .err import on_error
 from .shared import DreamConfig, MpegEncoderUtility
-from .types import *
+from .dreamtypes import *
 
 CONFIG = DreamConfig()
 
 
 @lru_cache(5)
-def _load_image_cached(filename) -> Image:
-    return Image.open(filename)
+def _load_image_cached(filename):
+    return PilImage.open(filename)
 
 
 class TempFileSet:
@@ -136,8 +136,8 @@ class DreamVideoEncoderMpegCoder:
     NODE_NAME = "Video Encoder (mpegCoder)"
     ICON = "🎬"
     CATEGORY = NodeCategories.ANIMATION_POSTPROCESSING
-    RETURN_TYPES = ()
-    RETURN_NAMES = ()
+    RETURN_TYPES = (LogEntry.ID,)
+    RETURN_NAMES = ("log_entry",)
     OUTPUT_NODE = True
     FUNCTION = "encode"
 
@@ -164,9 +164,10 @@ class DreamVideoEncoderMpegCoder:
 
     def encode(self, sequence, name, framerate_factor, remove_images):
         if not sequence.is_defined:
-            return ()
+            return (LogEntry([]),)
         config = DreamConfig()
-        filename = _make_video_filename(name, config.get("mpeg_coder.file_exension"))
+        filename = _make_video_filename(name, config.get("mpeg_coder.file_extension", "mp4"))
+        log_entry = LogEntry([])
         for batch_num in sequence.batches:
             try:
                 images = list(sequence.get_image_files_of_batch(batch_num))
@@ -182,13 +183,14 @@ class DreamVideoEncoderMpegCoder:
                                          fps=sequence.fps * framerate_factor,
                                          codec_name=config.get("mpeg_coder.codec_name", "libx265"))
                 enc.encode()
+                log_entry = log_entry.add("Generated video '{}'".format(filename))
                 if remove_images:
                     for imagepath in images:
                         if os.path.isfile(imagepath):
                             os.unlink(imagepath)
             except Exception as e:
                 on_error(self.__class__, str(e))
-        return ()
+        return (log_entry,)
 
 
 class DreamVideoEncoder:
@@ -207,8 +209,8 @@ class DreamVideoEncoder:
         }
 
     CATEGORY = NodeCategories.ANIMATION_POSTPROCESSING
-    RETURN_TYPES = ()
-    RETURN_NAMES = ()
+    RETURN_TYPES = (LogEntry.ID,)
+    RETURN_NAMES = ("log_entry",)
     OUTPUT_NODE = True
     FUNCTION = "encode"
 
@@ -230,24 +232,28 @@ class DreamVideoEncoder:
     def generate_video(self, files, fps, filename, config):
         filename = self._find_free_filename(filename, os.path.dirname(files[0]))
         _ffmpeg(config, files, fps, filename)
+        return filename
 
     def encode(self, sequence: AnimationSequence, name: str, remove_images, framerate_factor):
         if not sequence.is_defined:
-            return ()
+            return (LogEntry([]),)
 
         config = DreamConfig()
-        filename = _make_video_filename(name, config.get("ffmpeg.file_exension"))
+        filename = _make_video_filename(name, config.get("ffmpeg.file_extension", "mp4"))
+        log_entry = LogEntry([])
         for batch_num in sequence.batches:
             try:
                 images = list(sequence.get_image_files_of_batch(batch_num))
-                self.generate_video(images, sequence.fps * framerate_factor, filename, config)
+                actual_filename = self.generate_video(images, sequence.fps * framerate_factor, filename, config)
+
+                log_entry = log_entry.add("Generated video '{}'".format(actual_filename))
                 if remove_images:
                     for imagepath in images:
                         if os.path.isfile(imagepath):
                             os.unlink(imagepath)
             except Exception as e:
                 on_error(self.__class__, str(e))
-        return ()
+        return (log_entry,)
 
 
 class DreamSequenceTweening:

shared.py

@@ -10,12 +10,13 @@ import folder_paths as comfy_paths
 import glob
 import numpy
 import torch
-from PIL import Image, ImageFilter
+from PIL import Image, ImageFilter, ImageEnhance
 from PIL.ImageDraw import ImageDraw
 from PIL.PngImagePlugin import PngInfo
 from typing import Dict, Tuple, List
 
 from .dreamlogger import DreamLog
+from .embedded_config import EMBEDDED_CONFIGURATION
 
 NODE_FILE = os.path.abspath(__file__)
 DREAM_NODES_SOURCE_ROOT = os.path.dirname(NODE_FILE)
@@ -43,45 +44,7 @@ _config_data = None
 
 class DreamConfig:
     FILEPATH = os.path.join(os.path.dirname(os.path.abspath(__file__)), "config.json")
-    DEFAULT_CONFIG = {
-        "ffmpeg": {
-            "file_exension": "mp4",
-            "path": "ffmpeg",
-            "arguments": ["-r", "%FPS%", "-f", "concat", "-safe", "0", "-vsync",
-                          "cfr", "-i", "%FRAMES%", "-c:v", "libx265", "-pix_fmt",
-                          "yuv420p", "%OUTPUT%"]
-        },
-        "mpeg_coder": {
-            "encoding_threads": 4,
-            "bitrate_factor": 1.0,
-            "max_b_frame": 2,
-            "file_exension": "mp4",
-            "codec_name": "libx265"
-        },
-        "encoding": {
-            "jpeg_quality": 95
-        },
-        "debug": False,
-        "ui": {
-            "top_category": "Dream",
-            "prepend_icon_to_category": True,
-            "append_icon_to_category": False,
-            "prepend_icon_to_node": True,
-            "append_icon_to_node": False,
-            "category_icons": {
-                "animation": "🎥",
-                "postprocessing": "⚙",
-                "transforms": "🔀",
-                "curves": "📈",
-                "color": "🎨",
-                "generate": "⚡",
-                "utils": "🛠",
-                "image": "🌄",
-                "Dream": "✨"
-            }
-        },
-
-    }
+    DEFAULT_CONFIG = EMBEDDED_CONFIGURATION
 
     def __init__(self):
         global _config_data
@@ -188,6 +151,14 @@ class DreamImage:
         self.size = self.pil_image.size
         self._draw = ImageDraw(self.pil_image)
 
+    def change_brightness(self, factor):
+        enhancer = ImageEnhance.Brightness(self.pil_image)
+        return DreamImage(pil_image=enhancer.enhance(factor))
+
+    def change_contrast(self, factor):
+        enhancer = ImageEnhance.Contrast(self.pil_image)
+        return DreamImage(pil_image=enhancer.enhance(factor))
+
     def numpy_array(self):
         return numpy.array(self.pil_image)
 
@@ -232,6 +203,15 @@ class DreamImage:
     def blur(self, amount):
         return DreamImage(pil_image=self.pil_image.filter(ImageFilter.GaussianBlur(amount)))
 
+    def adjust_colors(self, red_factor=1.0, green_factor=1.0, blue_factor=1.0):
+        # newRed   = 1.1*oldRed  +  0*oldGreen    +  0*oldBlue  + constant
+        # newGreen = 0*oldRed    +  0.9*OldGreen  +  0*OldBlue  + constant
+        # newBlue  = 0*oldRed    +  0*OldGreen    +  1*OldBlue  + constant
+        matrix = (red_factor, 0, 0, 0,
+                  0, green_factor, 0, 0,
+                  0, 0, blue_factor, 0)
+        return DreamImage(pil_image=self.pil_image.convert("RGB", matrix))
+
     def get_pixel(self, x, y):
         p = self.pil_image.getpixel((x, y))
         if len(p) == 4:
@@ -352,9 +332,9 @@ class DreamStateStore:
 
 
 class DreamStateFile:
-    def __init__(self, state_file_path=os.path.join(TEMP_PATH, "state.json")):
-        self._dirname = os.path.dirname(state_file_path)
-        self._filepath = state_file_path
+    def __init__(self, state_collection_name="state"):
+        self._filepath = os.path.join(TEMP_PATH, state_collection_name+".json")
+        self._dirname = os.path.dirname(self._filepath)
         if not os.path.isdir(self._dirname):
             os.makedirs(self._dirname)
         if not os.path.isfile(self._filepath):
@@ -378,7 +358,6 @@ class DreamStateFile:
             self._data[key] = value
         with open(self._filepath, "w", encoding="utf-8") as f:
             json.dump(self._data, f)
-        print("* {} -> {}".format(key, value))
         return previous
 
 
@@ -397,7 +376,7 @@ class MpegEncoderUtility:
         self._logger = get_logger()
         self._enc = mpegCoder.MpegEncoder()
         bit_rate = self._calculate_bit_rate(width, height, fps, bit_rate_factor)
-        self._logger.info("Bitrate "+str(bit_rate))
+        self._logger.info("Bitrate " + str(bit_rate))
         self._enc.setParameter(
             videoPath=video_path, codecName=codec_name,
             nthread=encoding_threads, bitRate=bit_rate, width=width, height=height, widthSrc=width,
@@ -405,7 +384,7 @@ class MpegEncoderUtility:
             GOPSize=len(files), maxBframe=max_b_frame, frameRate=self._fps_to_tuple(fps))
 
     def _calculate_bit_rate(self, width: int, height: int, fps: float, bit_rate_factor: float):
-        bits_per_pixel_base = 0.075
+        bits_per_pixel_base = 0.5
         return round(max(10, float(width * height * fps * bits_per_pixel_base * bit_rate_factor * 0.001)))
 
     def encode(self):
@@ -427,6 +406,7 @@ class MpegEncoderUtility:
     def _fps_to_tuple(self, fps: float):
         def _is_almost_int(f: float):
             return abs(f - int(f)) < 0.001
+
         a = fps
         b = 1
         while not _is_almost_int(a) and b < 100:

switches.py

@@ -0,0 +1,212 @@
+from .categories import NodeCategories
+from .err import *
+from .shared import ALWAYS_CHANGED_FLAG, hashed_as_strings
+from .dreamtypes import RGBPalette
+
+
+def _generate_switch_input(type: str):
+    d = dict()
+    for i in range(10):
+        d["input_" + str(i)] = (type,)
+    return {
+        "required": {
+            "select": ("INT", {"defualt": 0, "min": 0, "max": 9}),
+            "on_missing": (["previous", "next"],)
+        },
+        "optional": d
+    }
+
+
+def _do_pick(cls, select, on_missing, **args):
+    direction = 1
+    if on_missing == "previous":
+        direction = -1
+    if len(args) == 0:
+        on_error(cls, "No inputs provided!")
+    while args.get("input_" + str(select), None) is None:
+        select = (select + direction) % 10
+    return args["input_" + str(select)],
+
+
+class DreamBigImageSwitch:
+    _switch_type = "IMAGE"
+    NODE_NAME = "Big Image Switch"
+    ICON = "⭆"
+    CATEGORY = NodeCategories.UTILS_SWITCHES
+    RETURN_TYPES = (_switch_type,)
+    RETURN_NAMES = ("selected",)
+    FUNCTION = "pick"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return _generate_switch_input(cls._switch_type)
+
+    @classmethod
+    def IS_CHANGED(cls, *values):
+        return ALWAYS_CHANGED_FLAG
+
+    def pick(self, select, on_missing, **args):
+        return _do_pick(self.__class__, select, on_missing, **args)
+
+
+class DreamBigLatentSwitch:
+    _switch_type = "LATENT"
+    NODE_NAME = "Big Latent Switch"
+    ICON = "⭆"
+    CATEGORY = NodeCategories.UTILS_SWITCHES
+    RETURN_TYPES = (_switch_type,)
+    RETURN_NAMES = ("selected",)
+    FUNCTION = "pick"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return _generate_switch_input(cls._switch_type)
+
+    @classmethod
+    def IS_CHANGED(cls, *values):
+        return ALWAYS_CHANGED_FLAG
+
+    def pick(self, select, on_missing, **args):
+        return _do_pick(self.__class__, select, on_missing, **args)
+
+
+class DreamBigTextSwitch:
+    _switch_type = "STRING"
+    NODE_NAME = "Big Text Switch"
+    ICON = "⭆"
+    CATEGORY = NodeCategories.UTILS_SWITCHES
+    RETURN_TYPES = (_switch_type,)
+    RETURN_NAMES = ("selected",)
+    FUNCTION = "pick"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return _generate_switch_input(cls._switch_type)
+
+    @classmethod
+    def IS_CHANGED(cls, *values):
+        return hashed_as_strings(values)
+
+    def pick(self, select, on_missing, **args):
+        return _do_pick(self.__class__, select, on_missing, **args)
+
+
+class DreamBigPaletteSwitch:
+    _switch_type = RGBPalette.ID
+    NODE_NAME = "Big Palette Switch"
+    ICON = "⭆"
+    CATEGORY = NodeCategories.UTILS_SWITCHES
+    RETURN_TYPES = (_switch_type,)
+    RETURN_NAMES = ("selected",)
+    FUNCTION = "pick"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return _generate_switch_input(cls._switch_type)
+
+    @classmethod
+    def IS_CHANGED(cls, *values):
+        return ALWAYS_CHANGED_FLAG
+
+    def pick(self, select, on_missing, **args):
+        return _do_pick(self.__class__, select, on_missing, **args)
+
+
+class DreamBigFloatSwitch:
+    _switch_type = "FLOAT"
+    NODE_NAME = "Big Float Switch"
+    ICON = "⭆"
+    CATEGORY = NodeCategories.UTILS_SWITCHES
+    RETURN_TYPES = (_switch_type,)
+    RETURN_NAMES = ("selected",)
+    FUNCTION = "pick"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return _generate_switch_input(cls._switch_type)
+
+    @classmethod
+    def IS_CHANGED(cls, *values):
+        return hashed_as_strings(values)
+
+    def pick(self, select, on_missing, **args):
+        return _do_pick(self.__class__, select, on_missing, **args)
+
+
+class DreamBigIntSwitch:
+    _switch_type = "INT"
+    NODE_NAME = "Big Int Switch"
+    ICON = "⭆"
+    CATEGORY = NodeCategories.UTILS_SWITCHES
+    RETURN_TYPES = (_switch_type,)
+    RETURN_NAMES = ("selected",)
+    FUNCTION = "pick"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return _generate_switch_input(cls._switch_type)
+
+    @classmethod
+    def IS_CHANGED(cls, *values):
+        return hashed_as_strings(values)
+
+    def pick(self, select, on_missing, **args):
+        return _do_pick(self.__class__, select, on_missing, **args)
+
+
+class DreamBoolToFloat:
+    NODE_NAME = "Boolean To Float"
+    ICON = "⬖"
+    CATEGORY = NodeCategories.UTILS_SWITCHES
+    RETURN_TYPES = ("FLOAT",)
+    RETURN_NAMES = ("result",)
+    FUNCTION = "pick"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "boolean": ("BOOLEAN", {"default": False}),
+                "on_true": ("FLOAT", {"default": 1.0}),
+                "on_false": ("FLOAT", {"default": 0.0})
+            }
+        }
+
+    @classmethod
+    def IS_CHANGED(cls, *values):
+        return hashed_as_strings(values)
+
+    def pick(self, boolean, on_true, on_false):
+        if boolean:
+            return (on_true,)
+        else:
+            return (on_false,)
+
+
+class DreamBoolToInt:
+    NODE_NAME = "Boolean To Int"
+    ICON = "⬖"
+    CATEGORY = NodeCategories.UTILS_SWITCHES
+    RETURN_TYPES = ("INT",)
+    RETURN_NAMES = ("result",)
+    FUNCTION = "pick"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "boolean": ("BOOLEAN", {"default": False}),
+                "on_true": ("INT", {"default": 1}),
+                "on_false": ("INT", {"default": 0})
+            }
+        }
+
+    @classmethod
+    def IS_CHANGED(cls, *values):
+        return hashed_as_strings(values)
+
+    def pick(self, boolean, on_true, on_false):
+        if boolean:
+            return (on_true,)
+        else:
+            return (on_false,)

utility.py

@@ -1,8 +1,220 @@
 # -*- coding: utf-8 -*-
+import datetime
 import math
+import os
+
+import folder_paths as comfy_paths
 
 from .categories import NodeCategories
-from .shared import hashed_as_strings
+from .shared import hashed_as_strings, DreamStateFile
+from .dreamtypes import LogEntry, SharedTypes, FrameCounter
+
+_logfile_state = DreamStateFile("logging")
+
+
+class DreamJoinLog:
+    NODE_NAME = "Log Entry Joiner"
+    ICON = "🗎"
+    CATEGORY = NodeCategories.UTILS
+    RETURN_TYPES = (LogEntry.ID,)
+    RETURN_NAMES = ("log_entry",)
+    FUNCTION = "convert"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "optional": {
+                "entry_0": (LogEntry.ID,),
+                "entry_1": (LogEntry.ID,),
+                "entry_2": (LogEntry.ID,),
+                "entry_3": (LogEntry.ID,),
+            }
+        }
+
+    def convert(self, **values):
+        entry = LogEntry([])
+        for i in range(4):
+            txt = values.get("entry_" + str(i), None)
+            if txt:
+                entry = entry.merge(txt)
+        return (entry,)
+
+
+class DreamFloatToLog:
+    NODE_NAME = "Float to Log Entry"
+    ICON = "🗎"
+    CATEGORY = NodeCategories.UTILS
+    RETURN_TYPES = (LogEntry.ID,)
+    RETURN_NAMES = ("log_entry",)
+    FUNCTION = "convert"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "value": ("FLOAT", {"default": 0}),
+                "label": ("STRING", {"default": ""}),
+            },
+        }
+
+    def convert(self, label, value):
+        return (LogEntry.new(label + ": " + str(value)),)
+
+
+class DreamIntToLog:
+    NODE_NAME = "Int to Log Entry"
+    ICON = "🗎"
+    CATEGORY = NodeCategories.UTILS
+    RETURN_TYPES = (LogEntry.ID,)
+    RETURN_NAMES = ("log_entry",)
+    FUNCTION = "convert"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "value": ("INT", {"default": 0}),
+                "label": ("STRING", {"default": ""}),
+            },
+        }
+
+    def convert(self, label, value):
+        return (LogEntry.new(label + ": " + str(value)),)
+
+
+class DreamStringToLog:
+    NODE_NAME = "String to Log Entry"
+    ICON = "🗎"
+    OUTPUT_NODE = True
+    CATEGORY = NodeCategories.UTILS
+    RETURN_TYPES = (LogEntry.ID,)
+    RETURN_NAMES = ("log_entry",)
+    FUNCTION = "convert"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "text": ("STRING", {"default": ""}),
+            },
+            "optional": {
+                "label": ("STRING", {"default": ""}),
+            }
+        }
+
+    def convert(self, text, **values):
+        label = values.get("label", "")
+        if label:
+            return (LogEntry.new(label + ": " + text),)
+        else:
+            return (LogEntry.new(text),)
+
+
+class DreamStringTokenizer:
+    NODE_NAME = "String Tokenizer"
+    ICON = "🪙"
+    OUTPUT_NODE = True
+    CATEGORY = NodeCategories.UTILS
+    RETURN_TYPES = ("STRING",)
+    RETURN_NAMES = ("token",)
+    FUNCTION = "exec"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "text": ("STRING", {"default": "", "multiline": True}),
+                "separator": ("STRING", {"default": ","}),
+                "selected": ("INT", {"default": 0, "min": 0})
+            },
+        }
+
+    def exec(self, text: str, separator: str, selected: int):
+        if separator is None or separator == "":
+            separator = " "
+        parts = text.split(sep=separator)
+        return (parts[abs(selected) % len(parts)].strip(),)
+
+
+class DreamLogFile:
+    NODE_NAME = "Log File"
+    ICON = "🗎"
+    OUTPUT_NODE = True
+    CATEGORY = NodeCategories.UTILS
+    RETURN_TYPES = ()
+    RETURN_NAMES = ()
+    FUNCTION = "write"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": SharedTypes.frame_counter | {
+                "log_directory": ("STRING", {"default": comfy_paths.output_directory}),
+                "log_filename": ("STRING", {"default": "dreamlog.txt"}),
+                "stdout": ("BOOLEAN", {"default": True}),
+                "active": ("BOOLEAN", {"default": True}),
+                "clock_has_24_hours": ("BOOLEAN", {"default": True}),
+            },
+            "optional": {
+                "entry_0": (LogEntry.ID,),
+                "entry_1": (LogEntry.ID,),
+                "entry_2": (LogEntry.ID,),
+                "entry_3": (LogEntry.ID,),
+                "entry_4": (LogEntry.ID,),
+                "entry_5": (LogEntry.ID,),
+                "entry_6": (LogEntry.ID,),
+                "entry_7": (LogEntry.ID,),
+            },
+        }
+
+    def _path_to_log_file(self, log_directory, logfile):
+        if os.path.isabs(logfile):
+            return os.path.normpath(os.path.abspath(logfile))
+        elif os.path.isabs(log_directory):
+            return os.path.normpath(os.path.abspath(os.path.join(log_directory, logfile)))
+        elif log_directory:
+            return os.path.normpath(os.path.abspath(os.path.join(comfy_paths.output_directory, log_directory, logfile)))
+        else:
+            return os.path.normpath(os.path.abspath(os.path.join(comfy_paths.output_directory, logfile)))
+
+    def _get_tm_format(self, clock_has_24_hours):
+        if clock_has_24_hours:
+            return "%a %H:%M:%S"
+        else:
+            return "%a %I:%M:%S %p"
+
+    def write(self, frame_counter: FrameCounter, log_directory, log_filename, stdout, active, clock_has_24_hours,
+              **entries):
+        if not active:
+            return ()
+        log_entry = None
+        for i in range(8):
+            e = entries.get("entry_" + str(i), None)
+            if e is not None:
+                if log_entry is None:
+                    log_entry = e
+                else:
+                    log_entry = log_entry.merge(e)
+        log_file_path = self._path_to_log_file(log_directory, log_filename)
+        ts = _logfile_state.get_section("timestamps").get(log_file_path, 0)
+        output_text = list()
+        last_t = 0
+        for (t, text) in log_entry.get_filtered_entries(ts):
+            dt = datetime.datetime.fromtimestamp(t)
+            output_text.append("[frame {}/{} (~{}%), timestamp {}]\n{}".format(frame_counter.current_frame + 1,
+                                                                               frame_counter.total_frames,
+                                                                               round(frame_counter.progress * 100),
+                                                                               dt.strftime(self._get_tm_format(
+                                                                                   clock_has_24_hours)), text.rstrip()))
+            output_text.append("---")
+            last_t = max(t, last_t)
+        output_text = "\n".join(output_text) + "\n"
+        if stdout:
+            print(output_text)
+        with open(log_file_path, "a", encoding="utf-8") as f:
+            f.write(output_text)
+        _logfile_state.get_section("timestamps").update(log_file_path, 0, lambda _: last_t)
+        return ()
 
 
 def _align_num(n: int, alignment: int, type: str):
@@ -52,4 +264,3 @@ class DreamFrameDimensions:
             return (width, height, final_width, final_height)
         else:
             return (height, width, final_height, final_width)
-