color match histogram mode deprecated in favor of gradient map

add HTTPS support for StreamWriter
custom GLSL shaders removed from node_list parse

__init__.py

@@ -202,6 +202,8 @@ class Lexicon(metaclass=LexiconMeta):
     G = '🟩', "Green"
     GAMMA = '🔆', "Gamma"
     GI = '💚', "Green Channel"
+    GLSL_CUSTOM = '🧙🏽‍♀️', "User GLSL Shader"
+    GLSL_INTERNAL = '🧙🏽', "Internal GLSL Shader"
     GRADIENT = '🇲🇺', "Gradient"
     H = '🇭', "Hue"
     HI = 'HI', "High / Top of range"
@@ -877,16 +879,16 @@ def __init__(self, *arg, **kw) -> None:
             JOV_IGNORE_NODE = []
 
         node_count = 0
-        for f in (ROOT / 'core').iterdir():
-            if f.suffix != ".py" or f.stem.startswith('_'):
+        for fname in (ROOT / 'core').iterdir():
+            if fname.suffix != ".py" or fname.stem.startswith('_'):
                 continue
-            if f.stem in JOV_IGNORE_NODE or f.stem+'.py' in JOV_IGNORE_NODE:
-                logger.warning(f"💀 [IGNORED] Jovimetrix.core.{f.stem}")
+            if fname.stem in JOV_IGNORE_NODE or fname.stem+'.py' in JOV_IGNORE_NODE:
+                logger.warning(f"💀 [IGNORED] Jovimetrix.core.{fname.stem}")
                 continue
             try:
-                module = importlib.import_module(f"Jovimetrix.core.{f.stem}")
+                module = importlib.import_module(f"Jovimetrix.core.{fname.stem}")
             except Exception as e:
-                logger.warning(f"module failed {f}")
+                logger.warning(f"module failed {fname}")
                 logger.warning(str(e))
                 continue
 
@@ -912,8 +914,11 @@ def __init__(self, *arg, **kw) -> None:
                     else:
                         Session.CLASS_MAPPINGS[name] = class_object
 
-                    desc = class_object.DESCRIPTION if hasattr(class_object, 'DESCRIPTION') else ""
-                    NODE_LIST_MAP[name] = desc.split('.')[0].strip('\n')
+                    if not name.endswith(Lexicon.GLSL_CUSTOM):
+                        desc = class_object.DESCRIPTION if hasattr(class_object, 'DESCRIPTION') else ""
+                        NODE_LIST_MAP[name] = desc.split('.')[0].strip('\n')
+                    else:
+                        logger.debug(f"customs {name}")
                     node_count += 1
 
             logger.info(f"✅ {module.__name__}")

core/compose.py

@@ -42,7 +42,7 @@
 class EnumColorMatchMode(Enum):
     REINHARD = 30
     LUT = 10
-    HISTOGRAM = 20
+    # HISTOGRAM = 20
 
 class EnumColorMatchMap(Enum):
     USER_MAP = 0
@@ -335,7 +335,7 @@ class ColorMatchNode(JOVImageNode):
     NAME = "COLOR MATCH (JOV) 💞"
     CATEGORY = f"JOVIMETRIX 🔺🟩🔵/{JOV_CATEGORY}"
     DESCRIPTION = """
-Adjust the color scheme of one image to match another with the Color Match Node. Choose from various color matching modes, including LUT, Histogram, and Reinhard. You can specify options like color maps, the number of colors, and whether to flip or invert the images. This node allows for the creation of seamless and cohesive visuals, making it ideal for texture work or masking in motion graphics and design projects.
+Adjust the color scheme of one image to match another with the Color Match Node. Choose from various color matching LUTs or Reinhard matching. You can specify a custom user color maps, the number of colors, and whether to flip or invert the images.
 """
 
     @classmethod
@@ -385,7 +385,7 @@ def run(self, **kw) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
                 if pA.ndim == 3 and pA.shape[2] == 4:
                     mask = image_mask(pA)
 
-            h, w = pA.shape[:2]
+            # h, w = pA.shape[:2]
             if pB is None:
                 pB = channel_solid(chan=EnumImageType.BGR)
             else:
@@ -399,21 +399,16 @@ def run(self, **kw) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
                         pB = None
                     colormap = EnumColorMap[colormap]
                     pA = color_match_lut(pA, colormap.value, pB, num_colors)
-                case EnumColorMatchMode.HISTOGRAM:
-                    pB = image_scalefit(pB, w, h, EnumScaleMode.CROP)
-                    pB = image_scalefit(pB, w, h, EnumScaleMode.MATTE)
-                    pA = color_match_histogram(pA, pB)
+
                 case EnumColorMatchMode.REINHARD:
                     pA = color_match_reinhard(pA, pB)
 
 
             if invert == True:
                 pA = image_invert(pA, 1)
 
-            logger.debug(mask)
             if mask is not None:
                 pA = image_mask_add(pA, mask)
-            logger.debug(pA.shape)
 
             images.append(cv2tensor_full(pA, matte))
             pbar.update_absolute(idx)
@@ -659,6 +654,7 @@ def run(self, **kw) -> torch.Tensor:
         pbar = ProgressBar(len(params))
         for idx, (pA, gradient, flip, mode, sample, wihi, matte) in enumerate(params):
             pA = channel_solid(chan=EnumImageType.BGR) if pA is None else tensor2cv(pA)
+            mask = None
             if pA.ndim == 3 and pA.shape[2] == 4:
                 mask = image_mask(pA)
 

core/create_glsl.py

@@ -268,10 +268,10 @@ def import_dynamic() -> Tuple[str,...]:
         class_name = name.title().replace(' ', '_')
         class_name = f'GLSLNode_{class_name}'
 
-        emoji = '🧙🏽‍♀️'
+        emoji = Lexicon.GLSL_CUSTOM
         sort_order = sort
         if fname.startswith(root):
-            emoji = '🧙🏽'
+            emoji = Lexicon.GLSL_INTERNAL
             sort_order -= 10000
 
         category = GLSLNodeDynamic.CATEGORY

core/device_stream.py

@@ -293,6 +293,7 @@ def __init__(self, *arg, **kw) -> None:
         super().__init__(*arg, **kw)
         self.__route = ""
         self.__unique = uuid.uuid4()
+
         self.__device = StreamManager().capture(self.__unique, static=True)
 
     def run(self, **kw) -> Tuple[torch.Tensor]:

node_list.json

@@ -15,9 +15,7 @@
     "FLATTEN (JOV) \u2b07\ufe0f": "Combine multiple input images into a single image by summing their pixel values",
     "GLSL (JOV) \ud83c\udf69": "Execute custom GLSL (OpenGL Shading Language) fragment shaders to generate images or apply effects",
     "GLSL BLEND LINEAR (JOV) \ud83e\uddd9\ud83c\udffd": "Simple linear blend between two images",
-    "GLSL FILTER RANGE (JOV) \ud83e\uddd9\ud83c\udffd\u200d\u2640\ufe0f": "Select pixels from start color through end color",
     "GLSL GRAYSCALE (JOV) \ud83e\uddd9\ud83c\udffd": "Convert input to grayscale",
-    "GLSL HSV ADJUST (JOV) \ud83e\uddd9\ud83c\udffd": "HSV ADJUST",
     "GLSL HSV-2-LAB (JOV) \ud83e\uddd9\ud83c\udffd": "Convert HSV input to LAB",
     "GLSL HSV-2-RGB (JOV) \ud83e\uddd9\ud83c\udffd": "Convert HSV input to RGB",
     "GLSL LAB-2-HSV (JOV) \ud83e\uddd9\ud83c\udffd": "Convert LAB color space to HSV",

sup/stream.py

@@ -4,6 +4,7 @@
 """
 
 import os
+import ssl
 import sys
 import json
 import time
@@ -20,6 +21,8 @@
 import numpy as np
 from PIL import Image, ImageGrab
 
+from comfy.cli_args import args as cmd_args
+
 from loguru import logger
 
 # SPOUT SUPPORT
@@ -557,14 +560,28 @@ def __init__(self, host: str='', port: int=JOV_STREAM_PORT) -> None:
         self.__host = host
         self.__port = port
         self.__address = (self.__host, self.__port)
+        self.__tls_keyfile = cmd_args.tls_keyfile
+        self.__tls_certfile = cmd_args.tls_certfile
         self.__thread_server = threading.Thread(target=self.__server, daemon=True)
         self.__thread_server.start()
         self.__thread_capture = threading.Thread(target=self.__capture, daemon=True)
         self.__thread_capture.start()
         logger.info("STARTED")
 
     def __server(self) -> None:
-        httpd = ThreadingHTTPServer(self.__address, lambda *args: StreamingHandler(StreamingServer.OUT, *args))
+        handler = lambda *args: StreamingHandler(StreamingServer.OUT, *args)
+        httpd = ThreadingHTTPServer(self.__address, handler)
+
+        if self.__tls_keyfile and self.__tls_certfile:
+            # HTTPS mode
+            context = ssl.SSLContext(ssl.PROTOCOL_TLS_SERVER)
+            context.load_cert_chain(self.__tls_certfile, self.__tls_keyfile)
+            httpd.socket = context.wrap_socket(httpd.socket, server_side=True)
+            logger.info(f"HTTPS server {self.__address}")
+        else:
+            # HTTP mode
+            logger.info(f"HTTP server {self.__address}")
+
         while True:
             httpd.handle_request()