feat: QR Code images

README.md

@@ -124,6 +124,10 @@ Custom nodes for ComfyUI providing Controlnet preprocessing capability. Licened
 
 Custom nodes for ComfyUI providing face restoration.
 
+### [ComfyQR](https://gitlab.com/sofuego-comfy-nodes/ComfyQR)
+
+Nodes for generating QR codes
+
 ## Development
 
 Requirements:

hordelib/comfy_horde.py

@@ -97,6 +97,39 @@
 
 
 # isort: off
+
+import logging
+
+
+class InterceptHandler(logging.Handler):
+ """
+ Add logging handler to augment python stdlib logging.
+
+ Logs which would otherwise go to stdlib logging are redirected through
+ loguru.
+ """
+
+ @logger.catch(default=True, reraise=True)
+ def emit(self, record):
+ # Get corresponding Loguru level if it exists.
+ try:
+ level = logger.level(record.levelname).name
+ except ValueError:
+ level = record.levelno
+
+ # Find caller from where originated the logged message.
+ frame, depth = logging.currentframe(), 2
+ while frame and frame.f_code.co_filename == logging.__file__:
+ frame = frame.f_back
+ depth += 1
+
+ logger.opt(depth=depth, exception=record.exc_info).log(level, record.getMessage())
+
+
+# ComfyUI uses stdlib logging, so we need to intercept it.
+logging.basicConfig(handlers=[InterceptHandler()], level=0, force=True)
+
+
 def do_comfy_import(
  force_normal_vram_mode: bool = False,
  extra_comfyui_args: list[str] | None = None,

hordelib/horde.py

@@ -23,6 +23,7 @@
 
 from hordelib.comfy_horde import Comfy_Horde
 from hordelib.consts import MODEL_CATEGORY_NAMES
+from hordelib.nodes.comfy_qr.qr_nodes import QRByModuleSizeSplitFunctionPatterns
 from hordelib.shared_model_manager import SharedModelManager
 from hordelib.utils.dynamicprompt import DynamicPromptParser
 from hordelib.utils.image_utils import ImageUtils
@@ -145,7 +146,7 @@ class HordeLib:
  "sampler_name": {"datatype": str, "values": list(SAMPLERS_MAP.keys()), "default": "k_euler"},
  "cfg_scale": {"datatype": float, "min": 1, "max": 100, "default": 8.0},
  "denoising_strength": {"datatype": float, "min": 0.01, "max": 1.0, "default": 1.0},
- "control_strength": {"datatype": float, "min": 0.01, "max": 1.0, "default": 1.0},
+ "control_strength": {"datatype": float, "min": 0.01, "max": 3.0, "default": 1.0},
  "seed": {"datatype": int, "default": random.randint(0, sys.maxsize)},
  "width": {"datatype": int, "min": 64, "max": 8192, "default": 512, "divisible": 64},
  "height": {"datatype": int, "min": 64, "max": 8192, "default": 512, "divisible": 64},
@@ -171,13 +172,20 @@ class HordeLib:
  "stable_cascade_stage_b": {"datatype": str, "default": None}, # Stable Cascade
  "stable_cascade_stage_c": {"datatype": str, "default": None}, # Stable Cascade
  "extra_source_images": {"datatype": list, "default": []}, # Stable Cascade Remix
+ "extra_texts": {"datatype": list, "default": []}, # QR Codes (for now)
+ "workflow": {"datatype": str, "default": "auto_detect"},
  }
 
  EXTRA_IMAGES_SCHEMA = {
  "image": {"datatype": Image.Image, "default": None},
  "strength": {"datatype": float, "min": 0.0, "max": 5.0, "default": 1.0},
  }
 
+ EXTRA_TEXTS_SCHEMA = {
+ "text": {"datatype": str, "default": ""},
+ "reference": {"datatype": str, "default": None},
+ }
+
  LORA_SCHEMA = {
  "name": {"datatype": str, "default": ""},
  "model": {"datatype": float, "min": -10.0, "max": 10.0, "default": 1.0},
@@ -198,6 +206,7 @@ class HordeLib:
  "sampler.cfg": "cfg_scale",
  "sampler.denoise": "denoising_strength",
  "sampler.seed": "seed",
+ "sampler.noise_seed": "seed",
  "empty_latent_image.height": "height",
  "empty_latent_image.width": "width",
  "sampler.scheduler": "scheduler",
@@ -243,6 +252,27 @@ class HordeLib:
  "2pass_sampler_stage_c.sampler_name": "sampler_name",
  "2pass_sampler_stage_c.denoise": "hires_fix_denoising_strength",
  "2pass_sampler_stage_b.sampler_name": "sampler_name",
+ # QR Codes
+ "sampler_bg.sampler_name": "sampler_name",
+ "sampler_bg.cfg": "cfg_scale",
+ "sampler_bg.denoise": "denoising_strength",
+ "sampler_bg.seed": "seed",
+ "sampler_bg.steps": "ddim_steps",
+ "sampler_bg.noise_seed": "seed",
+ "sampler_fg.sampler_name": "sampler_name",
+ "sampler_fg.cfg": "cfg_scale",
+ "sampler_fg.denoise": "denoising_strength",
+ "sampler_fg.seed": "seed",
+ "sampler_fg.steps": "ddim_steps",
+ "sampler_fg.noise_seed": "seed",
+ "controlnet_bg.strength": "control_strength",
+ "solidmask_grey.width": "width",
+ "solidmask_grey.height": "height",
+ "solidmask_white.width": "width",
+ "solidmask_white.height": "height",
+ "solidmask_black.width": "width",
+ "solidmask_black.height": "height",
+ "qr_code_split.max_image_size": "width",
  }
 
  _comfyui_callback: Callable[[str, dict, str], None] | None = None
@@ -356,6 +386,12 @@ def _validate_data_structure(self, data, schema_definition=PAYLOAD_SCHEMA):
  data["extra_source_images"][i] = self._validate_data_structure(img, HordeLib.EXTRA_IMAGES_SCHEMA)
  data["extra_source_images"] = [x for x in data["extra_source_images"] if x.get("image")]
 
+ # Do the same for extra texts, if we have them in this data structure
+ if data.get("extra_texts"):
+ for i, img in enumerate(data.get("extra_texts")):
+ data["extra_texts"][i] = self._validate_data_structure(img, HordeLib.EXTRA_TEXTS_SCHEMA)
+ data["extra_texts"] = [x for x in data["extra_texts"] if x.get("text")]
+
  return data
 
  def _apply_aihorde_compatibility_hacks(self, payload: dict) -> tuple[dict, list[GenMetadataEntry]]:
@@ -500,6 +536,11 @@ def _apply_aihorde_compatibility_hacks(self, payload: dict) -> tuple[dict, list[
  if not payload.get("hires_fix_denoising_strength"):
  payload["hires_fix_denoising_strength"] = payload.get("denoising_strength")
 
+ if payload.get("workflow") == "qr_code":
+ if payload.get("source_processing") and payload.get("source_processing") != "txt2img":
+ if not payload.get("hires_fix_denoising_strength"):
+ payload["hires_fix_denoising_strength"] = payload.get("denoising_strength")
+
  # # Remap "denoising" to "controlnet strength", historical hack
  # if payload.get("control_type"):
  # if payload.get("denoising_strength"):
@@ -902,6 +943,92 @@ def _final_pipeline_adjustments(self, payload, pipeline_data) -> tuple[dict, lis
  f"unclip_conditioning_{node_index}",
  )
 
+ # If we have a qr code request, we check for extra texts such as the generation url
+ if payload.get("workflow") == "qr_code":
+ original_width = pipeline_params.get("empty_latent_image.width", 512)
+ original_height = pipeline_params.get("empty_latent_image.height", 512)
+ pipeline_params["qr_code_split.max_image_size"] = max(original_width, original_height)
+ pipeline_params["qr_code_split.text"] = "https://haidra.net"
+ for text in payload.get("extra_texts"):
+ if text["reference"] == "qr_text":
+ pipeline_params["qr_code_split.text"] = text["text"]
+ if text["reference"] == "protocol" and text["text"].lower() in ["https", "http"]:
+ pipeline_params["qr_code_split.protocol"] = text["text"].capitalize()
+ if text["reference"] == "module_drawer" and text["text"].lower() in [
+ "square",
+ "gapped square",
+ "circle",
+ "rounded",
+ "vertical bars",
+ "horizontal bars",
+ ]:
+ pipeline_params["qr_code_split.module_drawer"] = text["text"].capitalize()
+ if text["reference"] == "function_layer_prompt":
+ pipeline_params["function_layer_prompt.text"] = text["text"]
+ if text["reference"] == "x_offset" and text["text"].lstrip("-").isdigit():
+ x_offset = int(text["text"])
+ if x_offset < 0:
+ x_offset = 10
+ pipeline_params["qr_flattened_composite.x"] = x_offset
+ if text["reference"] == "y_offset" and text["text"].lstrip("-").isdigit():
+ y_offset = int(text["text"])
+ if y_offset < 0:
+ y_offset = 10
+ pipeline_params["qr_flattened_composite.y"] = y_offset
+ if text["reference"] == "qr_border" and text["text"].lstrip("-").isdigit():
+ border = int(text["text"])
+ if border < 0:
+ border = 10
+ pipeline_params["qr_code_split.border"] = border
+ if not pipeline_params.get("qr_code_split.protocol"):
+ pipeline_params["qr_code_split.protocol"] = "None"
+ if not pipeline_params.get("function_layer_prompt.text"):
+ pipeline_params["function_layer_prompt.text"] = payload["prompt"]
+ try:
+ test_qr = QRByModuleSizeSplitFunctionPatterns()
+ _, _, _, _, _, qr_size = test_qr.generate_qr(
+ protocol=pipeline_params.get("qr_code_split.protocol"),
+ text=pipeline_params["qr_code_split.text"],
+ module_size=16,
+ max_image_size=pipeline_params["qr_code_split.max_image_size"],
+ fill_hexcolor="#FFFFFF",
+ back_hexcolor="#000000",
+ error_correction="High",
+ border=1,
+ module_drawer="Square",
+ )
+ except RuntimeError as err:
+ logger.error(err)
+ pipeline_params["qr_code_split.text"] = "This QR Code is too large for this image"
+ test_qr = QRByModuleSizeSplitFunctionPatterns()
+ qr_size = 624
+
+ if not pipeline_params.get("qr_flattened_composite.x"):
+ x_offset = int((original_width / 2) - qr_size / 2)
+ # I don't know why but through trial and error I've discovered that the QR codes
+ # are more legible when they're placed in an offset which is a multiple of 64
+ x_offset = x_offset - (x_offset % 64) if x_offset % 64 != 0 else x_offset
+ pipeline_params["qr_flattened_composite.x"] = x_offset
+ if pipeline_params.get("qr_flattened_composite.x", 0) > int((original_width) - qr_size):
+ pipeline_params["qr_flattened_composite.x"] = int((original_width) - qr_size) - 10
+ if not pipeline_params.get("qr_flattened_composite.y"):
+ y_offset = int((original_height / 2) - qr_size / 2)
+ y_offset = y_offset - (y_offset % 64) if y_offset % 64 != 0 else y_offset
+ pipeline_params["qr_flattened_composite.y"] = y_offset
+ if pipeline_params.get("qr_flattened_composite.y", 0) > int((original_height) - qr_size):
+ pipeline_params["qr_flattened_composite.y"] = int((original_height) - qr_size) - 10
+ pipeline_params["module_layer_composite.x"] = pipeline_params["qr_flattened_composite.x"]
+ pipeline_params["module_layer_composite.y"] = pipeline_params["qr_flattened_composite.y"]
+ pipeline_params["function_layer_composite.x"] = pipeline_params["qr_flattened_composite.x"]
+ pipeline_params["function_layer_composite.y"] = pipeline_params["qr_flattened_composite.y"]
+ pipeline_params["mask_composite.x"] = pipeline_params["qr_flattened_composite.x"]
+ pipeline_params["mask_composite.y"] = pipeline_params["qr_flattened_composite.y"]
+ if SharedModelManager.manager.compvis:
+ model_details = SharedModelManager.manager.compvis.get_model_reference_info(payload["model_name"])
+ if model_details and model_details.get("baseline") == "stable diffusion 1":
+ pipeline_params["controlnet_qr_model_loader.control_net_name"] = (
+ "control_v1p_sd15_qrcode_monster_v2.safetensors"
+ )
  return pipeline_params, faults
 
  def _get_appropriate_pipeline(self, params):
@@ -921,8 +1048,11 @@ def _get_appropriate_pipeline(self, params):
  # stable_cascade
  # stable_cascade_remix
  # stable_cascade_2pass
+ # qr_code
 
  # controlnet, controlnet_hires_fix controlnet_annotator
+ if params.get("workflow") == "qr_code":
+ return "qr_code"
  if params.get("model_name"):
  model_details = SharedModelManager.manager.compvis.get_model_reference_info(params["model_name"])
  if model_details.get("baseline") == "stable_cascade":