From 9fdacdcf02402ae5c1c4558bdc15caa2c1f182a8 Mon Sep 17 00:00:00 2001 From: db0 Date: Sun, 19 May 2024 18:29:46 +0200 Subject: [PATCH] added comfy_qr --- hordelib/nodes/comfy_qr | 1 - hordelib/nodes/comfy_qr/LICENSE | 661 +++++++++++++++++++++++ hordelib/nodes/comfy_qr/README.md | 146 +++++ hordelib/nodes/comfy_qr/__init__.py | 3 + hordelib/nodes/comfy_qr/qr_nodes.py | 645 ++++++++++++++++++++++ hordelib/nodes/comfy_qr/requirements.txt | 1 + 6 files changed, 1456 insertions(+), 1 deletion(-) delete mode 160000 hordelib/nodes/comfy_qr create mode 100644 hordelib/nodes/comfy_qr/LICENSE create mode 100644 hordelib/nodes/comfy_qr/README.md create mode 100644 hordelib/nodes/comfy_qr/__init__.py create mode 100644 hordelib/nodes/comfy_qr/qr_nodes.py create mode 100644 hordelib/nodes/comfy_qr/requirements.txt diff --git a/hordelib/nodes/comfy_qr b/hordelib/nodes/comfy_qr deleted file mode 160000 index 29cd1235..00000000 --- a/hordelib/nodes/comfy_qr +++ /dev/null @@ -1 +0,0 @@ -Subproject commit 29cd12358e3d24252ff01b014654eff39193a669 diff --git a/hordelib/nodes/comfy_qr/LICENSE b/hordelib/nodes/comfy_qr/LICENSE new file mode 100644 index 00000000..127684a4 --- /dev/null +++ b/hordelib/nodes/comfy_qr/LICENSE @@ -0,0 +1,661 @@ + GNU AFFERO GENERAL PUBLIC LICENSE + Version 3, 19 November 2007 + + Copyright (C) 2007 Free Software Foundation, Inc. + Everyone is permitted to copy and distribute verbatim copies + of this license document, but changing it is not allowed. + + Preamble + + The GNU Affero General Public License is a free, copyleft license for +software and other kinds of works, specifically designed to ensure +cooperation with the community in the case of network server software. + + The licenses for most software and other practical works are designed +to take away your freedom to share and change the works. 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If not, see . + +Also add information on how to contact you by electronic and paper mail. + + If your software can interact with users remotely through a computer +network, you should also make sure that it provides a way for users to +get its source. For example, if your program is a web application, its +interface could display a "Source" link that leads users to an archive +of the code. There are many ways you could offer source, and different +solutions will be better for different programs; see section 13 for the +specific requirements. + + You should also get your employer (if you work as a programmer) or school, +if any, to sign a "copyright disclaimer" for the program, if necessary. +For more information on this, and how to apply and follow the GNU AGPL, see +. diff --git a/hordelib/nodes/comfy_qr/README.md b/hordelib/nodes/comfy_qr/README.md new file mode 100644 index 00000000..c054c53a --- /dev/null +++ b/hordelib/nodes/comfy_qr/README.md @@ -0,0 +1,146 @@ +# ComfyQR + +A set of ComfyUI nodes to dynamically create QR image layers for generative QR art without the hassle of leaving the webui. + +Everything in this pack is primarily focused on the creation of patterns. While the `Mask QR Errors` does some basic statistics on the differences between pixels, a more definative node on determining scannability can be found in the companion project [ComfyQR-scanning-nodes](https://gitlab.com/sofuego-comfy-nodes/ComfyQR-scanning-nodes) which uses additional dependencies for the reading of QRs. + +This repository is managed publicly on [Gitlab](https://gitlab.com/sofuego-comfy-nodes/ComfyQR), but also mirrored on [Github](https://github.com/coreyryanhanson/ComfyQR). Please submit any [issues](https://gitlab.com/sofuego-comfy-nodes/ComfyQR/-/issues) or [pull requests](https://gitlab.com/sofuego-comfy-nodes/ComfyQR/-/merge_requests) to the gitlab repo. + +![QR code with repo link](example_generations/main_qr_inpainted.png) + +## Getting started + +This project currently contains two nodes for generating QR codes. + +### QR Code and QR Code (Split) + +A dynamically sized QR code without any resampling scaled by the text length, the module size, and the error correction level. Use the `QR Code `for simple workflows and the `QR Code (Split)` if you want to build more advanced pipelines with additional outputs for the `MODULE_LAYER`, `FINDER_LAYER`, or `FINDER_MASK`. + +![Split QR Code Node Example](img/node-qr-code-split.png) + +#### Inputs + +* `protocol` - If enabled this will prefix the textbox input with a preset to represent the internet protocol. This is included both for convenience and as a workaround for the textbox clipping strings with this character combination. + * `Http` - Adds "http://" before the text. + * `Https` - Adds "https://" before the text. + * `None` - Uses only the contents of the `text` box. +* `text` - What text to build your QR code with. If `protocol` is specified, this textbox will be combined it with the selected option. +* `module_size` - The pixel width of the smallest unit of a QR code. +* `max_image_size` - The maximum size of the resulting QR code. If the combination of `text`, `module_size`, and `error_correction` create dimensions that exceed this, an error will halt the pipeline. +* `fill_hexcolor` - A string of characters representing the hex value of the QR units. Can be 3 or 6 hexadecimal characters with an optional # before. +* `back_hexcolor` - A string of characters representing the hex value of the space around the QR units. Can be 3 or 6 hexadecimal characters with an optional # before. +* `error_correction` - The level of error correction to apply. + * `Low` - 7% error correction. + * `Medium` - 15% error correction. + * `Quartile` - 25% error correction. + * `High` - 30% error correction. +* `border` - The border size (In multiples of `module` widths) +* `module_drawer` - The shape the QR code modules should be. The default is `square`, but see [Alternate Module Drawers](#alternate-module-drawers) below for new examples. + +#### Outputs + +* `QR_CODE` - The QR code +* `MODULE_LAYER` - The QR code with the `back_hexcolor` filling in the function patterns (to remove their influence from the early diffusion steps). +* `FINDER_LAYER` - The isolated finder patterns over the `back_hexcolor`. +* `FINDER_MASK` - A mask that isolates the locations of the 3 finder patterns. +* `QR_VERSION` - An integer of the QR version that was selected based on the text length and error correction level. +* `IMAGE_SIZE` - An integer based on the pixel width of the resulting QR code. + +### QR Code (Conformed to Image Size) + +![Conformed QR Code Node Example](img/node-qr-code-conformed.png) + +A QR code fixed to specific output dimensions through image resampling. + +#### Inputs + +* `protocol` - If enabled this will prefix the textbox input with a preset to represent the internet protocol. This is included both for convenience and as a workaround for the textbox clipping strings with this character combination. + * `Http` - Adds "http://" before the text. + * `Https` - Adds "https://" before the text. + * `None` - Uses only the contents of the `text` box. +* `text` - What text to build your QR code with. If `protocol` is specified, this textbox will be combined it with the selected option. +* `image_size` - The pixel dimensions to conform the QR code to. +* `fill_hexcolor` - A string of characters representing the hex value of the QR units. Can be 3 or 6 hexadecimal characters with an optional # before. +* `back_hexcolor` - A string of characters representing the hex value of the space around the QR units. Can be 3 or 6 hexadecimal characters with an optional # before. +* `error_correction` - The level of error correction to apply. + * `Low` - 7% error correction. + * `Medium` - 15% error correction. + * `Quartile` - 25% error correction. + * `High` - 30% error correction. +* `border` - The border size (In multiples of `module` widths) +* `resampling` - The resampling algorithm to use when rescaling the QR code. + * `Bicubic` - Bicubic interpolation + * `Bilinear` - Bilinear interpolation + * `Box` - Box interpolation + * `Hamming` - Hamming interpolation + * `Lanczos` - Lanczos interpolation + * `Nearest` - Nearest Neighbor interpolation +* `module_drawer` - The shape the QR code modules should be. The default is `square`, but see [Alternate Module Drawers](#alternate-module-drawers) below for new examples. + +#### Outputs + +* `QR_CODE` - The QR code +* `QR_VERSION` - An integer of the QR version that was selected based on the text length and error correction level. + +### Mask QR Errors + +A node that that will analyze the differences between a modified QR and create a mask of the estimated errors. + +![Mask QR Errors Node Example](img/node-mask-qr-errors.png) + +**Note**: _This is an extremly powerful node but relies on several assumptions in order to be used._ +1. A QR with a fixed module size that has not been resampled irregularly or distorted. +2. Shared allignment between the `source_qr` and `modified_qr`. +3. Fill and back colors must be perfectly white and black (`#FFFFFF`, `#000000`) for the `source_qr`. +4. The canvas can be bigger than the QR code, but on the `source_qr`, there should be no pixels the same color as the module color outside of the QR exterior. + +#### Inputs + +* `source_qr` - The original QR code used to generate the image (with the same placement and dimensions as `modified_qr`). +* `modified_qr` - The generated QR art to evaluate (with the same placement and dimensions as `source_qr`). +* `module_size` - The size in pixels of each QR module (the individual blocks that make up a qr code) in the provided images. +* `grayscale_method` - How to convert the RGB color channels to a single grayscale value. + * `mean` - A simple average of the RGB values. + * `luminance` - Converts colors to grayscale using a [more advanced formula](https://en.wikipedia.org/wiki/Grayscale#Colorimetric_(perceptual_luminance-preserving)_conversion_to_grayscale) to better match percieved brightness. +* `aggregate_method` - How to aggregate the many pixels that make up a QR module into a single value. + * `mean` - Within each module a simple average is taken of all constituent pixels. +* `evaluate` - Which part of the QR to examine. + * `full_qr` - The entire QR code is evaluated. + * `module_pattern` - Has the node focus only on the modules while excluding the finder pattern. + * `finder_pattern` - Ignores the modules while examining only the 3 finder patterns at the corners of the QR. +* `error_difficulty` - It is possible that while using the same reader a QR code could be easily scannable on one monitor, but not on another. The way the colors are displayed can have a major effect on unsability. By increasing this threshold, you are simulating inability to distinguish midrange pixels for both the `PERCENT_ERROR` and `QR_ERROR_MASK` outputs. It ranges from 0 to 1 where 0 only automatically fails perfect grays while 1 accepts only exactly matched modules that are perfectly black or white. +* `inverted_pattern` - If set to `True` this assumes that the QR code has inverted colors (a black background with white modules.) +* `gamma` - If using the `grayscale` method based on `luminance`, this will influence the formula by appending the gamma expansion and compression formulas before and after the color conversion. A gamma of 2.2 will use the [formula specific to srgb](qr_nodes.py#0.04045), while other gamma values will simply use the gamma amount as an exponent. + +#### Outputs + +* `QR_ERROR_MASK` - A mask with white areas falling on locations of modules with errors (precision set by `error_difficulty`). This mask can be used for streamlined img2img operations to salvage unscannable QRs. +* `PERCENT_ERROR` - Number of modules that do not fall into the acceptable threshold (set by `error_difficulty`) divided by the total number of modules. +* `CORRELATION` - The Pearson correlation coefficient between the QR patterns on the `source_qr` and `modified_qr` +* `RMSE` - The root mean squared error between both QR codes. In this case, a value of 0 indicates an identical match to the `source_qr`. A value of 1 indicates a perfect inversion where each expected color is the complete opposite. + +## Examples + +There is an assortment of workflow examples that can be found in the `examples` directory or in the metadata of the images in the `example_generations` folder. For example taking this image. + +![Bad Scan Example](example_generations/unscannable_00001_.png) + +And then aggressively increasing the strength of the ControlNet on only the error pixels to make something previously completely unscannable more reliably across different monitors and QR readers. + +![Fixed Scan Example](example_generations/unscannable_00001_fixed_.png) + +Any workflow in the example that ends with "validated" (and a few image examples) assume the installation of the [scanning pack](https://gitlab.com/sofuego-comfy-nodes/ComfyQR-scanning-nodes) as well. + +## Alternate Module Drawers + +The QR generation nodes now support alternate module styles. Experiment using different ones for greater flexibility during generation. + +| Square | Gapped Square | Circle | Rounded | Vertical bars | Horizontal bars | +|:---: | :---: | :---: | :---: | :---: | :---: | +| ![Example QR](/img/square.png) | ![Example QR](img/gapped_square.png) | ![Example QR](img/circle.png) | ![Example QR](img/rounded.png) | ![Example QR](img/vertical-bars.png) | ![Example QR](img/horizontal-bars.png) | + +**Note** _Even unaltered non square styles will inherently register small deviations from RMSE values and possible minute deviations for correlations when using the [Mask QR Errors](#mask-qr-errors) node. When information is extracted, the `source_qr` values are rounded so that they can only be 0 or 1 (to allow alternate drawers to be used as inputs) and matched against the unrounded aggregation of the `modified_qr` values._ + +## Future updates + +If the solution is clean enough and if it can definitively improve scannability, there may be additional plans for the seperation of alignment patterns (based on `module_size`, `border`, and `QR_VERSION`) for more advanced workflows. diff --git a/hordelib/nodes/comfy_qr/__init__.py b/hordelib/nodes/comfy_qr/__init__.py new file mode 100644 index 00000000..7243352d --- /dev/null +++ b/hordelib/nodes/comfy_qr/__init__.py @@ -0,0 +1,3 @@ +from .qr_nodes import NODE_CLASS_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS + +__all__ = ['NODE_CLASS_MAPPINGS', 'NODE_DISPLAY_NAME_MAPPINGS'] diff --git a/hordelib/nodes/comfy_qr/qr_nodes.py b/hordelib/nodes/comfy_qr/qr_nodes.py new file mode 100644 index 00000000..ac24431c --- /dev/null +++ b/hordelib/nodes/comfy_qr/qr_nodes.py @@ -0,0 +1,645 @@ +import numpy as np +import qrcode +from qrcode.image.styles.moduledrawers import (GappedSquareModuleDrawer, + CircleModuleDrawer, + RoundedModuleDrawer, + VerticalBarsDrawer, + HorizontalBarsDrawer) +from qrcode.image.styledpil import StyledPilImage +from qrcode.image.styles.colormasks import SolidFillColorMask +from qrcode.compat.pil import Image +import torch +import torch.nn.functional as F + + +class QRBase: + def __init__(self): + self.text = "" + self.fill = None + self.back = None + + FUNCTION = "generate_qr" + CATEGORY = "ComfyQR" + + def _get_error_correction_constant(self, error_correction_string): + if error_correction_string == "Low": + return qrcode.constants.ERROR_CORRECT_L + if error_correction_string == "Medium": + return qrcode.constants.ERROR_CORRECT_M + if error_correction_string == "Quartile": + return qrcode.constants.ERROR_CORRECT_Q + return qrcode.constants.ERROR_CORRECT_H + + def _img_to_tensor(self, img): + out_image = np.array(img, dtype=np.uint8).astype(np.float32) / 255 + return torch.from_numpy(out_image).unsqueeze(0) + + def _make_qr(self, qr, fill_hexcolor, back_hexcolor, module_drawer): + self.fill = self._parse_hexcolor_string(fill_hexcolor, "fill_hexcolor") + self.back = self._parse_hexcolor_string(back_hexcolor, "back_hexcolor") + qr.make(fit=True) + if module_drawer == "Square": + # Keeps using Square QR generation the old way for faster speeds. + return qr.make_image(fill_color=self.fill, back_color=self.back) + color_mask = SolidFillColorMask(back_color=self.back, + front_color=self.fill) + module_drawing_method = self._select_module_drawer(module_drawer) + return qr.make_image(image_factory=StyledPilImage, + color_mask=color_mask, + module_drawer=module_drawing_method) + + def _parse_hexcolor_string(self, s, parameter): + if s.startswith("#"): + s = s[1:] + if len(s) == 3: + rgb = (c + c for c in s) + elif len(s) == 6: + rgb = (s[i] + s[i+1] for i in range(0, 6, 2)) + else: + raise ValueError(f"{parameter} must be 3 or 6 characters long") + try: + return tuple(int(channel, 16) for channel in rgb) + except ValueError: + raise ValueError(f"{parameter} contains invalid hexadecimal " + f"characters") + + def _validate_qr_size(self, size, max_size): + if size > max_size: + raise RuntimeError(f"QR dimensions of {size} exceed max size of " + f"{max_size}.") + + def _select_module_drawer(self, module_drawer_string): + """Square is not included in the results, for a speed optimization + applying color masks. Current version of python-qr code suffers a + slowdown when using custom colors combined with custom module drawers. + By bypassing square QRs, non standard colors will load faster.""" + if module_drawer_string == "Gapped square": + return GappedSquareModuleDrawer() + if module_drawer_string == "Circle": + return CircleModuleDrawer() + if module_drawer_string == "Rounded": + return RoundedModuleDrawer() + if module_drawer_string == "Vertical bars": + return VerticalBarsDrawer() + if module_drawer_string == "Horizontal bars": + return HorizontalBarsDrawer() + raise ValueError(f"Module drawing method of {module_drawer_string} " + f"not supported") + + def update_text(self, protocol, text): + """This function takes input from a text box and a chosen internet + protocol and stores a full address within an instance variable. + Backslashes will invalidate text box input and this acts as a + workaround to be able to use them when required in QR strings. + + Args: + protocol: A categorical variable of one of the available internet + protocols. + text: The input from the text box. + """ + if protocol == "Https": + prefix = "https://" + elif protocol == "Http": + prefix = "http://" + elif protocol == "None": + prefix = "" + self.text = prefix + text + + +class QRByImageSize(QRBase): + + @classmethod + def INPUT_TYPES(cls): + return { + "required": { + "protocol": (["Http", "Https", "None"], {"default": "Https"}), + "text": ("STRING", {"multiline": True}), + "image_size": ("INT", {"default": 512, + "min": 64, + "max": 4096, + "step": 64}), + "fill_hexcolor": ("STRING", {"multiline": False, + "default": "#000000"}), + "back_hexcolor": ("STRING", {"multiline": False, + "default": "#FFFFFF"}), + "error_correction": (["Low", "Medium", "Quartile", "High"], + {"default": "High"}), + "border": ("INT", {"default": 1, + "min": 0, + "max": 100, + "step": 1}), + "resampling": (["Bicubic", + "Bilinear", + "Box", + "Hamming", + "Lanczos", + "Nearest" + ], {"default": "Nearest"}), + "module_drawer": (["Square", + "Gapped square", + "Circle", + "Rounded", + "Vertical bars", + "Horizontal bars" + ], {"default": "Square"}) + }, + } + + RETURN_TYPES = ("IMAGE", "INT") + RETURN_NAMES = ("QR_CODE", "QR_VERSION") + + def _select_resampling_method(self, resampling_string): + if resampling_string == "Nearest": + return Image.NEAREST + if resampling_string == "Bicubic": + return Image.BICUBIC + if resampling_string == "Bilinear": + return Image.BILINEAR + if resampling_string == "Lanczos": + return Image.LANCZOS + if resampling_string == "Box": + return Image.BOX + if resampling_string == "Hamming": + return Image.HAMMING + raise ValueError(f"Resampling method of {resampling_string} not " + f"supported") + + def generate_qr( + self, + protocol, + text, + image_size, + fill_hexcolor, + back_hexcolor, + error_correction, + border, + resampling, + module_drawer + ): + resampling_method = self._select_resampling_method(resampling) + error_level = self._get_error_correction_constant(error_correction) + self.update_text(protocol, text) + qr = qrcode.QRCode( + error_correction=error_level, + box_size=16, + border=border) + qr.add_data(self.text) + img = self._make_qr(qr, fill_hexcolor, back_hexcolor, module_drawer) + img = img.resize((image_size, image_size), resample=resampling_method) + return (self._img_to_tensor(img), qr.version) + + +class QRByModuleSize(QRBase): + + @classmethod + def INPUT_TYPES(cls): + return { + "required": { + "protocol": (["Http", "Https", "None"], {"default": "Https"}), + "text": ("STRING", {"multiline": True}), + "module_size": ("INT", {"default": 16, + "min": 1, + "max": 64, + "step": 1}), + "max_image_size": ("INT", {"default": 512, + "min": 64, + "max": 4096, + "step": 64}), + "fill_hexcolor": ("STRING", {"multiline": False, + "default": "#000000"}), + "back_hexcolor": ("STRING", {"multiline": False, + "default": "#FFFFFF"}), + "error_correction": (["Low", "Medium", "Quartile", "High"], + {"default": "High"}), + "border": ("INT", {"default": 1, + "min": 0, + "max": 100, + "step": 1}), + "module_drawer": (["Square", + "Gapped square", + "Circle", + "Rounded", + "Vertical bars", + "Horizontal bars" + ], {"default": "Square"}) + }, + } + + RETURN_TYPES = ("IMAGE", "INT", "INT") + RETURN_NAMES = ("QR_CODE", "QR_VERSION", "IMAGE_SIZE") + + def generate_qr( + self, + protocol, + text, + module_size, + max_image_size, + fill_hexcolor, + back_hexcolor, + error_correction, + border, + module_drawer + ): + self.update_text(protocol, text) + error_level = self._get_error_correction_constant(error_correction) + qr = qrcode.QRCode( + error_correction=error_level, + box_size=module_size, + border=border) + qr.add_data(self.text) + img = self._make_qr(qr, fill_hexcolor, back_hexcolor, module_drawer) + self._validate_qr_size(img.pixel_size, max_image_size) + return (self._img_to_tensor(img), qr.version, img.pixel_size) + + +class QRByModuleSizeSplitFunctionPatterns(QRBase): + + @classmethod + def INPUT_TYPES(cls): + return { + "required": { + "protocol": (["Http", "Https", "None"], {"default": "Https"}), + "text": ("STRING", {"multiline": True}), + "module_size": ("INT", {"default": 16, + "min": 1, + "max": 64, + "step": 1}), + "max_image_size": ("INT", {"default": 512, + "min": 64, + "max": 4096, + "step": 64}), + "fill_hexcolor": ("STRING", {"multiline": False, + "default": "#000000"}), + "back_hexcolor": ("STRING", {"multiline": False, + "default": "#FFFFFF"}), + "error_correction": (["Low", "Medium", "Quartile", "High"], + {"default": "High"}), + "border": ("INT", {"default": 1, + "min": 0, + "max": 100, + "step": 1}), + "module_drawer": (["Square", + "Gapped square", + "Circle", + "Rounded", + "Vertical bars", + "Horizontal bars" + ], {"default": "Square"}) + }, + } + + RETURN_TYPES = ("IMAGE", "IMAGE", "IMAGE", "MASK", "INT", "INT") + RETURN_NAMES = ("QR_CODE", + "MODULE_LAYER", + "FINDER_LAYER", + "FINDER_MASK", + "QR_VERSION", + "IMAGE_SIZE") + + def _generate_finder_pattern_ranges(self, module_size, border_size): + outer = module_size * border_size + inner = 7 * module_size + outer + # Alternate behavior is required to prevent bugs from 0 border_size. + far_outer = -outer if border_size else None + return [ + (outer, inner, outer, inner), + (outer, inner, -inner, far_outer), + (-inner, far_outer, outer, inner) + ] + + def _generate_finder_pattern_mask(self, + pixel_size, + module_size, + border_size): + mask = np.zeros((pixel_size, pixel_size), dtype=bool) + for (x_min, + x_max, + y_min, + y_max) in self._generate_finder_pattern_ranges(module_size, + border_size): + mask[y_min:y_max, x_min:x_max] = True + return mask + + def _apply_fill_to_mask(self, img, mask): + array = np.array(img).copy() + indices = np.nonzero(mask) + array[indices[0], indices[1], :] = self.back + return Image.fromarray(array) + + def _mask_to_tensor(self, mask): + out_image = mask.astype(np.float32) + return torch.from_numpy(out_image).unsqueeze(0) + + def generate_qr( + self, + protocol, + text, + module_size, + max_image_size, + fill_hexcolor, + back_hexcolor, + error_correction, + border, + module_drawer + ): + self.update_text(protocol, text) + error_level = self._get_error_correction_constant(error_correction) + qr = qrcode.QRCode( + error_correction=error_level, + box_size=module_size, + border=border) + qr.add_data(self.text) + img = self._make_qr(qr, fill_hexcolor, back_hexcolor, module_drawer) + pixel_size = img.pixel_size + self._validate_qr_size(pixel_size, max_image_size) + mask = self._generate_finder_pattern_mask(pixel_size, + module_size, + border) + module_image = self._apply_fill_to_mask(img, mask) + function_image = self._apply_fill_to_mask(img, ~mask) + return ( + self._img_to_tensor(img), + self._img_to_tensor(module_image), + self._img_to_tensor(function_image), + self._mask_to_tensor(mask), + qr.version, + pixel_size, + ) + + +class QRErrorMasker: + def __init__(self): + self.module_size = None + self.canvas_shape = None + self.qr_bounds = None + + FUNCTION = "find_qr_errors" + CATEGORY = "ComfyQR" + RETURN_TYPES = ("MASK", "FLOAT", "FLOAT", "FLOAT") + RETURN_NAMES = ("QR_ERROR_MASK", "PERCENT_ERROR", "CORRELATION", "RMSE") + OUTPUT_IS_LIST = (False, True, True, True) + + @classmethod + def INPUT_TYPES(cls): + return { + "required": { + "source_qr": ("IMAGE",), + "modified_qr": ("IMAGE",), + "module_size": ("INT", {"default": 16, + "min": 1, + "max": 64, + "step": 1}), + "grayscale_method": (["mean", "luminance"], + {"default": "luminance"}), + "aggregate_method": (["mean",], {"default": "mean"}), + "evaluate": (["full_qr", "module_pattern", "finder_pattern"], + {"default": "module_pattern"}), + "error_difficulty": ("FLOAT", {"default": 0, + "min": 0, + "max": 1, + "step": .01}), + "inverted_pattern": ("BOOLEAN", {"default": False}), + "gamma": ("FLOAT", {"default": 2.2, + "min": .1, + "max": 2.8, + "step": .1}), + }, + } + + def _get_qr_bounds(self, tensor, invert): + module_color = 1.0 if invert else 0.0 + module_pixels = (tensor == module_color) + indices = torch.nonzero(module_pixels, as_tuple=True) + # The viewer patterns will guarentee a module pixel in the upper left + # The bottom right does not have that guarentee so max is used. + return (indices[0][0], + indices[0].max() + 1, + indices[1][0], indices[1].max() + 1) + + def _extract_pattern_from_bounds(self, tensor): + return tensor[self.qr_bounds[0]: self.qr_bounds[1], + self.qr_bounds[2]: self.qr_bounds[3]] + + def _trim_to_qr_area(self, source_qr, modified_qr, inverted_pattern): + self.qr_bounds = self._get_qr_bounds(source_qr, inverted_pattern) + self._check_bounds_and_module_size() + source_qr = self._extract_pattern_from_bounds(source_qr) + modified_qr = self._extract_pattern_from_bounds(modified_qr) + return source_qr, modified_qr + + def _reshape_tensor_to_modules(self, tensor): + if len(tensor.shape) != 2: + raise RuntimeError("Module reshaping requires a 2 dimensional " + "array.") + length = tensor.shape[0] // self.module_size + reshaped_tensor = tensor.view(length, + self.module_size, + length, + self.module_size) + rehaped_tensor = reshaped_tensor.permute(0, 2, 1, 3).contiguous() + return rehaped_tensor.view(length, length, self.module_size ** 2) + + def _check_bounds_and_module_size(self): + height = self.qr_bounds[1] - self.qr_bounds[0] + width = self.qr_bounds[3] - self.qr_bounds[2] + color_warning = "Make sure that qr_fill and back colors have exact " + "#FFFFFFF and #000000 values (and that module color values do not " + "occur outside the QR) and invert is set correctly." + if width != height: + raise RuntimeError(f"Source QR dimensions are {width} x {height}. " + f"They must be a perfect square. " + f"{color_warning}") + if width % self.module_size: + raise RuntimeError(f"QR width of {width} does not fit module_size " + f"of {self.module_size}. It must be perfectly " + f"divisible. {color_warning}") + + def _check_equal_shape(self, source_qr, modified_qr): + if source_qr.shape != modified_qr.shape: + raise ValueError("Source and modified QR must have the same batch " + "size and dimensions.") + + def _squeeze_by_mean(self, tensor): + return torch.mean(tensor, dim=-1) + + def _gamma_expansion(self, tensor, gamma): + if gamma == 1: + return tensor + if gamma == 2.2: + return torch.where(tensor <= 0.04045, + tensor / 12.92, + (tensor + 0.055) / 1.055) ** 2.4 + return tensor ** gamma + + def _gamma_compression(self, tensor, gamma): + if gamma == 1: + return tensor + if gamma == 2.2: + return torch.where(tensor <= .0031308, + tensor * 12.92, + 1.055 * tensor ** (1/2.4) - 0.055) + return tensor ** (1/gamma) + + def _grayscale_by_luminance(self, tensor, gamma): + weights = torch.tensor([0.2125, 0.7154, 0.0721], dtype=torch.float32) + tensor = self._gamma_expansion(tensor, gamma) + tensor = tensor @ weights + if gamma != 1: + tensor = tensor ** gamma + return self._gamma_compression(tensor, gamma) + + def _squeeze_to_modules(self, tensor, method): + tensor = self._reshape_tensor_to_modules(tensor) + if method == "mean": + return self._squeeze_by_mean(tensor) + raise RuntimeError("Module aggregation currently only supports the " + "mean.") + + def _reduce_to_modules( + self, + source_qr, + modified_qr, + module_size, + grayscale_method, + aggregate_method, + inverted_pattern, + gamma + ): + self.module_size = module_size + self.canvas_shape = (source_qr.shape[0], source_qr.shape[1]) + # Processed first for simplified indexing of QR bounds. + source_qr = self._squeeze_by_mean(source_qr) + source_qr, modified_qr = self._trim_to_qr_area(source_qr, + modified_qr, + inverted_pattern + ) + if grayscale_method == "mean": + modified_qr = self._squeeze_by_mean(modified_qr) + elif grayscale_method == "luminance": + modified_qr = self._grayscale_by_luminance(modified_qr, gamma) + else: + raise ValueError("Currently only mean is supported for rgb to " + "grayscale conversion.") + source_qr = torch.round(self._squeeze_to_modules(source_qr, "mean")) + modified_qr = self._squeeze_to_modules(modified_qr, aggregate_method) + return source_qr, modified_qr + + def _create_finder_pattern_mask(self, width, inverted): + mask = torch.zeros((width, width), dtype=torch.bool) + # When borders are trimmed and QR code has module size of 1, results + # are consistent. + finder_coords = [[0, 7, 0, 7], [0, 7, -7, None], [-7, None, 0, 7]] + for x_min, x_max, y_min, y_max in finder_coords: + mask[y_min:y_max, x_min:x_max] = True + return ~mask if inverted else mask + + def _create_qr_mask(self, tensor, evaluate): + if evaluate == "module_pattern": + return self._create_finder_pattern_mask(tensor, True) + if evaluate == "finder_pattern": + return self._create_finder_pattern_mask(tensor, False) + return None + + def _bin_tensor_to_threshold(self, tensor, contrast_difficulty): + tensor = tensor.clone() + threshold = contrast_difficulty / 2 + # Since we are only interested in value matches and there is a clear + # stable dividing line of .5, bringing in the other array is + # unneccessary and the binning process can be simplified. + bin_condition = (tensor + threshold <= .5) & (tensor != .5) + tensor[bin_condition] = 0.0 + bin_condition = (tensor - threshold >= .5) & (tensor != .5) + tensor[bin_condition] = 1.0 + return tensor + + def _replace_qr_to_canvas(self, tensor): + length = tensor.shape[0] * self.module_size + bounds = self.qr_bounds + tensor = F.interpolate(tensor.unsqueeze(0).unsqueeze(0), + size=(length, length), + mode='nearest') + canvas = torch.zeros(self.canvas_shape, dtype=torch.float32) + canvas[bounds[0]:bounds[1], bounds[2]:bounds[3]] = tensor.squeeze() + return canvas + + def _compare_modules( + self, + source_qr, + modified_qr, + mask, + error_difficulty + ): + modified_qr = self._bin_tensor_to_threshold(modified_qr, + error_difficulty) + error = source_qr != modified_qr + percent_error = error[mask].sum().item() / error[mask].numel() + if mask is not None: + error[~mask] = False + return (self._replace_qr_to_canvas((error).to(torch.float32)), + percent_error) + + def _qr_correlation(self, source_qr, modified_qr, mask): + source_qr = source_qr[mask].numpy().reshape((-1)) + modified_qr = modified_qr[mask].numpy().reshape((-1)) + return np.corrcoef(source_qr, modified_qr)[0, 1] + + def _qr_rmse(self, source_qr, modified_qr, mask): + diff = source_qr[mask].numpy() - modified_qr[mask].numpy() + return np.sqrt((diff ** 2).mean()) + + def find_qr_errors( + self, + source_qr, + modified_qr, + module_size, + grayscale_method, + aggregate_method, + evaluate, + error_difficulty, + inverted_pattern, + gamma, + ): + self._check_equal_shape(source_qr, modified_qr) + error_masks, error_percents, correlations, rmses = [], [], [], [] + for i in range(source_qr.shape[0]): + qr_s, qr_m = source_qr[i], modified_qr[i] + qr_s, qr_m = self._reduce_to_modules(qr_s, + qr_m, + module_size, + grayscale_method, + aggregate_method, + inverted_pattern, + gamma + ) + mask = self._create_qr_mask(qr_s.shape[0], evaluate) + error_mask, percent_error = self._compare_modules(qr_s, + qr_m, + mask, + error_difficulty + ) + correlation = self._qr_correlation(qr_s, qr_m, mask) + rmse = self._qr_rmse(qr_s, qr_m, mask) + error_masks.append(error_mask) + error_percents.append(percent_error) + correlations.append(correlation) + rmses.append(rmse) + error_masks = torch.stack(error_masks, dim=0) + return (error_masks, error_percents, correlations, rmses) + + +NODE_CLASS_MAPPINGS = { + "comfy-qr-by-module-size": QRByModuleSize, + "comfy-qr-by-image-size": QRByImageSize, + "comfy-qr-by-module-split": + QRByModuleSizeSplitFunctionPatterns, + "comfy-qr-mask_errors": QRErrorMasker, + } + + +NODE_DISPLAY_NAME_MAPPINGS = { + "comfy-qr-by-module-size": "QR Code", + "comfy-qr-by-image-size": "QR Code (Conformed " + "to Image Size)", + "comfy-qr-by-module-split": "QR Code (Split)", + "comfy-qr-mask_errors": "Mask QR Errors", + } diff --git a/hordelib/nodes/comfy_qr/requirements.txt b/hordelib/nodes/comfy_qr/requirements.txt new file mode 100644 index 00000000..38f035e9 --- /dev/null +++ b/hordelib/nodes/comfy_qr/requirements.txt @@ -0,0 +1 @@ +qrcode >= 7.1