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@@ -33,3 +33,12 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+custom_nodes/ComfyQR/example_generations/main_qr_error_corrected.png filter=lfs diff=lfs merge=lfs -text
+custom_nodes/ComfyQR/example_generations/main_qr_inpainted.png filter=lfs diff=lfs merge=lfs -text
+custom_nodes/ComfyQR/example_generations/main_qr_unscannable.png filter=lfs diff=lfs merge=lfs -text
+custom_nodes/ComfyQR/example_generations/old_main_qr_first_iteration.png filter=lfs diff=lfs merge=lfs -text
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+custom_nodes/ComfyQR/example_generations/unscannable_00001_fixed_.png filter=lfs diff=lfs merge=lfs -text
+custom_nodes/ComfyQR/img/for_deletion/badgers_levels_adjusted.png filter=lfs diff=lfs merge=lfs -text
+custom_nodes/ComfyQR/img/for_deletion/badgers.png filter=lfs diff=lfs merge=lfs -text
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custom_nodes/ComfyQR/LICENSE

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+                    GNU AFFERO GENERAL PUBLIC LICENSE
+                       Version 3, 19 November 2007
+
+ Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/>
+ Everyone is permitted to copy and distribute verbatim copies
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+                            Preamble
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+GNU Affero General Public License, you may choose any version ever published
+by the Free Software Foundation.
+
+  If the Program specifies that a proxy can decide which future
+versions of the GNU Affero General Public License can be used, that proxy's
+public statement of acceptance of a version permanently authorizes you
+to choose that version for the Program.
+
+  Later license versions may give you additional or different
+permissions.  However, no additional obligations are imposed on any
+author or copyright holder as a result of your choosing to follow a
+later version.
+
+  15. Disclaimer of Warranty.
+
+  THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
+APPLICABLE LAW.  EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
+HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
+OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
+THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
+PURPOSE.  THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM
+IS WITH YOU.  SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
+ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
+
+  16. Limitation of Liability.
+
+  IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
+WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
+THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
+GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
+USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
+DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
+PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
+EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
+SUCH DAMAGES.
+
+  17. Interpretation of Sections 15 and 16.
+
+  If the disclaimer of warranty and limitation of liability provided
+above cannot be given local legal effect according to their terms,
+reviewing courts shall apply local law that most closely approximates
+an absolute waiver of all civil liability in connection with the
+Program, unless a warranty or assumption of liability accompanies a
+copy of the Program in return for a fee.
+
+                     END OF TERMS AND CONDITIONS
+
+            How to Apply These Terms to Your New Programs
+
+  If you develop a new program, and you want it to be of the greatest
+possible use to the public, the best way to achieve this is to make it
+free software which everyone can redistribute and change under these terms.
+
+  To do so, attach the following notices to the program.  It is safest
+to attach them to the start of each source file to most effectively
+state the exclusion of warranty; and each file should have at least
+the "copyright" line and a pointer to where the full notice is found.
+
+    <one line to give the program's name and a brief idea of what it does.>
+    Copyright (C) 2023  Corey Ryan Hanson
+
+    This program is free software: you can redistribute it and/or modify
+    it under the terms of the GNU Affero General Public License as published
+    by the Free Software Foundation, either version 3 of the License, or
+    (at your option) any later version.
+
+    This program is distributed in the hope that it will be useful,
+    but WITHOUT ANY WARRANTY; without even the implied warranty of
+    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+    GNU Affero General Public License for more details.
+
+    You should have received a copy of the GNU Affero General Public License
+    along with this program.  If not, see <https://www.gnu.org/licenses/>.
+
+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
+<https://www.gnu.org/licenses/>.

custom_nodes/ComfyQR/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.

custom_nodes/ComfyQR/__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']

custom_nodes/ComfyQR/examples/img2img-on-errors-validated.json

@@ -0,0 +1,2078 @@
+{
+  "last_node_id": 52,
+  "last_link_id": 116,
+  "nodes": [
+    {
+      "id": 19,
+      "type": "PreviewImage",
+      "pos": [
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+        158.36729999999957
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+      "size": {
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+        "1": 246
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+      "flags": {},
+      "order": 33,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "images",
+          "type": "IMAGE",
+          "link": 27
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "PreviewImage"
+      }
+    },
+    {
+      "id": 20,
+      "type": "MaskToImage",
+      "pos": [
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+      "mode": 0,
+      "inputs": [
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+          "type": "MASK",
+          "link": 113
+        }
+      ],
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            27
+          ],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "MaskToImage"
+      }
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+    {
+      "id": 10,
+      "type": "CLIPTextEncode",
+      "pos": [
+        -242.0780999999985,
+        498.3673000000002
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+      "mode": 0,
+      "inputs": [
+        {
+          "name": "clip",
+          "type": "CLIP",
+          "link": 8
+        }
+      ],
+      "outputs": [
+        {
+          "name": "CONDITIONING",
+          "type": "CONDITIONING",
+          "links": [
+            10
+          ],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "title": "Positive Prompt",
+      "properties": {
+        "Node name for S&R": "CLIPTextEncode"
+      },
+      "widgets_values": [
+        "An evil robot inside a factory destroys paperwork by firing a laser beam with his eyes, futuristic, colorful"
+      ]
+    },
+    {
+      "id": 11,
+      "type": "CLIPTextEncode",
+      "pos": [
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+      "mode": 0,
+      "inputs": [
+        {
+          "name": "clip",
+          "type": "CLIP",
+          "link": 9
+        }
+      ],
+      "outputs": [
+        {
+          "name": "CONDITIONING",
+          "type": "CONDITIONING",
+          "links": [
+            11
+          ],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "title": "Negative Prompt",
+      "properties": {
+        "Node name for S&R": "CLIPTextEncode"
+      },
+      "widgets_values": [
+        "worst quality"
+      ]
+    },
+    {
+      "id": 9,
+      "type": "CheckpointLoaderSimple",
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+      "mode": 0,
+      "outputs": [
+        {
+          "name": "MODEL",
+          "type": "MODEL",
+          "links": [
+            16
+          ],
+          "shape": 3,
+          "slot_index": 0
+        },
+        {
+          "name": "CLIP",
+          "type": "CLIP",
+          "links": [
+            8,
+            9
+          ],
+          "shape": 3,
+          "slot_index": 1
+        },
+        {
+          "name": "VAE",
+          "type": "VAE",
+          "links": [
+            18,
+            33
+          ],
+          "shape": 3,
+          "slot_index": 2
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "CheckpointLoaderSimple"
+      },
+      "widgets_values": [
+        "1.5/Deliberate-inpainting.safetensors"
+      ]
+    },
+    {
+      "id": 25,
+      "type": "PrimitiveNode",
+      "pos": [
+        1037.9219000000098,
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+      "size": {
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+        "1": 82
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+      "flags": {},
+      "order": 1,
+      "mode": 0,
+      "outputs": [
+        {
+          "name": "INT",
+          "type": "INT",
+          "links": [
+            38,
+            39,
+            40,
+            41
+          ],
+          "slot_index": 0,
+          "widget": {
+            "name": "left"
+          }
+        }
+      ],
+      "title": "Pad",
+      "properties": {
+        "Run widget replace on values": false
+      },
+      "widgets_values": [
+        40,
+        "fixed"
+      ]
+    },
+    {
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+      "type": "PrimitiveNode",
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+      "size": {
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+        "1": 106
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+      "flags": {},
+      "order": 2,
+      "mode": 0,
+      "outputs": [
+        {
+          "name": "COMBO",
+          "type": "COMBO",
+          "links": [
+            46,
+            48
+          ],
+          "slot_index": 0,
+          "widget": {
+            "name": "protocol"
+          }
+        }
+      ],
+      "title": "Protocol",
+      "properties": {
+        "Run widget replace on values": false
+      },
+      "widgets_values": [
+        "Https",
+        "fixed",
+        ""
+      ]
+    },
+    {
+      "id": 29,
+      "type": "PrimitiveNode",
+      "pos": [
+        -535.078099999998,
+        -266.6327000000004
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+      "size": {
+        "0": 210,
+        "1": 76
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+      "flags": {},
+      "order": 3,
+      "mode": 0,
+      "outputs": [
+        {
+          "name": "STRING",
+          "type": "STRING",
+          "links": [
+            47,
+            85
+          ],
+          "slot_index": 0,
+          "widget": {
+            "name": "text"
+          }
+        }
+      ],
+      "title": "URL",
+      "properties": {
+        "Run widget replace on values": false
+      },
+      "widgets_values": [
+        "gitlab.com/sofuego-comfy-nodes/comfy-qr-validation-nodes"
+      ]
+    },
+    {
+      "id": 22,
+      "type": "VAEEncode",
+      "pos": [
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+        231
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+        "1": 46
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+      "flags": {},
+      "order": 15,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "pixels",
+          "type": "IMAGE",
+          "link": 87
+        },
+        {
+          "name": "vae",
+          "type": "VAE",
+          "link": 33
+        }
+      ],
+      "outputs": [
+        {
+          "name": "LATENT",
+          "type": "LATENT",
+          "links": [
+            31
+          ],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "VAEEncode"
+      }
+    },
+    {
+      "id": 14,
+      "type": "KSampler",
+      "pos": [
+        647.9219000000045,
+        458.3673000000005
+      ],
+      "size": {
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+        "1": 474
+      },
+      "flags": {},
+      "order": 26,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "model",
+          "type": "MODEL",
+          "link": 16
+        },
+        {
+          "name": "positive",
+          "type": "CONDITIONING",
+          "link": 35
+        },
+        {
+          "name": "negative",
+          "type": "CONDITIONING",
+          "link": 36
+        },
+        {
+          "name": "latent_image",
+          "type": "LATENT",
+          "link": 32
+        }
+      ],
+      "outputs": [
+        {
+          "name": "LATENT",
+          "type": "LATENT",
+          "links": [
+            17
+          ],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "KSampler"
+      },
+      "widgets_values": [
+        507775986242591,
+        "randomize",
+        25,
+        8,
+        "euler_ancestral",
+        "normal",
+        0.9600000000000002
+      ]
+    },
+    {
+      "id": 8,
+      "type": "MaskToImage",
+      "pos": [
+        558,
+        -42
+      ],
+      "size": {
+        "0": 210,
+        "1": 26
+      },
+      "flags": {},
+      "order": 23,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "mask",
+          "type": "MASK",
+          "link": 92
+        }
+      ],
+      "outputs": [
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custom_nodes/ComfyQR/examples/img2img-on-errors.json

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custom_nodes/ComfyQR/examples/img2img-only.json

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custom_nodes/ComfyQR/examples/module-driven-control-net.json

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custom_nodes/ComfyQR/examples/noisy-latent-split-controlnet.json

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+      69,
+      0,
+      39,
+      1,
+      "Http,Https,None"
+    ],
+    [
+      159,
+      13,
+      0,
+      12,
+      0,
+      "IMAGE"
+    ]
+  ],
+  "groups": [],
+  "config": {},
+  "extra": {},
+  "version": 0.4
+}

custom_nodes/ComfyQR/examples/simple-qr-error-mask.json

@@ -0,0 +1,427 @@
+{
+  "last_node_id": 11,
+  "last_link_id": 12,
+  "nodes": [
+    {
+      "id": 5,
+      "type": "MaskToImage",
+      "pos": [
+        420,
+        740
+      ],
+      "size": {
+        "0": 210,
+        "1": 26
+      },
+      "flags": {},
+      "order": 3,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "mask",
+          "type": "MASK",
+          "link": 1
+        }
+      ],
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            3
+          ],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "MaskToImage"
+      }
+    },
+    {
+      "id": 6,
+      "type": "ImageCompositeMasked",
+      "pos": [
+        640,
+        280
+      ],
+      "size": {
+        "0": 315,
+        "1": 146
+      },
+      "flags": {},
+      "order": 4,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "destination",
+          "type": "IMAGE",
+          "link": 3
+        },
+        {
+          "name": "source",
+          "type": "IMAGE",
+          "link": 12
+        },
+        {
+          "name": "mask",
+          "type": "MASK",
+          "link": null
+        }
+      ],
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            8
+          ],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "ImageCompositeMasked"
+      },
+      "widgets_values": [
+        16,
+        16,
+        false
+      ]
+    },
+    {
+      "id": 2,
+      "type": "LoadImage",
+      "pos": [
+        680,
+        520
+      ],
+      "size": {
+        "0": 315,
+        "1": 314.0000305175781
+      },
+      "flags": {},
+      "order": 0,
+      "mode": 0,
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            9
+          ],
+          "shape": 3,
+          "slot_index": 0
+        },
+        {
+          "name": "MASK",
+          "type": "MASK",
+          "links": null,
+          "shape": 3
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "LoadImage"
+      },
+      "widgets_values": [
+        "unscannable_00001_.png",
+        "image"
+      ]
+    },
+    {
+      "id": 9,
+      "type": "comfy-qr-mask_errors",
+      "pos": [
+        1030,
+        310
+      ],
+      "size": {
+        "0": 317.4000244140625,
+        "1": 238
+      },
+      "flags": {},
+      "order": 5,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "source_qr",
+          "type": "IMAGE",
+          "link": 8
+        },
+        {
+          "name": "modified_qr",
+          "type": "IMAGE",
+          "link": 9
+        }
+      ],
+      "outputs": [
+        {
+          "name": "QR_ERROR_MASK",
+          "type": "MASK",
+          "links": [
+            10
+          ],
+          "shape": 3,
+          "slot_index": 0
+        },
+        {
+          "name": "PERCENT_ERROR",
+          "type": "FLOAT",
+          "links": null,
+          "shape": 3
+        },
+        {
+          "name": "CORRELATION",
+          "type": "FLOAT",
+          "links": null,
+          "shape": 3
+        },
+        {
+          "name": "RMSE",
+          "type": "FLOAT",
+          "links": null,
+          "shape": 3
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "comfy-qr-mask_errors"
+      },
+      "widgets_values": [
+        16,
+        "mean",
+        "mean",
+        "module_pattern",
+        0,
+        false
+      ]
+    },
+    {
+      "id": 8,
+      "type": "MaskToImage",
+      "pos": [
+        1399,
+        333
+      ],
+      "size": {
+        "0": 210,
+        "1": 26
+      },
+      "flags": {},
+      "order": 6,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "mask",
+          "type": "MASK",
+          "link": 10
+        }
+      ],
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            11
+          ],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "MaskToImage"
+      }
+    },
+    {
+      "id": 10,
+      "type": "SaveImage",
+      "pos": [
+        1574,
+        474
+      ],
+      "size": {
+        "0": 315,
+        "1": 270
+      },
+      "flags": {},
+      "order": 7,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "images",
+          "type": "IMAGE",
+          "link": 11
+        }
+      ],
+      "properties": {},
+      "widgets_values": [
+        "ComfyUI"
+      ]
+    },
+    {
+      "id": 4,
+      "type": "SolidMask",
+      "pos": [
+        38,
+        733
+      ],
+      "size": {
+        "0": 315,
+        "1": 106
+      },
+      "flags": {},
+      "order": 1,
+      "mode": 0,
+      "outputs": [
+        {
+          "name": "MASK",
+          "type": "MASK",
+          "links": [
+            1
+          ],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "SolidMask"
+      },
+      "widgets_values": [
+        0.5,
+        768,
+        768
+      ]
+    },
+    {
+      "id": 11,
+      "type": "comfy-qr-by-module-split",
+      "pos": [
+        111,
+        258
+      ],
+      "size": {
+        "0": 400,
+        "1": 344
+      },
+      "flags": {},
+      "order": 2,
+      "mode": 0,
+      "outputs": [
+        {
+          "name": "QR_CODE",
+          "type": "IMAGE",
+          "links": [
+            12
+          ],
+          "shape": 3,
+          "slot_index": 0
+        },
+        {
+          "name": "MODULE_LAYER",
+          "type": "IMAGE",
+          "links": null,
+          "shape": 3
+        },
+        {
+          "name": "FINDER_LAYER",
+          "type": "IMAGE",
+          "links": null,
+          "shape": 3
+        },
+        {
+          "name": "FINDER_MASK",
+          "type": "MASK",
+          "links": null,
+          "shape": 3
+        },
+        {
+          "name": "QR_VERSION",
+          "type": "INT",
+          "links": null,
+          "shape": 3
+        },
+        {
+          "name": "IMAGE_SIZE",
+          "type": "INT",
+          "links": null,
+          "shape": 3
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "comfy-qr-by-module-split"
+      },
+      "widgets_values": [
+        "Https",
+        "gitlab.com/sofuego-comfy-nodes/comfy-qr-validation-nodes",
+        16,
+        768,
+        "#000000",
+        "#FFFFFF",
+        "High",
+        1,
+        "Square"
+      ]
+    }
+  ],
+  "links": [
+    [
+      1,
+      4,
+      0,
+      5,
+      0,
+      "MASK"
+    ],
+    [
+      3,
+      5,
+      0,
+      6,
+      0,
+      "IMAGE"
+    ],
+    [
+      8,
+      6,
+      0,
+      9,
+      0,
+      "IMAGE"
+    ],
+    [
+      9,
+      2,
+      0,
+      9,
+      1,
+      "IMAGE"
+    ],
+    [
+      10,
+      9,
+      0,
+      8,
+      0,
+      "MASK"
+    ],
+    [
+      11,
+      8,
+      0,
+      10,
+      0,
+      "IMAGE"
+    ],
+    [
+      12,
+      11,
+      0,
+      6,
+      1,
+      "IMAGE"
+    ]
+  ],
+  "groups": [],
+  "config": {},
+  "extra": {},
+  "version": 0.4
+}

custom_nodes/ComfyQR/examples/simple-qr-export.json

@@ -0,0 +1,92 @@
+{
+  "last_node_id": 3,
+  "last_link_id": 2,
+  "nodes": [
+    {
+      "id": 2,
+      "type": "SaveImage",
+      "pos": [
+        1034,
+        495
+      ],
+      "size": {
+        "0": 315,
+        "1": 270
+      },
+      "flags": {},
+      "order": 1,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "images",
+          "type": "IMAGE",
+          "link": 2
+        }
+      ],
+      "properties": {},
+      "widgets_values": [
+        "ComfyUI"
+      ]
+    },
+    {
+      "id": 3,
+      "type": "comfy-qr-by-image-size",
+      "pos": [
+        516,
+        479
+      ],
+      "size": {
+        "0": 400,
+        "1": 264
+      },
+      "flags": {},
+      "order": 0,
+      "mode": 0,
+      "outputs": [
+        {
+          "name": "QR_CODE",
+          "type": "IMAGE",
+          "links": [
+            2
+          ],
+          "shape": 3,
+          "slot_index": 0
+        },
+        {
+          "name": "QR_VERSION",
+          "type": "INT",
+          "links": null,
+          "shape": 3
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "comfy-qr-by-image-size"
+      },
+      "widgets_values": [
+        "Https",
+        "gitlab.com/sofuego-comfy-nodes/comfy-qr",
+        512,
+        "00F",
+        "FF0",
+        "High",
+        1,
+        "Nearest",
+        "Circle"
+      ]
+    }
+  ],
+  "links": [
+    [
+      2,
+      3,
+      0,
+      2,
+      0,
+      "IMAGE"
+    ]
+  ],
+  "groups": [],
+  "config": {},
+  "extra": {},
+  "version": 0.4
+}

custom_nodes/ComfyQR/pyproject.toml

@@ -0,0 +1,15 @@
+[project]
+name = "comfyqr"
+description = "QR generation within ComfyUI. Contains nodes suitable for workflows from generating basic QR images to techniques with advanced QR masking."
+version = "0.4.0"
+license = { file = "LICENSE" }
+dependencies = ["qrcode >= 7.1"]
+
+[project.urls]
+Repository = "https://github.com/coreyryanhanson/ComfyQR"
+#  Used by Comfy Registry https://comfyregistry.org
+
+[tool.comfy]
+PublisherId = "coreyryanhanson"
+DisplayName = "ComfyQR"
+Icon = ""

custom_nodes/ComfyQR/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 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",
+                              }

custom_nodes/ComfyQR/requirements.txt

@@ -0,0 +1 @@
+qrcode >= 7.1