ComfyUI Node: Mask QR Errors

Mask QR Errors:

The comfy-qr-mask_errors node is designed to analyze and compare QR codes, identifying discrepancies between a source QR code and a modified version. This node is particularly useful for detecting errors and variations that may occur during the generation or modification of QR codes. By providing detailed error masks, percentage errors, correlations, and root mean square errors (RMSE), this node helps you understand the quality and accuracy of your QR codes. It is an essential tool for ensuring the reliability and readability of QR codes, especially in applications where precision is critical.

Mask QR Errors Input Parameters:

source_qr

This parameter represents the original QR code that serves as the reference for comparison. It is essential for identifying discrepancies when compared to the modified QR code.

modified_qr

This parameter is the QR code that has been altered or generated anew. The node will compare this QR code against the source_qr to identify any errors or differences.

module_size

Defines the size of each module (or pixel) in the QR code. This parameter impacts the granularity of the error detection. The default value is 16, with a minimum of 1 and a maximum of 64.

grayscale_method

Specifies the method used to convert the QR code to grayscale. This affects how the QR code is processed and compared. Different methods may yield different results based on the color and contrast of the QR codes.

aggregate_method

Determines how the data from the QR code modules are aggregated during the comparison process. This can influence the accuracy and sensitivity of the error detection.

evaluate

A boolean parameter that indicates whether the QR code should be evaluated for errors. Setting this to True enables the error detection process.

error_difficulty

Defines the threshold for what constitutes an error in the QR code. Higher values make the error detection more stringent, while lower values are more lenient.

inverted_pattern

A boolean parameter that specifies whether the QR code pattern is inverted. This is useful for QR codes with non-standard color schemes.

gamma

Adjusts the gamma correction applied to the QR codes during processing. This can help in enhancing the contrast and visibility of the QR code modules.

Mask QR Errors Output Parameters:

QR_ERROR_MASK

This output is a mask that highlights the areas of the QR code where errors were detected. It is useful for visually identifying the specific modules that differ between the source and modified QR codes.

PERCENT_ERROR

This output provides the percentage of modules in the QR code that contain errors. It gives a quantitative measure of the overall accuracy of the modified QR code compared to the source.

CORRELATION

This output indicates the correlation between the source and modified QR codes. A higher correlation value suggests that the two QR codes are more similar, while a lower value indicates greater differences.

RMSE

The Root Mean Square Error (RMSE) output quantifies the average magnitude of the errors between the source and modified QR codes. Lower RMSE values indicate fewer and smaller errors.

Mask QR Errors Usage Tips:

• Ensure that the module_size parameter is set appropriately for the resolution of your QR codes to achieve accurate error detection.
• Use the grayscale_method and aggregate_method parameters to fine-tune the comparison process based on the specific characteristics of your QR codes.
• Adjust the error_difficulty parameter to control the sensitivity of the error detection, especially if you are working with QR codes that have minor variations.
• Utilize the QR_ERROR_MASK output to visually inspect and identify specific areas of the QR code that need correction.

Mask QR Errors Common Errors and Solutions:

"Shape mismatch between source and modified QR codes"

• Explanation: This error occurs when the dimensions of the source and modified QR codes do not match.
• Solution: Ensure that both the source and modified QR codes have the same dimensions before running the node.

"Invalid module size"

• Explanation: The module_size parameter is set to a value outside the acceptable range.
• Solution: Set the module_size parameter to a value between 1 and 64.

"Grayscale method not recognized"

• Explanation: The specified grayscale_method is not supported.
• Solution: Choose a valid grayscale method from the available options.

"Error difficulty threshold too high"

• Explanation: The error_difficulty parameter is set too high, making it impossible to detect any errors.
• Solution: Lower the error_difficulty parameter to a more reasonable value to allow for error detection.