ComfyUI Node: Blob Track | Akatz

Blob Track | Akatz:

The AK_BlobTrack node is designed to detect and track blobs, or distinct areas of interest, within a sequence of images or video frames. Utilizing OpenCV's SimpleBlobDetector, this node isolates movement through frame differencing and thresholding techniques. It then identifies blobs based on specified criteria such as size and brightness. The node provides a visual representation by drawing outlines around detected blobs and connecting them with lines, enhancing the understanding of movement patterns. This functionality is particularly beneficial for AI artists looking to analyze motion or changes within visual media, offering a straightforward method to highlight and track dynamic elements.

Blob Track | Akatz Input Parameters:

image

This parameter represents the input image or frame sequence where blob detection will be performed. It is essential for the node to process and identify areas of interest.

cache_frames

Determines the number of frames to cache for frame differencing, which is crucial for detecting movement. The value ranges from 1 to 120, with a default of 1, allowing you to control the sensitivity to motion over time.

diff_threshold

Sets the threshold for frame differencing, influencing the sensitivity to changes between frames. The range is from 0.0 to 255.0, with a default of 30.0, where higher values may ignore minor changes.

min_threshold

Defines the minimum threshold for blob detection, affecting the initial sensitivity to potential blobs. It ranges from 0 to 255, with a default of 50.

max_threshold

Specifies the maximum threshold for blob detection, setting the upper limit for blob sensitivity. The range is from 1 to 255, with a default of 220.

threshold_step

Controls the step size between thresholds during blob detection, impacting the granularity of detection. It ranges from 1 to 50, with a default of 10.

filter_by_area

A boolean option to filter blobs based on their area. When set to "true" (default), only blobs within the specified area range are detected.

min_area

Sets the minimum area for blob detection, ensuring that only sufficiently large blobs are considered. The range is from 0.0 to 1e6, with a default of 25.0.

max_area

Defines the maximum area for blob detection, preventing overly large blobs from being detected. The range is from 1.0 to 1e8, with a default of 1e5.

detect_bright_blobs

A boolean option to detect bright blobs. When set to "true", the node focuses on bright areas, with a default of "false".

max_blobs

Limits the number of blobs to be detected, allowing you to focus on the most significant ones. The range is from 1 to 100, with a default of 10.

blob_outline_thickness

Specifies the thickness of the outline drawn around detected blobs, enhancing their visibility. The range is from 1 to 20, with a default of 2.

blob_outline_color

Sets the color of the blob outline using a hex code, with a default of "#ff0000" (red), allowing for customization of the visual output.

blob_outline_alpha

Controls the transparency of the blob outline, with a range from 0.0 (fully transparent) to 1.0 (fully opaque), and a default of 1.0.

line_thickness

Determines the thickness of lines connecting blob centers, aiding in visualizing movement paths. The range is from 1 to 20, with a default of 2.

line_color

Sets the color of the connecting lines using a hex code, with a default of "#00ff00" (green), allowing for customization of the visual output.

line_alpha

Controls the transparency of the connecting lines, with a range from 0.0 (fully transparent) to 1.0 (fully opaque), and a default of 1.0.

Blob Track | Akatz Output Parameters:

IMAGE

The output image with detected blobs outlined and connected by lines, providing a visual representation of movement and areas of interest.

MASK

A binary mask image where detected blobs are filled in white, useful for further processing or analysis of the detected areas.

Blob Track | Akatz Usage Tips:

• Adjust the diff_threshold to fine-tune sensitivity to movement; lower values detect subtle changes, while higher values focus on significant motion.
• Use filter_by_area to exclude irrelevant blobs by setting appropriate min_area and max_area values, ensuring only meaningful blobs are tracked.

Blob Track | Akatz Common Errors and Solutions:

ValueError: Expected 6-digit hex color

• Explanation: This error occurs when the color parameters are not provided in the correct 6-digit hex format.
• Solution: Ensure all color inputs, such as blob_outline_color and line_color, are specified as 6-digit hex codes, e.g., "#ff0000".

Invalid frame index

• Explanation: This error might occur if the cache_frames parameter is set to a value larger than the available frames.
• Solution: Verify that cache_frames does not exceed the number of frames in your input sequence. Adjust the parameter accordingly.