ComfyUI Node: LoadJPGFrame

LoadJPGFrame:

The LoadJPGFrame node is designed to load a specific frame from a sequence of JPEG images stored in a directory. This node is particularly useful for AI artists who work with image sequences or video frames and need to process individual frames for tasks such as animation, video editing, or frame-by-frame image manipulation. By specifying the frame number, frame rate, and path to the directory containing the JPEG images, you can easily load and convert the desired frame into a format suitable for further processing in your AI workflows. The node ensures that the loaded image is in RGB format and normalized, making it ready for use in various AI models and applications.

LoadJPGFrame Input Parameters:

frame

The frame parameter specifies the frame number you want to load from the sequence of JPEG images. It is an integer value with a minimum of 1 and a maximum of 100000, ensuring flexibility in handling large sequences. The default value is 1. This parameter is crucial as it determines which specific image file (e.g., 00001.jpg, 00002.jpg, etc.) will be loaded from the directory.

frameRate

The frameRate parameter defines the rate at which frames are processed, measured in frames per second (FPS). It is an integer value ranging from 0 to 144, with a default value of 0. If set to a non-zero value, the node will introduce a delay to simulate the specified frame rate, which can be useful for synchronizing with other time-based processes or for creating a real-time playback effect.

path

The path parameter is a string that specifies the directory path where the JPEG images are stored. The default value is an empty string, and this parameter is not forced to be input, meaning it can be left blank if the path is set elsewhere in your workflow. This parameter is essential as it tells the node where to find the image files to load the specified frame.

LoadJPGFrame Output Parameters:

IMAGE

The IMAGE output parameter provides the loaded frame as an image tensor. This tensor is in RGB format and normalized to a range of 0 to 1, making it suitable for further processing in AI models. The output is a PyTorch tensor with an added batch dimension, ensuring compatibility with various deep learning frameworks and applications.

LoadJPGFrame Usage Tips:

• Ensure that the path parameter correctly points to the directory containing your JPEG images to avoid file not found errors.
• Use the frameRate parameter to control the processing speed, especially if you need to synchronize the frame loading with other time-dependent processes.
• Verify that the frame number specified in the frame parameter exists in the directory to prevent runtime errors.

LoadJPGFrame Common Errors and Solutions:

Error reading image file: <error_message>

• Explanation: This error occurs when the node fails to read the specified image file, possibly due to an incorrect path, missing file, or unsupported file format.
• Solution: Ensure that the path parameter is correct and that the specified frame number exists in the directory. Verify that the image files are in JPEG format and named correctly (e.g., 00001.jpg, 00002.jpg, etc.).

Error reading image file: cannot identify image file

• Explanation: This error indicates that the node could not identify the file as a valid image, which may happen if the file is corrupted or not a JPEG image.
• Solution: Check the integrity of the image files and ensure they are in the correct JPEG format. Replace any corrupted files and try again.