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Batch processing node for loading visual media files from specified paths, useful for AI artists for efficient workflows.
The JNodes_LoadVisualMediaFromPath_Batch
node is designed to load visual media files, such as videos or image sequences, from specified paths in a batch processing manner. This node is particularly useful for AI artists who need to process multiple media files simultaneously, ensuring efficient and streamlined workflows. By leveraging this node, you can extract frames from videos or images from sequences, apply various transformations, and prepare the media for further processing or analysis. The node handles different media formats and provides options to control the starting point, sampling rate, and frame skipping, making it a versatile tool for managing large media datasets.
The media_path
parameter specifies the file path to the visual media you want to load. This can be a path to a video file or an image sequence. The node will attempt to open and read the media from this path. Ensure the path is correct and accessible to avoid errors.
The start_at_n
parameter defines the starting point in the media file from which to begin processing. This value, combined with start_at_unit
, determines the exact frame or time to start. For example, if start_at_n
is set to 10 and start_at_unit
is "seconds", the node will start processing from the 10th second of the video.
The start_at_unit
parameter works in conjunction with start_at_n
to specify the unit of the starting point. Common units include "frames" and "seconds". This allows you to precisely control where the media processing begins.
The sample_next_n
parameter indicates the number of frames or time units to sample after the starting point. This helps in selecting a subset of frames for processing, which can be useful for tasks that do not require the entire media file.
The sample_next_unit
parameter, used with sample_next_n
, specifies the unit for sampling. Similar to start_at_unit
, it can be "frames" or "seconds", allowing you to define the sampling interval accurately.
The frame_skip
parameter determines the number of frames to skip between each processed frame. For example, a frame_skip
value of 2 means every third frame will be processed. This is useful for reducing the number of frames and focusing on key frames.
The discard_transparency
parameter is a boolean flag that, when set to true, will discard any transparency information in the frames. This is useful when working with media that includes alpha channels, but you only need the RGB data.
The out_images
parameter is a tensor containing the processed frames or images from the media file. This output can be used for further processing, analysis, or as input to other nodes in your workflow.
The media_info
parameter provides metadata about the processed media, including the total number of frames, original frame rate, width, and height. This information is useful for understanding the characteristics of the media and for debugging purposes.
The output_media_info
parameter contains detailed information about the output media, such as the frame rate after skipping frames, the number of frames processed, and the dimensions of the frames. This helps in verifying the processing results and ensuring they meet your requirements.
media_path
is correct and accessible to avoid file not found errors.start_at_n
and start_at_unit
to precisely control where the media processing begins, which is useful for skipping intros or focusing on specific segments.sample_next_n
and sample_next_unit
to sample frames at desired intervals, reducing the amount of data processed and focusing on key frames.frame_skip
to skip unnecessary frames, which can speed up processing and reduce memory usage.discard_transparency
if you do not need alpha channel information, simplifying the data and potentially improving performance.media_path
does not exist or is incorrect.start_at_n
and start_at_unit
combination results in an invalid starting point.start_at_n
and start_at_unit
values to ensure they fall within the media file's duration.frame_skip
value is too high, resulting in no frames being processed.frame_skip
value to ensure some frames are processed.© Copyright 2024 RunComfy. All Rights Reserved.