ComfyUI Node: 🌻 Batch Image Load From Directory

🌻 Batch Image Load From Directory:

The AD_BatchImageLoadFromDir node is designed to facilitate the batch loading of images from a specified directory, making it an essential tool for AI artists who need to process multiple images efficiently. This node scans a given directory for image files, supporting various formats such as .jpg, .jpeg, .png, .bmp, .gif, and .webp. It allows you to load a specified number of images while skipping a defined number of initial files, providing flexibility in managing large datasets. The node converts the images into a format suitable for further processing in AI models, ensuring they are ready for tasks such as training or inference. By automating the image loading process, this node saves time and reduces the manual effort required to prepare image data, making it a valuable asset in any AI art pipeline.

🌻 Batch Image Load From Directory Input Parameters:

Directory

The Directory parameter specifies the path to the folder containing the images you wish to load. It is crucial to provide the correct path to ensure the node can access and process the images. This parameter is a string and defaults to an empty string, meaning you need to set it explicitly to point to your desired directory.

Load_Cap

The Load_Cap parameter determines the maximum number of images to load from the directory. It allows you to control the batch size, which can be useful for managing memory usage and processing time. The default value is 100, with a minimum of 1 and a maximum of 1000, providing flexibility depending on your system's capabilities and your specific needs.

Skip_Frame

The Skip_Frame parameter allows you to skip a certain number of images at the beginning of the directory. This can be useful if you want to start processing from a specific point in a large dataset. The default value is 0, with a minimum of 0 and a maximum of 100, giving you control over where to begin loading images.

seed

The seed parameter is an integer used for randomization purposes, although its specific role in this node is not detailed in the context. It defaults to 0 and can range from 0 to a very large number (0xffffffffffffffff), allowing for a wide range of potential randomization effects if applicable.

🌻 Batch Image Load From Directory Output Parameters:

Images

The Images output is a list of loaded images, each converted into a format suitable for AI processing. This output is crucial as it provides the actual image data that can be fed into AI models for various tasks.

Image_Paths

The Image_Paths output is a list of strings, each representing the full path to a loaded image. This is useful for tracking the source of each image and for any operations that require knowledge of the file location.

Image_Names_suffix

The Image_Names_suffix output provides a list of the filenames of the loaded images, including their extensions. This can be helpful for identifying images and maintaining a record of the specific files processed.

Image_Names

The Image_Names output is a list of the filenames of the loaded images without their extensions. This is useful for operations that require just the base name of the files, such as logging or further processing.

Count

The Count output is an integer representing the total number of images successfully loaded. This provides a quick reference to verify how many images were processed, which can be useful for debugging and ensuring the correct number of images are being handled.

🌻 Batch Image Load From Directory Usage Tips:

• Ensure the Directory path is correctly set to avoid errors in loading images. Double-check the path for typos or incorrect folder names.
• Adjust the Load_Cap and Skip_Frame parameters to manage memory usage and processing time effectively, especially when dealing with large datasets.

🌻 Batch Image Load From Directory Common Errors and Solutions:

Error loading image '<file_path>': <error_message>

• Explanation: This error occurs when the node encounters an issue while trying to load a specific image file. The problem could be due to a corrupted file, unsupported format, or incorrect file permissions.
• Solution: Verify that the image file is not corrupted and is in a supported format. Check the file permissions to ensure the node has access to read the file. If the issue persists, try opening the image in a standard image viewer to confirm its integrity.