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Efficiently enhance Florence2 model output images with batch post-processing for consistent high quality results.
Florence2PostprocessAll is a node designed to handle the post-processing of images generated or processed by the Florence2 model. This node is particularly useful for refining and enhancing the output images by applying various post-processing techniques. It ensures that the final images are polished and meet the desired quality standards. The node is capable of handling multiple images at once, making it efficient for batch processing tasks. By utilizing this node, you can achieve consistent and high-quality results across all your images, saving time and effort in manual post-processing.
This parameter represents the Florence2 model and its associated components, including the model itself, the processor, the version, and the device on which it is running. It is essential for the node to function correctly as it provides the necessary tools and configurations for processing the images. The FLORENCE2 parameter ensures that the node can access and utilize the model's capabilities effectively.
The image parameter is the input image or a batch of images that you want to post-process. This parameter is crucial as it provides the raw data that the node will refine and enhance. The quality and characteristics of the input image(s) will directly impact the final output. Ensure that the images are in a compatible format and resolution for optimal results.
The task parameter specifies the type of post-processing task you want to perform on the input image(s). This could include tasks such as sharpening, blending, or other enhancement techniques. The task parameter allows you to customize the post-processing according to your specific needs and desired outcomes. The available options for this parameter will depend on the capabilities of the Florence2 model and the node's implementation.
The text_input parameter allows you to provide additional textual information or instructions that can influence the post-processing task. This can be useful for tasks that require contextual understanding or specific adjustments based on textual descriptions. The text_input parameter adds an extra layer of customization and control over the post-processing process.
The IMAGE output parameter represents the final post-processed image or batch of images. This output is the result of applying the specified post-processing tasks to the input image(s). The IMAGE parameter provides you with the refined and enhanced images that are ready for use or further processing.
The STRING output parameter contains a textual representation of the results, including any relevant information or metadata generated during the post-processing. This can include details about the applied tasks, adjustments made, and other contextual information. The STRING parameter is useful for logging, debugging, or further analysis of the post-processing results.
The F_BBOXES output parameter provides information about any bounding boxes or other relevant features detected or generated during the post-processing. This can include coordinates, labels, and other attributes associated with the features. The F_BBOXES parameter is essential for tasks that involve object detection, segmentation, or other feature-based processing.
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