ComfyUI Node: Image Interleaved Upscaler (720p to 1080i)

Image Interleaved Upscaler (720p to 1080i):

The ImageInterleavedUpscaler is a powerful node designed to upscale images while maintaining their aspect ratio through an interleaving technique. This node is particularly beneficial for AI artists who wish to enhance the resolution of their images without compromising on quality. By utilizing interleaving, the node ensures that the upscaled image retains its original details and textures, providing a more natural and visually appealing result. The node is capable of handling various image dimensions and formats, making it versatile for different artistic needs. Its ability to apply edge enhancement further refines the output, ensuring that the upscaled images are sharp and clear. Overall, the ImageInterleavedUpscaler is an essential tool for artists looking to improve the quality of their digital artwork efficiently.

Image Interleaved Upscaler (720p to 1080i) Input Parameters:

image

The image parameter is the input image that you want to upscale. It should be provided as a PyTorch tensor, and the node ensures that it is on the correct device and has the appropriate dimensions for processing. This parameter is crucial as it serves as the base for the upscaling operation.

input_width

The input_width parameter specifies the width of the input image. It is used to determine the scaling factor and ensure that the aspect ratio is maintained during the upscaling process. This parameter is important for achieving the desired output dimensions.

input_height

The input_height parameter indicates the height of the input image. Similar to input_width, it helps in calculating the scaling factor and maintaining the aspect ratio. This ensures that the upscaled image does not appear stretched or distorted.

scale_factor

The scale_factor parameter determines the amount by which the image will be upscaled. A higher scale factor results in a larger image, while a lower scale factor produces a smaller image. This parameter allows you to control the level of detail and resolution in the final output.

field_order

The field_order parameter defines the order in which the fields are interleaved during the upscaling process. It can affect the visual quality of the output, and choosing the correct order is essential for achieving the best results.

blend_factor

The blend_factor parameter controls the blending of fields during the interleaving process. It influences the smoothness and transition between different parts of the image, impacting the overall visual quality.

interpolation_mode

The interpolation_mode parameter specifies the method used for interpolating pixel values during upscaling. Common options include "bilinear" and "nearest," each offering different trade-offs between speed and quality.

field_strength

The field_strength parameter adjusts the intensity of the interleaving effect. A higher field strength can enhance the details in the image, while a lower strength may result in a softer appearance.

edge_enhancement

The edge_enhancement parameter applies additional sharpening to the edges of the upscaled image. This can help in highlighting details and improving the clarity of the final output.

Image Interleaved Upscaler (720p to 1080i) Output Parameters:

output_image

The output_image is the upscaled version of the input image, provided as a PyTorch tensor. It retains the original aspect ratio and incorporates the enhancements specified by the input parameters. This output is crucial for artists looking to achieve high-quality, detailed images from lower-resolution sources.

Image Interleaved Upscaler (720p to 1080i) Usage Tips:

• Experiment with different scale_factor values to find the optimal balance between image size and quality for your specific project.
• Utilize the edge_enhancement parameter to sharpen details in images that may appear too soft after upscaling.
• Adjust the blend_factor to control the smoothness of transitions in the image, which can be particularly useful for images with complex textures.

Image Interleaved Upscaler (720p to 1080i) Common Errors and Solutions:

Expected 4D tensor output (BHWC), got shape <result.shape>

• Explanation: This error occurs when the output image does not have the expected dimensions, which should be a 4D tensor in the format (Batch, Height, Width, Channels).
• Solution: Ensure that the input image is correctly formatted and that all processing steps maintain the required dimensions. Check that the input image is a 3D tensor before processing and that the batch dimension is added correctly.