ComfyUI Node: FLUX 1.0 [depth] Finetuned

FLUX 1.0 [depth] Finetuned:

FLUX 1.0 [depth] Finetuned is a specialized node designed to enhance image generation by leveraging depth information in a finely tuned manner. This node is part of the Flux Finetuned category, which focuses on providing more precise and controlled outputs by utilizing additional depth data. The primary goal of this node is to allow artists to generate images that are not only visually appealing but also exhibit a realistic sense of depth and perspective. By incorporating depth information, the node can produce images with enhanced dimensionality and detail, making it an invaluable tool for creating complex and lifelike scenes. This capability is particularly beneficial for projects that require a high level of detail and realism, such as architectural visualizations, game environments, and cinematic scenes.

FLUX 1.0 [depth] Finetuned Input Parameters:

prompt

The prompt parameter is a required input that allows you to provide a textual description of the image you wish to generate. This parameter supports multiline text, enabling you to include detailed and complex prompts to guide the image generation process. The prompt serves as the primary source of inspiration for the node, influencing the overall theme, style, and content of the generated image.

control_image

The control_image parameter is a required input that accepts an image file. This image serves as a reference or guide for the node, helping it to understand the desired depth and perspective for the generated output. By providing a control image, you can ensure that the generated image aligns with specific visual characteristics or compositions present in the reference image.

finetune_id

The finetune_id parameter is a required input that specifies the identifier for the finetuning model to be used. This parameter allows you to select a specific finetuning configuration that has been pre-trained to enhance certain aspects of image generation, such as style or content. The finetune_id ensures that the node applies the appropriate adjustments to achieve the desired output.

finetune_strength

The finetune_strength parameter is an optional input that controls the intensity of the finetuning applied to the image generation process. It is a float value with a default of 1.1, a minimum of 0.0, and a maximum of 2.0. Adjusting this parameter allows you to fine-tune the balance between the original model's capabilities and the enhancements provided by the finetuning model, giving you greater control over the final output.

seed

The seed parameter is an optional input that sets the random seed for the image generation process. It is an integer value with a default of 0, a minimum of 0, and a maximum of 4294967294. By specifying a seed, you can ensure reproducibility of the generated images, allowing you to achieve consistent results across multiple runs with the same input parameters.

guidance

The guidance parameter is an optional input that influences the adherence of the generated image to the provided prompt. It is a float value with a default of 15.0, a minimum of 1.0, and a maximum of 100, with a step of 0.1. Higher guidance values result in images that more closely follow the prompt, while lower values allow for more creative freedom and variation in the output.

steps

The steps parameter is an optional input that determines the number of steps taken during the image generation process. It is an integer value with a default of 50, a minimum of 15, and a maximum of 50. Increasing the number of steps can lead to more detailed and refined images, but may also increase the processing time.

prompt_upsampling

The prompt_upsampling parameter is an optional boolean input that, when enabled, enhances the resolution of the prompt's influence on the generated image. The default value is False. Enabling this option can result in images with finer details and sharper features, particularly when using complex or detailed prompts.

safety_tolerance

The safety_tolerance parameter is an optional input that sets the level of safety filtering applied to the generated image. It is an integer value with a default of 2, a minimum of 0, and a maximum of 6. This parameter helps to ensure that the output adheres to content guidelines and avoids generating inappropriate or harmful content.

output_format

The output_format parameter is an optional input that specifies the format of the generated image file. It is a string value with a default of "jpeg". This parameter allows you to choose the most suitable file format for your needs, whether it be for web use, printing, or further editing.

FLUX 1.0 [depth] Finetuned Output Parameters:

image

The image output parameter provides the final generated image based on the input parameters and the finetuning model applied. This image reflects the depth and perspective enhancements made possible by the node, resulting in a visually compelling and realistic output. The generated image can be used for a variety of creative projects, including digital art, design, and visualization.

FLUX 1.0 [depth] Finetuned Usage Tips:

• To achieve the best results, provide a high-quality control image that closely matches the desired depth and perspective of your final output. This will help the node generate images that are more aligned with your vision.
• Experiment with different finetune_strength values to find the optimal balance between the original model's capabilities and the enhancements provided by the finetuning model. This can help you achieve the desired level of detail and style in your images.

FLUX 1.0 [depth] Finetuned Common Errors and Solutions:

Error: "Invalid control image format"

• Explanation: This error occurs when the control image provided is not in a supported format.
• Solution: Ensure that the control image is in a valid image format, such as JPEG or PNG, and try again.

Error: "Finetune ID not recognized"

• Explanation: This error indicates that the specified finetune_id does not match any available finetuning models.
• Solution: Double-check the finetune_id for any typos or errors, and ensure that it corresponds to a valid finetuning model.

Error: "Guidance value out of range"

• Explanation: This error occurs when the guidance parameter is set outside the allowed range.
• Solution: Adjust the guidance value to be within the specified range of 1.0 to 100, and try again.