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Blueberry3ssfinal Image Generation

Blueberry3ssfinal is an advanced AI model designed for high-quality image generation and editing. Let's explore what this AI model can do for you!

Platform: Replicate
Text-to-Image GenerationImage InpaintingLoRA IntegrationCreative Design
92 runs
H100
License Check Required

🚀Function Overview

This AI model generates or modifies images using text prompts, reference images, and masks. Discover how this AI model can transform your workflow!

Key Features

  • Creates images from textual prompts with trigger words
  • Modifies existing images via inpainting or image-to-image translation
  • Supports LoRA weights from multiple sources for specialized styles
  • Adjustable output dimensions, quality, and generation parameters
  • Optimized speed modes for faster processing
  • Safety checker for generated content

Use Cases

  • Marketing visuals for products (e.g., beverage packaging)
  • Creative digital artwork generation
  • Photo editing and enhancement
  • Concept art development
  • Advertising campaign imagery

⚙️Input Parameters

prompt

string

Prompt for generated image. If you include the `trigger_word` used in the training process you are more likely to activate the trained object, style, or concept in the resulting image.

image

string

Input image for image to image or inpainting mode. If provided, aspect_ratio, width, and height inputs are ignored.

mask

string

Image mask for image inpainting mode. If provided, aspect_ratio, width, and height inputs are ignored.

aspect_ratio

string

Aspect ratio for the generated image. If custom is selected, uses height and width below & will run in bf16 mode

height

integer

Height of generated image. Only works if `aspect_ratio` is set to custom. Will be rounded to nearest multiple of 16. Incompatible with fast generation

width

integer

Width of generated image. Only works if `aspect_ratio` is set to custom. Will be rounded to nearest multiple of 16. Incompatible with fast generation

prompt_strength

number

Prompt strength when using img2img. 1.0 corresponds to full destruction of information in image

model

string

Which model to run inference with. The dev model performs best with around 28 inference steps but the schnell model only needs 4 steps.

num_outputs

integer

Number of outputs to generate

num_inference_steps

integer

Number of denoising steps. More steps can give more detailed images, but take longer.

guidance_scale

number

Guidance scale for the diffusion process. Lower values can give more realistic images. Good values to try are 2, 2.5, 3 and 3.5

seed

integer

Random seed. Set for reproducible generation

output_format

string

Format of the output images

output_quality

integer

Quality when saving the output images, from 0 to 100. 100 is best quality, 0 is lowest quality. Not relevant for .png outputs

disable_safety_checker

boolean

Disable safety checker for generated images.

go_fast

boolean

Run faster predictions with model optimized for speed (currently fp8 quantized); disable to run in original bf16

megapixels

string

Approximate number of megapixels for generated image

lora_scale

number

Determines how strongly the main LoRA should be applied. Sane results between 0 and 1 for base inference. For go_fast we apply a 1.5x multiplier to this value; we've generally seen good performance when scaling the base value by that amount. You may still need to experiment to find the best value for your particular lora.

extra_lora

string

Load LoRA weights. Supports Replicate models in the format <owner>/<username> or <owner>/<username>/<version>, HuggingFace URLs in the format huggingface.co/<owner>/<model-name>, CivitAI URLs in the format civitai.com/models/<id>[/<model-name>], or arbitrary .safetensors URLs from the Internet. For example, 'fofr/flux-pixar-cars'

extra_lora_scale

number

Determines how strongly the extra LoRA should be applied. Sane results between 0 and 1 for base inference. For go_fast we apply a 1.5x multiplier to this value; we've generally seen good performance when scaling the base value by that amount. You may still need to experiment to find the best value for your particular lora.

💡Usage Examples

Example 1

Input Parameters

{
  "model": "dev",
  "prompt": "Hyper-Realistic Summer Explosion – Blueberry & Vanilla Beer Can\n\nA vibrant, hyper-realistic product shot of a craft beer can erupting in a dynamic explosion of fresh blueberry juice and delicate vanilla flowers, capturing the essence of summer freshness. This image must evoke refreshing, bright, and tropical energy, making the viewer feel the coolness of the beer on a hot summer day.\n\nComposition & Scene Dynamics:\n\t•\tThe Beer Can:\n\t•\tThe main subject, a sleek, ice-cold aluminum craft beer can, positioned centrally or slightly tilted, appearing freshly cracked open, releasing an aromatic burst of flavor.\n\t•\tWater droplets of condensation cling to the can, glistening under the warm summer sunlight.\n\t•\tThe label is sharp and clear, blending harmoniously with the surrounding splash of colors, reinforcing the flavor experience of blueberry and vanilla.\n\t•\tThe Blueberry Juice Explosion:\n\t•\tA burst of rich, deep indigo and violet blueberry juice, frozen mid-air in a high-speed splash effect, with droplets suspended as if caught in motion.\n\t•\tThe juice appears thick and glossy, reflecting light in a way that makes it tangible and luscious, with tiny bits of blueberry pulp visible, reinforcing its natural quality.\n\t•\tSome whole blueberries, plump and fresh, are scattered within the splash, adding movement and depth.\n\t•\tThe Vanilla Flowers:\n\t•\tSoft, creamy-white vanilla orchid flowers subtly woven into the composition, appearing as if they are being carried by the juice explosion.\n\t•\tSome petals have tiny specks of vanilla bean dust, enhancing the depth and realism of the vanilla essence.\n\t•\tThe flowers appear weightless, almost floating, adding a sense of elegance and fragrance to the image.\n\nLighting & Mood:\n\t•\tWarm, golden sunlight filtering through, creating a backlit glow that enhances the translucency of the juice splash and highlights the natural textures of the ingredients.\n\t•\tSoft lens flares and gentle sun rays reinforce the summer atmosphere, making the image feel warm and inviting.\n\t•\tA slight breeze effect, with fine mist and condensation drifting subtly in the air, reinforcing refreshment.\n\nColor Palette & Realism:\n\t•\tCool, deep blues and purples of the blueberries contrast beautifully with the warm golden sunlight and creamy whites of the vanilla flowers.\n\t•\tHigh-definition textures:\n\t•\tThe aluminum can should have a realistic reflective surface, with subtle highlights capturing the freshness.\n\t•\tThe juice splash should feel dynamic and weighty, not just a blur but an organic motion of thick liquid suspended in air.\n\t•\tThe vanilla flowers should be soft, natural, and delicate, with a subtle glow from the sunlight.\n\nFinal Effect & Emotional Impact:\n\nThis image should immediately transport the viewer to a bright summer afternoon, evoking the feeling of biting into a fresh blueberry and inhaling the sweet, floral aroma of vanilla. It must feel ultra-refreshing, dynamic, and premium, making the beer can appear as a must-have summer drink.",
  "go_fast": false,
  "lora_scale": 1,
  "megapixels": "1",
  "num_outputs": 1,
  "aspect_ratio": "1:1",
  "output_format": "webp",
  "guidance_scale": 3,
  "output_quality": 80,
  "prompt_strength": 0.8,
  "extra_lora_scale": 1,
  "num_inference_steps": 28
}

Output Results

https://replicate.delivery/xezq/bWmkWzCAWPJ3OVNabQEn7l0KRFfRZ3jxtECU3hr7L1ZqUEOKA/out-0.webp