If you're looking for an API, you can choose from your desired programming language.
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import requests
api_key = "YOUR_API_KEY"
url = "https://api.segmind.com/v1/flux-redux-schnell"
# Prepare data and files
data = {}
files = {}
data['seed'] = 98566
data['megapixels'] = "1"
data['num_outputs'] = 1
# For parameter "redux_image", you can send a raw file or a URI:
# files['redux_image'] = open('IMAGE_PATH', 'rb') # To send a file
# data['redux_image'] = 'IMAGE_URI' # To send a URI
data['aspect_ratio'] = "1:1"
data['output_format'] = "jpg"
data['output_quality'] = 80
data['num_inference_steps'] = 4
data['disable_safety_checker'] = False
headers = {'x-api-key': api_key}
response = requests.post(url, data=data, files=files, headers=headers)
print(response.content) # The response is the generated image
Random seed. Set for reproducible generation
Approximate number of megapixels for generated image. Use match_input to match the size of the input (with an upper limit of 1440x1440 pixels)
Allowed values:
Number of outputs to generate
min : 1,
max : 4
Input image to condition your output on. This replaces prompt for FLUX.1 Redux models
Aspect ratio for the generated image
Allowed values:
Format of the output images
Allowed values:
Quality when saving the output images, from 0 to 100. 100 is best quality, 0 is lowest quality. Not relevant for .png outputs
min : 0,
max : 100
Number of denoising steps. 4 is recommended, and lower number of steps produce lower quality outputs, faster.
min : 1,
max : 4
Disable safety checker for generated images.
To keep track of your credit usage, you can inspect the response headers of each API call. The x-remaining-credits property will indicate the number of remaining credits in your account. Ensure you monitor this value to avoid any disruptions in your API usage.
Unlock the full potential of generative AI with Segmind. Create stunning visuals and innovative designs with total creative control. Take advantage of powerful development tools to automate processes and models, elevating your creative workflow.
Gain greater control by dividing the creative process into distinct steps, refining each phase.
Customize at various stages, from initial generation to final adjustments, ensuring tailored creative outputs.
Integrate and utilize multiple models simultaneously, producing complex and polished creative results.
Deploy Pixelflows as APIs quickly, without server setup, ensuring scalability and efficiency.
Flux Redux Schnell is a cutting-edge AI model in the FLUX.1 family, specifically engineered for image enhancement and refinement. Unlike traditional models focused on generating images from scratch, Flux Redux Schnell is designed to improve the quality, detail, and aesthetics of existing images while preserving their original composition and intent.
Flux Redux Schnell specializes in image refinement, prioritizing:
Image enhancement: Elevates visual quality.
Detail improvement: Delivers sharper and more defined images.
Quality upscaling: Transforms lower-resolution images into high-resolution versions.
Style preservation: Maintains the artistic essence of the image.
Composition maintenance: Focuses on refinement rather than altering the image's core structure.
Unlike generation-focused models, Flux Redux Schnell is purpose-built for enhancing existing images, making it a vital tool for post-processing workflows.
Flux Redux Schnell offers a robust feature set tailored for exceptional image refinement:
Image quality enhancement: Improves overall visual appeal.
Detail refinement: Ensures intricate textures and clarity.
Texture improvement: Delivers natural and realistic finishes.
Style-consistent enhancement: Preserves artistic intent.
Resolution optimization: Scales images seamlessly.
Artifact reduction: Removes noise and distortions.
Natural detail addition: Enriches image authenticity.
Flux Redux Schnell is a versatile tool suitable for various scenarios, including:
Enhancing low-quality images: Transforms blurry or pixelated visuals.
Improving AI-generated content: Refines outputs from other generative models.
Refining artistic works: Perfects digital artwork and illustrations.
Upscaling images: Increases resolution without compromising quality.
Adding natural details: Creates realistic enhancements in images.
Professional photo enhancement: Provides polished results for photographers and editors.
Content post-processing: Ideal for marketing, design, and creative industries.
SDXL Img2Img is used for text-guided image-to-image translation. This model uses the weights from Stable Diffusion to generate new images from an input image using StableDiffusionImg2ImgPipeline from diffusers
Take a picture/gif and replace the face in it with a face of your choice. You only need one image of the desired face. No dataset, no training
This model is capable of generating photo-realistic images given any text input, with the extra capability of inpainting the pictures by using a mask
Take a picture/gif and replace the face in it with a face of your choice. You only need one image of the desired face. No dataset, no training