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import requests
api_key = "YOUR_API_KEY"
url = "https://api.segmind.com/v1/flux-canny-pro"
# Prepare data and files
data = {}
files = {}
data['seed'] = 965778
data['steps'] = 40
data['prompt'] = "photo of a car on a street"
data['guidance'] = 30
# For parameter "control_image", you can send a raw file or a URI:
# files['control_image'] = open('IMAGE_PATH', 'rb') # To send a file
# data['control_image'] = 'IMAGE_URI' # To send a URI
data['output_format'] = "jpg"
data['safety_tolerance'] = 2
data['prompt_upsampling'] = 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
Number of diffusion steps. Higher values yield finer details but increase processing time.
min : 15,
max : 50
Text prompt for image generation
Controls the balance between adherence to the text as well as image prompt and image quality/diversity. Higher values make the output more closely match the prompt but may reduce overall image quality. Lower values allow for more creative freedom but might produce results less relevant to the prompt.
min : 1,
max : 50
Image to use as control input. Must be jpeg, png, or webp.
Format of the output images.
Allowed values:
Safety tolerance, 1 is most strict and 6 is most permissive
min : 1,
max : 6
Automatically modify the prompt for more creative generation
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 Canny Pro is an advanced AI model developed by Black Forest Labs, designed to enhance image generation by integrating edge detection techniques. This model leverages the Canny edge detection algorithm to identify and emphasize the structural outlines within images, resulting in outputs with enhanced clarity and definition.
Edge Detection Integration: Utilizes the Canny algorithm to detect edges, ensuring that generated images maintain sharp and well-defined structures.
Enhanced Image Clarity: By focusing on prominent edges, the model produces images with improved clarity and detail, making them more visually appealing.
Versatile Application: Suitable for various creative projects, including digital art, graphic design, and content creation, where precise image details are crucial.
Improved Visual Quality: The integration of edge detection leads to images with better-defined features, enhancing the overall visual quality.
Consistency in Output: Ensures that generated images consistently exhibit clear and sharp edges, maintaining a high standard across different projects.
Efficiency in Workflow: Streamlines the image generation process by automatically emphasizing structural details, reducing the need for manual adjustments.
Digital Art Creation: Assists artists in producing detailed and sharp images, enhancing the artistic quality of digital artworks.
Graphic Design: Enables designers to create visuals with clear outlines, improving the effectiveness of design elements.
Content Generation: Facilitates the creation of high-quality images for various content needs, including marketing materials and social media posts.
By incorporating the Canny edge detection algorithm, Flux Canny Pro offers a powerful tool for professionals seeking to generate images with enhanced structural clarity and detail.
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
CodeFormer is a robust face restoration algorithm for old photos or AI-generated faces.
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