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import requests
api_key = "YOUR_API_KEY"
url = "https://api.segmind.com/v1/flux-depth-pro"
# Prepare data and files
data = {}
files = {}
data['seed'] = 96522
data['steps'] = 40
data['prompt'] = "American man, smiling, waving, eyeglasses, casual clothing, sitting at desk, laptop, home office, indoor, daylight, modern decor, house plants, bookshelf, natural lighting"
data['guidance'] = 7
# 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.
Flux Depth Pro is an advanced AI model developed by Black Forest Labs, designed to enhance image generation by integrating depth information. This model leverages depth maps to provide a three-dimensional perspective, resulting in images with improved realism and spatial accuracy.
Depth Map Integration: Utilizes depth maps to inform the generation process, ensuring that images accurately represent spatial relationships and depth cues.
Enhanced Realism: By incorporating depth information, the model produces images with a more lifelike appearance, capturing the nuances of light and shadow.
Versatile Application: Suitable for various creative projects, including digital art, virtual reality content, and architectural visualization, where depth perception is crucial.
Improved Visual Quality: The integration of depth maps leads to images with better-defined spatial relationships, enhancing the overall visual quality.
Consistency in Output: Ensures that generated images consistently exhibit accurate depth cues, maintaining a high standard across different projects.
Efficiency in Workflow: Streamlines the image generation process by automatically incorporating depth information, reducing the need for manual adjustments.
Digital Art Creation: Assists artists in producing detailed and realistic images, enhancing the artistic quality of digital artworks.
Virtual Reality Content: Enables the creation of immersive VR experiences by generating images with accurate depth perception.
Architectural Visualization: Facilitates the creation of realistic architectural renderings, accurately representing spatial relationships and depth.
By incorporating depth information, Flux Depth Pro offers a powerful tool for professionals seeking to generate images with enhanced realism and spatial accuracy.
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
Turn a face into 3D, emoji, pixel art, video game, claymation or toy
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
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