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import requests
import base64
# Use this function to convert an image file from the filesystem to base64
def image_file_to_base64(image_path):
with open(image_path, 'rb') as f:
image_data = f.read()
return base64.b64encode(image_data).decode('utf-8')
# Use this function to fetch an image from a URL and convert it to base64
def image_url_to_base64(image_url):
response = requests.get(image_url)
image_data = response.content
return base64.b64encode(image_data).decode('utf-8')
api_key = "YOUR_API_KEY"
url = "https://api.segmind.com/v1/consistent-character-with-pose"
# Request payload
data = {
"base_64": False,
"custom_height": 1024,
"custom_width": 1024,
"face_image": image_url_to_base64("https://segmind-sd-models.s3.amazonaws.com/display_images/ccpose_ip.png"), # Or use image_file_to_base64("IMAGE_PATH")
"output_format": "png",
"pose_image": image_url_to_base64("https://segmind-sd-models.s3.amazonaws.com/display_images/cc_pose_img.png"), # Or use image_file_to_base64("IMAGE_PATH")
"prompt": "A candid photo of a woman , wearing a blue denim shirt and matching jeans. light smile on her face",
"quality": 95,
"samples": 1,
"seed": 2778725438,
"use_input_img_dimension": True
}
headers = {'x-api-key': api_key}
response = requests.post(url, json=data, headers=headers)
print(response.content) # The response is the generated image
Output as base64 encoded string
Custom height for output image
min : 64,
max : 4096
Custom width for output image
min : 64,
max : 4096
Face image
Output image format
Allowed values:
Pose image
Textual description for the image generation
Image quality setting for output
min : 10,
max : 100
Number of images to generate
min : 1,
max : 4
Random seed for generation
Whether to use the input image's dimensions
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.
Consistent Character lets you generate new images of a specific person with remarkable consistency. It takes just one reference image and a text description of the desired pose variations. The magic lies in its ability to seamlessly transfer the person's unique characteristics onto a new body in a different pose. Under the hood of Consistent Character model is a combination of IP Adapter Face and instant id and openpose controlnet for generating image with pose followed by upscaling.
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
Best-in-class clothing virtual try on in the wild
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