API
If you're looking for an API, you can choose from your desired programming language.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
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')
# Use this function to convert a list of image URLs to base64
def image_urls_to_base64(image_urls):
return [image_url_to_base64(url) for url in image_urls]
api_key = "YOUR_API_KEY"
url = "https://api.segmind.com/v1/kling-bloombloom"
# Request payload
data = {
"image": image_url_to_base64("https://segmind-resources.s3.amazonaws.com/output/183fe2c8-fcdd-4b58-9308-e3c0c8390961-802185687995670354.png"), # Or use image_file_to_base64("IMAGE_PATH")
"mode": "pro",
"duration": 5
}
headers = {'x-api-key': api_key}
response = requests.post(url, json=data, headers=headers)
print(response.content) # The response is the generated imageAttributes
Image
Mode of generation
Allowed values:
Duration of the animation in seconds
Allowed values:
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 Potential of Kling AI for Dynamic Content Creation
For developers and creators, Kling AI offers a powerful toolset for producing high-quality visual content with enhanced realism and detail. Leveraging deep learning techniques and diffusion-based architectures, Kling AI excels in transforming text and image inputs into dynamic video content. This capability is particularly beneficial for digital storytellers and animators seeking realistic human movement and emotive facial animations through its 3D face and body reconstruction technology. Developers can integrate Kling AI into workflows through Segmind’s SDKs and documentation to implement these advanced features in custom applications.
Creators can benefit from Kling AI’s intuitive interface and extended video generation capabilities, which now support projects up to three minutes long. This feature is ideal for crafting narrative-filled videos, marketing material, and educational simulations. Further enhancing its utility is the AI-powered sound generation, enabling seamless audio integration to enhance viewer engagement and storytelling depth.
The Spatiotemporal Joint Attention Mechanism offers a breakthrough in achieving consistent and lifelike motion across video productions, ensuring that moving objects maintain realistic paths and lighting. To make the most of Kling AI, creators should focus on detailed text prompts and reference images, iteratively refining storyboard inputs to guide AI outputs effectively.
For executives aiming to leverage generative AI for competitive advantage, Kling AI presents a compelling case for ROI through accelerated content production and enhanced creative output. Its sophisticated modeling and production tools streamline workflows, allowing businesses to innovate and create premium visual content that sets them apart in the digital landscape.
Other Popular Models
sdxl-img2img
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
sd1.5-majicmix
The most versatile photorealistic model that blends various models to achieve the amazing realistic images.
codeformer
CodeFormer is a robust face restoration algorithm for old photos or AI-generated faces.
sd2.1-faceswapper
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
