Pebblely Fashion API Documentation
Sign up for a Pebblely Fashion API accountPebblely provides an API for individuals and companies that are considering processing large volumes of on-model fashion photos.
Sign up here to get an access token and 20 free credits.
Authentication
All Pebblely API queries require a valid access token, which you can obtain by signing up for API access.
Include your token as a X-Pebblely-Access-Token header on all API queries.
CORS
At the moment, accessing the API via client-side will return a CORS error. Instead, you should access the API via server-side instead, which should resolve the CORS issue, as well as keep your API key secure.
Endpoints
All Pebblely API endpoints follow the following format:
https://fashion-api.pebblely.com/api_v1/{endpoint}By default, all API keys are rate-limited at 1 query per second. The latency for each endpoint varies, see the specific endpoint for more details. Contact us if you have specific requirements around rate-limiting and latencies.
Each API query consumes 1 credit.
Note that there is a maximum file size of 5MB for all images uploaded.
Get Credits
GET /utils/credits
Retrieves the number of remaining credits for an account.
Response
Response: # "credits" - Number of credits remaining credits: intExample
import requestsendpoint_url = "https://fashion-api.pebblely.com/api_v1/utils/credits"response = requests.get( endpoint_url, headers={ "X-Pebblely-Access-Token": "<YOUR ACCESS TOKEN>", },)remaining_credits = response.json()["credits"]Get Themes
GET /utils/themes
Retrieves the list of themes and their respective thumbnails.
Response
Response: # List of Theme objects, where each object comprises the following keys and values # "label": str - Label of theme # "thumbnail": str - Sample thumbnail URL List[Dict[str, str]]Example
import requestsendpoint_url = "https://fashion-api.pebblely.com/api_v1/utils/themes"response = requests.get( endpoint_url)themes = response.json()print(len(themes)) # Should print number of themesprint(themes[0]["label"]) # Should print "Streets"Create Background
POST /generate/virtual_pose
Use the virtual_pose endpoint with a photo of a top to create a photo of a model posing in your top.
This endpoint takes ~20 seconds for a 1024 by 1024 input image.
Request body
RequestBody: # "cloth_image" - A photo of the top apparel, see example below cloth_image: str = "" # "theme" - One of ["Streets", "Beach", "Rooftop", "Home", "Park", "Cafe"] theme: str = None # "prompt" - Custom prompt describing the model, including gender, ethnicity, age, and/or the background # If a `theme` is supplied, this will be used in addition to the theme prompt: str = "Black hair, beautiful female model posing in jeans" # "negative_prompt" - A list of comma-separated attributes that should be discouraged from the image negative_prompt: str = "" # "background_color" - Hex string representing a color e.g. "#FFFFFF" background_color: str = None # "height", "width" - Height and width of image, up to a maximum of 2048 # If only one dimension is provided, the other dimension defaults to the same value and a square image will be generated height: int = 1024 width: int = 1024Response
Response: # "data" - Base64 representation of the resulting image data: str # "credits" - Number of remaining credits credits: intExample
import base64import ioimport requestsfrom PIL import Imageendpoint_url = "https://fashion-api.pebblely.com/api_v1/generate/virtual_pose"response = requests.post( endpoint_url, headers={ "Content-Type": "application/json", "X-Pebblely-Access-Token": "<YOUR ACCESS TOKEN>", }, json={ "cloth_image": "<YOUR APPAREL IMAGE URL OR BASE64>", "theme": "Streets", "prompt": "Blue hair Japanese female model", })# Process Base64 output and save locally image_b64 = response.json()["data"]image_encoded = image_b64.encode("utf-8")image_bytes = io.BytesIO(base64.b64decode(image_encoded))image = Image.open(image_bytes)image.save("image.jpg")Product Categories
Photography Ideas