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API Calls and Credits

Ximilar billing is based on the number of API method calls. To differentiate between different complexity of the methods, every api call corresponds to a certain number of credits. New Ximilar users have some free monthly credits to be used for testing. Then, there are several pricing plans with different amount of available credits and other limits. You can see the number of credits you have used in current month in the Ximilar app dashboard.

Credits in general

In general, each API call that sends (uploads) an image to Ximilar API endpoint costs one credit. All other methods are for free and some special complex methods that combine several functions can cost more than one credit.

Every record counts!

Some methods allow to send more than one image at once via records field. For the purpose of billing, every record counts as single request (typically as one credit). However processing batch (multiple) records in one request is faster than sending multiple requests with one record.

Credits in detail

Here is a list of all API methods and their credit value. We show only methods that are not for free (all other are).

Custom Image Recognition services

This category covers these services: Image categorization & tagging, Object detection, and Flows.

Path Description Number of credits
/recognition/v2/classify Classifying (categorization or tagging) an image by your custom model 1.0
/recognition/v2/training-image Uploading a training image to custom image recognition 1.0
/detection/v2/detect Predicting bounding boxes of some features/objects on the image 5.0
/flows/v2/process Chaining individual categorization, tagging and detection models by your "flow" 0.0

Ready-to-use Image Recognition services

Fashion and Home Decor tagging

Path Description Number of credits
/tagging/fashion/v2/tags Get category and tags for product photo with apparel, footwear, bags, etc. 15.0
/tagging/fashion/v2/detect Detect fashion objects 5.0
/tagging/fashion/v2/detect_tags Detect fashion objects and extract category and tags for largest or specified object 20.0
/tagging/fashion/v2/detect_tags_all Detect fashion objects and extract category and tags for all objects 60.0
/tagging/fashion/v2/meta Get meta information about fashion product photos (scene, background, angle, etc.) 3.0
/tagging/homedecor/v2/tags Analyze tags for home decor products 10.0

Photo Tagging

Path Description Number of credits
/tagging/generic/v2/tags Get tags for a generic photo 1.0

Dominant Colors

Path Description Number of credits
/dom_colors/generic/v2/dominantcolor Get dominant colors colors of generic photos 1.0
/dom_colors/product/v2/dominantcolor Get dominant colors colors of product photos (ignore background) 1.0

Face Detection

Path Description Number of credits
/face/v2/detect Detect all faces in an image and get their bounding boxes 5.0

Visual Search services

Photo & Product Similarity

Prefixes

https://api.ximilar.com/similarity/photos/v2/<method> https://api.ximilar.com/similarity/products/v2/<method> https://api.ximilar.com/<your_private_cloud_service>/v2/<method>

Path Description Number of credits
/*/v2/insert Insert an image into your collection 1.0
/*/v2/visualKNN Find visually similar images to a given image from the collection 0.25 or 1.0
/*/v2/visualTagsKNN Find images that are similar based on combination of visual and tags similarity 0.25 or 1.0
/*/v2/visualKNNMulti Find visually similar images from the collection to a given list of images 0.25 or 1.0
/*/v2/visualTagsKNNMulti Find images that are similar to a given list of images based on combination of visual and tags similarity 0.25 or 1.0
/*/v2/nearDuplicates finds those images in the collection that are the same or very similar to the query image 0.25 or 1.0
/*/v2/range find visually similar images to a given image from the collection up to a certain query radius 0.25 or 1.0
sync process by Ximilar Ximilar can run regular sync process to update a similarity collection from your database export 3000

The credit price of all the search queries is * 0.25 in case the query object(s) is specified by field _id; this means that the query object is already in the index and it's just read from the, * 1.0 in case the query is external - specified by _url or _base64; in this case, the image must be preprocessed on GPU, which is more costly.

URL prefix:

https://api.ximilar.com/similarity/fashion/

Path Description Number of credits
/v2/insert Insert an image into your collection & get its fashion tags 16.0
/v2/visualTagsKNN Detect clothing on the image; get fashion tags + similar products to the largest detected object 16.0
/v2/visualTagsKNN Get fashion tags + similar products to a selected detected object 16.0
/v2/visualTagsKNN Given a product from the collection (specified by _id), get similar products 1.0

Prefixes

https://api.ximilar.com/similarity/custom/v2/<method>

The credit values of all API requests are 4x the credit values of operations specified in Photo & Product Similarity.

Image Matching

Path Description Number of credits
/image_matching/v2/visual_hash Get visual hash(es) for given image 1.0
/image_matching/v2/remove_duplicates Identify (near-)duplicate images 1.0 (per image)
/image_matching/v2/rank_images Rank images by hash-based similarity to the query image 1.0 (per image)
/image_matching/v2/<collection_method> You can search for matching images in your collection see photo similarity

Image Tool services

Remove Background

Detect foreground object(s) are replace the rest by transparent layer.

Path Description Number of credits
/removebg/precise/removebg Remove background by a slower but precise method 50.0
/removebg/fast/removebg Remove background by a faster and still quite precise method 30.0

Image Upscaler

Take a photo and create a new version of the photo that has higher resolution.

Path Description Number of credits
/upscaler/2x/upscale Increase the photo resolution 2x 50.0
/upscaler/4x/upscale Increase the photo resolution 4x 75.0
/upscaler/8x/upscale Increase the photo resolution 8x 100.0