This Furniture & Household Item Recognition API provides an accurate identification of furniture & household items with advanced intelligent detection, categorization, and counting technologies.
This solution offers AI-driven image analysis, ideal for identifying household items in photos. It streamlines inventory management for interior design, real estate, retail, and enhances service efficiency for moving companies.
This API is created by API4AI. We build our APIs on a completely cloud technology stack which provides full operability, scalability and stable uptime. Our sole goal is to create out-of-the-box self-contained AI solutions that can easily be integrated into any application with just a few simple steps.
METHOD | URL | DESCRIPTION |
---|---|---|
GET | https://furniture-and-household-items.p.rapidapi.com/v1/version |
Get a service version. |
POST | https://furniture-and-household-items.p.rapidapi.com/v1/results |
Perform image analysis and get results. |
Returns an actual version of the service in format vX.Y.Z
where X is the version of API.
PROPERTY | DESCRIPTION |
---|---|
Endpoint | https://furniture-and-household-items.p.rapidapi.com/v1/version |
Method | GET |
Query parameters | – |
POST parameters | – |
Example
curl -X 'GET' 'https://furniture-and-household-items.p.rapidapi.com/v1/version' \
-H 'X-RapidAPI-Key: ...'
v1.3.0
Performs actual image analysis and responds with results.
PROPERTY | DESCRIPTION |
---|---|
Endpoint | https://furniture-and-household-items.p.rapidapi.com/v1/results |
Method | POST |
POST parameters | image , url |
Passing image
Image can be passed by posting regular “multipart form data” in two alternative ways:
image
fieldurl
fieldImage must be a regular JPEG or PNG image (with or without transparency) or PDF file.
Usually such images have extensions: .jpg
, .jpeg
, .png
, .pdf
. In case of PDF
each page will be converted to PNG image and processed separately (note: you will be charged for each page!).
The service checks input file by MIME type and accepts the following types:
image/jpeg
image/png
application/pdf
The size of the image file must be less than 16Mb
.
The maximum allowed resolution is 4096x4096
.
Response schema
For responses with 200
HTTP code the type of response is JSON object with the following schema:
{
"results": [
{
"status": {
"code": ...,
"message": ...
},
"name": ...,
"md5": ...,
"page": ...,
"width": ...,
"height": ...,
"entities": [
{
"kind": "mapping",
"name": "household-stuff",
"mapping": {
...
}
}
]
}
]
}
Primary fields:
Name | Type | Description |
---|---|---|
results[].status.code |
string |
Status code of image processing: ok or failure . |
results[].status.message |
string |
Human readable explanation for status of image processing. |
results[].name |
string |
Original image name passed in request (e.g. furniture.jpg ). |
results[].md5 |
string |
MD5 sum of original image passed in request. |
results[].page |
int |
Optinal page number (presented for multipage inputs only). |
results[].width |
int |
Optinal image width (presented for valid inputs only). |
results[].height |
int |
Optinal image height (presented for valid inputs only). |
results[].entities[].mapping |
object |
Detected items and count. |
Some details:
"item": count
pairs, where "item"
is item name and count
is count of items of this kind.curl -X 'POST' 'https://furniture-and-household-items.p.rapidapi.com/v1/results' \
-H 'X-RapidAPI-Key: ...' \
-F 'image=@furniture.jpg'
{
"results": [
{
"status": {
"code": "ok",
"message": "Success"
},
"name": "furniture.jpg",
"md5": "a447c0aa2b2b89aa6ffb488317c0ab1e",
"entities": [
{
"kind": "mapping",
"name": "household-stuff",
"mapping": {
"American fridge": 1,
"Bar stool": 2,
"Bottle": 3,
"Extractor hood": 1,
"Large plant": 1,
"Oven": 1,
"Stove": 1,
"Table": 1,
"Table-top fridge": 1
}
}
]
}
]
}
When a client sends an image that can not be processed for some reason(s), the service responds with 200
code and returns a JSON object in the same format as the format for successful analysis. In this case, the results[].status.code
will have failure
value and results[].status.message
will contain relevant explanation.
Example of possible reasons for the issue:
Example response for image with unsupported MIME type:
{
"results": [
{
"status": {
"code": "failure",
"message": "Can not load image."
},
"name": "file.txt",
"md5": "d41d8cd98f00b204e9800998ecf8427e",
"entities": []
}
]
}
Request size is limited by approximately 32Mb
.
When a client sends a request that exceeds this limit, the service responds with 413
code.
The typical reason for exceeding this limit is an overly large image.
Taking into account additional HTTP overhead, we strongly recommend not passing image files of size more than 16Mb
.
Example response for overly big image:
Error: Request Entity Too Large
Your client issued a request that was too large.
When a client sends a request without an image, the service responds with 422
code and returns a JSON object.
Example response for request with missing image:
{"detail":"Missing image or url field."}
Post a file content as a “multipart form data” field named image
.
curl -X 'POST' 'https://furniture-and-household-items.p.rapidapi.com/v1/results' \
-H 'X-RapidAPI-Key: ...' \
-F 'image=@furniture.jpg'
Post a URL to file as a “multipart form data” field named url
.
curl -X 'POST' 'https://furniture-and-household-items.p.rapidapi.com/v1/results' \
-H 'X-RapidAPI-Key: ...' \
-F 'url=https://storage.googleapis.com/api4ai-static/samples/household-stuff-1.jpg'
Code examples in Python, C#, JavaScript, Swift and other popular programming languages: https://gitlab.com/api4ai/examples/household-stuff-recognition
Feel free to contact API4AI team if you have any questions.