> For clean Markdown of any page, append .md to the page URL. > For a complete documentation index, see https://docs.amniscient.com/llms.txt. > For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.amniscient.com/_mcp/server. # Load a Model & Detect an Object POST https://api.amniscient.com/inference/detect-with-model/{model_id} Content-Type: multipart/form-data Initializes a model for inference and detects an object within an uploaded image file within a single API call. This eliminates the need to load a model before running detection. Reference: https://docs.amniscient.com/api/api-reference/detect-with-model ## Request ### Path parameters - `model_id` (string, required) — The model ID of an active and trained AI model within your organization. ### Headers - `x-api-key` (string, required) — Your organization's active API Key. ### Body (multipart/form-data) This endpoint expects a multipart form containing a file. - `organization_id` (string, required) — Your organization's unique identifier. - `file` (file, required) — An image file you'd like to run detection on. ## Response ### 200 200 - Detection successful - `xywh` (list of DetectionResponseXywhItems, optional) — An array of information related to the object detected. If an object was not detected, this array will be empty. - `detection_found` (boolean, optional) — A boolean value denoting whether an object was successfully detected in the image file provided. - `inference_id` (string, optional) — A unique identifier for the results of a successful inference call. ## Errors ### 400 Bad Request Error Bad Request - `detail` (string, optional) — A message describing the successful action or error state. ### 404 Not Found Error Model Not Found - `detail` (string, optional) — A message describing the successful action or error state. ## Types ### DetectionResponseXywhItems - `id` (string, optional) — The detection item id of the object detected. This will match the detection item id in the library for this object. - `confidence` (double, optional) — A value between 0 and 1 rating how confident the object detection output is based on the model and image provided. - `x` (double, optional) — A value between 0 and 1 denoting the x coordinate of the detected object. - `y` (double, optional) — A value between 0 and 1 denoting the y coordinate of the detected object. - `width` (double, optional) — A value between 0 and 1 describing the width of the detected object. - `height` (double, optional) — A value between 0 and 1 describing the height of the detected object. - `tag` (map from string to string, optional) — A map of attributes associated with the detected object. These attributes will match the attributes within the library for this object. ## Examples **Request** ```json { "file": "", "organization_id": "string" } ``` **Response** ```json { "xywh": [ { "id": "xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx", "confidence": 0.95, "x": 0.5, "y": 0.7, "width": 0.4, "height": 0.5, "tag": { "tag_key": "tag_value" } } ], "detection_found": true, "inference_id": "xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" } ``` **SDK Code** ```python Successful Detection import requests url = "https://api.amniscient.com/inference/detect-with-model/model_id" files = { "file": "open('string', 'rb')" } payload = { "organization_id": "string" } headers = {"x-api-key": "x-api-key"} response = requests.post(url, data=payload, files=files, headers=headers) print(response.json()) ``` ```javascript Successful Detection const url = 'https://api.amniscient.com/inference/detect-with-model/model_id'; const form = new FormData(); form.append('file', 'string'); form.append('organization_id', 'string'); const options = {method: 'POST', headers: {'x-api-key': 'x-api-key'}}; options.body = form; try { const response = await fetch(url, options); const data = await response.json(); console.log(data); } catch (error) { console.error(error); } ``` ```go Successful Detection package main import ( "fmt" "strings" "net/http" "io" ) func main() { url := "https://api.amniscient.com/inference/detect-with-model/model_id" payload := strings.NewReader("-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"file\"; filename=\"string\"\r\nContent-Type: application/octet-stream\r\n\r\n\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"organization_id\"\r\n\r\nstring\r\n-----011000010111000001101001--\r\n") req, _ := http.NewRequest("POST", url, payload) req.Header.Add("x-api-key", "x-api-key") res, _ := http.DefaultClient.Do(req) defer res.Body.Close() body, _ := io.ReadAll(res.Body) fmt.Println(res) fmt.Println(string(body)) } ``` ```ruby Successful Detection require 'uri' require 'net/http' url = URI("https://api.amniscient.com/inference/detect-with-model/model_id") http = Net::HTTP.new(url.host, url.port) http.use_ssl = true request = Net::HTTP::Post.new(url) request["x-api-key"] = 'x-api-key' request.body = "-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"file\"; filename=\"string\"\r\nContent-Type: application/octet-stream\r\n\r\n\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"organization_id\"\r\n\r\nstring\r\n-----011000010111000001101001--\r\n" response = http.request(request) puts response.read_body ``` ```java Successful Detection import com.mashape.unirest.http.HttpResponse; import com.mashape.unirest.http.Unirest; HttpResponse response = Unirest.post("https://api.amniscient.com/inference/detect-with-model/model_id") .header("x-api-key", "x-api-key") .body("-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"file\"; filename=\"string\"\r\nContent-Type: application/octet-stream\r\n\r\n\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"organization_id\"\r\n\r\nstring\r\n-----011000010111000001101001--\r\n") .asString(); ``` ```php Successful Detection request('POST', 'https://api.amniscient.com/inference/detect-with-model/model_id', [ 'multipart' => [ [ 'name' => 'file', 'filename' => 'string', 'contents' => null ], [ 'name' => 'organization_id', 'contents' => 'string' ] ] 'headers' => [ 'x-api-key' => 'x-api-key', ], ]); echo $response->getBody(); ``` ```csharp Successful Detection using RestSharp; var client = new RestClient("https://api.amniscient.com/inference/detect-with-model/model_id"); var request = new RestRequest(Method.POST); request.AddHeader("x-api-key", "x-api-key"); request.AddParameter("undefined", "-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"file\"; filename=\"string\"\r\nContent-Type: application/octet-stream\r\n\r\n\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"organization_id\"\r\n\r\nstring\r\n-----011000010111000001101001--\r\n", ParameterType.RequestBody); IRestResponse response = client.Execute(request); ``` ```swift Successful Detection import Foundation let headers = ["x-api-key": "x-api-key"] let parameters = [ [ "name": "file", "fileName": "string" ], [ "name": "organization_id", "value": "string" ] ] let boundary = "---011000010111000001101001" var body = "" var error: NSError? = nil for param in parameters { let paramName = param["name"]! body += "--\(boundary)\r\n" body += "Content-Disposition:form-data; name=\"\(paramName)\"" if let filename = param["fileName"] { let contentType = param["content-type"]! let fileContent = String(contentsOfFile: filename, encoding: String.Encoding.utf8) if (error != nil) { print(error as Any) } body += "; filename=\"\(filename)\"\r\n" body += "Content-Type: \(contentType)\r\n\r\n" body += fileContent } else if let paramValue = param["value"] { body += "\r\n\r\n\(paramValue)" } } let request = NSMutableURLRequest(url: NSURL(string: "https://api.amniscient.com/inference/detect-with-model/model_id")! as URL, cachePolicy: .useProtocolCachePolicy, timeoutInterval: 10.0) request.httpMethod = "POST" request.allHTTPHeaderFields = headers request.httpBody = postData as Data let session = URLSession.shared let dataTask = session.dataTask(with: request as URLRequest, completionHandler: { (data, response, error) -> Void in if (error != nil) { print(error as Any) } else { let httpResponse = response as? HTTPURLResponse print(httpResponse) } }) dataTask.resume() ```