Set target constraints
curl --request POST \
--url https://studio.edgeimpulse.com/v1/api/{projectId}/target-constraints \
--header 'Content-Type: application/json' \
--header 'x-api-key: <api-key>' \
--data '
{
"targetDevices": [
{
"processors": [
{
"part": "<string>",
"format": "low-end MCU",
"architecture": "Cortex-M",
"specificArchitecture": "Cortex-M0+",
"accelerator": "Arm Cortex-U55",
"fpu": true,
"clockRateMhz": {
"minimum": 123,
"maximum": 123
},
"memory": {
"ram": {
"fastBytes": {
"minimum": 123,
"maximum": 123
},
"slowBytes": {
"minimum": 123,
"maximum": 123
}
},
"rom": {
"fastBytes": {
"minimum": 123,
"maximum": 123
},
"slowBytes": {
"minimum": 123,
"maximum": 123
}
}
}
}
],
"board": "<string>",
"name": "<string>",
"latencyDevice": "cortex-m4f-80mhz"
}
],
"applicationBudgets": [
{
"latencyPerInferenceMs": {
"minimum": 123,
"maximum": 123
},
"energyPerInferenceJoules": {
"minimum": 123,
"maximum": 123
},
"memoryOverhead": {
"ram": {
"fastBytes": {
"minimum": 123,
"maximum": 123
},
"slowBytes": {
"minimum": 123,
"maximum": 123
}
},
"rom": {
"fastBytes": {
"minimum": 123,
"maximum": 123
},
"slowBytes": {
"minimum": 123,
"maximum": 123
}
}
}
}
]
}
'import requests
url = "https://studio.edgeimpulse.com/v1/api/{projectId}/target-constraints"
payload = {
"targetDevices": [
{
"processors": [
{
"part": "<string>",
"format": "low-end MCU",
"architecture": "Cortex-M",
"specificArchitecture": "Cortex-M0+",
"accelerator": "Arm Cortex-U55",
"fpu": True,
"clockRateMhz": {
"minimum": 123,
"maximum": 123
},
"memory": {
"ram": {
"fastBytes": {
"minimum": 123,
"maximum": 123
},
"slowBytes": {
"minimum": 123,
"maximum": 123
}
},
"rom": {
"fastBytes": {
"minimum": 123,
"maximum": 123
},
"slowBytes": {
"minimum": 123,
"maximum": 123
}
}
}
}
],
"board": "<string>",
"name": "<string>",
"latencyDevice": "cortex-m4f-80mhz"
}
],
"applicationBudgets": [
{
"latencyPerInferenceMs": {
"minimum": 123,
"maximum": 123
},
"energyPerInferenceJoules": {
"minimum": 123,
"maximum": 123
},
"memoryOverhead": {
"ram": {
"fastBytes": {
"minimum": 123,
"maximum": 123
},
"slowBytes": {
"minimum": 123,
"maximum": 123
}
},
"rom": {
"fastBytes": {
"minimum": 123,
"maximum": 123
},
"slowBytes": {
"minimum": 123,
"maximum": 123
}
}
}
}
]
}
headers = {
"x-api-key": "<api-key>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {'x-api-key': '<api-key>', 'Content-Type': 'application/json'},
body: JSON.stringify({
targetDevices: [
{
processors: [
{
part: '<string>',
format: 'low-end MCU',
architecture: 'Cortex-M',
specificArchitecture: 'Cortex-M0+',
accelerator: 'Arm Cortex-U55',
fpu: true,
clockRateMhz: {minimum: 123, maximum: 123},
memory: {
ram: {
fastBytes: {minimum: 123, maximum: 123},
slowBytes: {minimum: 123, maximum: 123}
},
rom: {
fastBytes: {minimum: 123, maximum: 123},
slowBytes: {minimum: 123, maximum: 123}
}
}
}
],
board: '<string>',
name: '<string>',
latencyDevice: 'cortex-m4f-80mhz'
}
],
applicationBudgets: [
{
latencyPerInferenceMs: {minimum: 123, maximum: 123},
energyPerInferenceJoules: {minimum: 123, maximum: 123},
memoryOverhead: {
ram: {
fastBytes: {minimum: 123, maximum: 123},
slowBytes: {minimum: 123, maximum: 123}
},
rom: {
fastBytes: {minimum: 123, maximum: 123},
slowBytes: {minimum: 123, maximum: 123}
}
}
}
]
})
};
fetch('https://studio.edgeimpulse.com/v1/api/{projectId}/target-constraints', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));<?php
$curl = curl_init();
curl_setopt_array($curl, [
CURLOPT_URL => "https://studio.edgeimpulse.com/v1/api/{projectId}/target-constraints",
CURLOPT_RETURNTRANSFER => true,
CURLOPT_ENCODING => "",
CURLOPT_MAXREDIRS => 10,
CURLOPT_TIMEOUT => 30,
CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
CURLOPT_CUSTOMREQUEST => "POST",
CURLOPT_POSTFIELDS => json_encode([
'targetDevices' => [
[
'processors' => [
[
'part' => '<string>',
'format' => 'low-end MCU',
'architecture' => 'Cortex-M',
'specificArchitecture' => 'Cortex-M0+',
'accelerator' => 'Arm Cortex-U55',
'fpu' => true,
'clockRateMhz' => [
'minimum' => 123,
'maximum' => 123
],
'memory' => [
'ram' => [
'fastBytes' => [
'minimum' => 123,
'maximum' => 123
],
'slowBytes' => [
'minimum' => 123,
'maximum' => 123
]
],
'rom' => [
'fastBytes' => [
'minimum' => 123,
'maximum' => 123
],
'slowBytes' => [
'minimum' => 123,
'maximum' => 123
]
]
]
]
],
'board' => '<string>',
'name' => '<string>',
'latencyDevice' => 'cortex-m4f-80mhz'
]
],
'applicationBudgets' => [
[
'latencyPerInferenceMs' => [
'minimum' => 123,
'maximum' => 123
],
'energyPerInferenceJoules' => [
'minimum' => 123,
'maximum' => 123
],
'memoryOverhead' => [
'ram' => [
'fastBytes' => [
'minimum' => 123,
'maximum' => 123
],
'slowBytes' => [
'minimum' => 123,
'maximum' => 123
]
],
'rom' => [
'fastBytes' => [
'minimum' => 123,
'maximum' => 123
],
'slowBytes' => [
'minimum' => 123,
'maximum' => 123
]
]
]
]
]
]),
CURLOPT_HTTPHEADER => [
"Content-Type: application/json",
"x-api-key: <api-key>"
],
]);
$response = curl_exec($curl);
$err = curl_error($curl);
curl_close($curl);
if ($err) {
echo "cURL Error #:" . $err;
} else {
echo $response;
}package main
import (
"fmt"
"strings"
"net/http"
"io"
)
func main() {
url := "https://studio.edgeimpulse.com/v1/api/{projectId}/target-constraints"
payload := strings.NewReader("{\n \"targetDevices\": [\n {\n \"processors\": [\n {\n \"part\": \"<string>\",\n \"format\": \"low-end MCU\",\n \"architecture\": \"Cortex-M\",\n \"specificArchitecture\": \"Cortex-M0+\",\n \"accelerator\": \"Arm Cortex-U55\",\n \"fpu\": true,\n \"clockRateMhz\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"memory\": {\n \"ram\": {\n \"fastBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"slowBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n }\n },\n \"rom\": {\n \"fastBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"slowBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n }\n }\n }\n }\n ],\n \"board\": \"<string>\",\n \"name\": \"<string>\",\n \"latencyDevice\": \"cortex-m4f-80mhz\"\n }\n ],\n \"applicationBudgets\": [\n {\n \"latencyPerInferenceMs\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"energyPerInferenceJoules\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"memoryOverhead\": {\n \"ram\": {\n \"fastBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"slowBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n }\n },\n \"rom\": {\n \"fastBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"slowBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n }\n }\n }\n }\n ]\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("x-api-key", "<api-key>")
req.Header.Add("Content-Type", "application/json")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := io.ReadAll(res.Body)
fmt.Println(string(body))
}HttpResponse<String> response = Unirest.post("https://studio.edgeimpulse.com/v1/api/{projectId}/target-constraints")
.header("x-api-key", "<api-key>")
.header("Content-Type", "application/json")
.body("{\n \"targetDevices\": [\n {\n \"processors\": [\n {\n \"part\": \"<string>\",\n \"format\": \"low-end MCU\",\n \"architecture\": \"Cortex-M\",\n \"specificArchitecture\": \"Cortex-M0+\",\n \"accelerator\": \"Arm Cortex-U55\",\n \"fpu\": true,\n \"clockRateMhz\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"memory\": {\n \"ram\": {\n \"fastBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"slowBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n }\n },\n \"rom\": {\n \"fastBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"slowBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n }\n }\n }\n }\n ],\n \"board\": \"<string>\",\n \"name\": \"<string>\",\n \"latencyDevice\": \"cortex-m4f-80mhz\"\n }\n ],\n \"applicationBudgets\": [\n {\n \"latencyPerInferenceMs\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"energyPerInferenceJoules\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"memoryOverhead\": {\n \"ram\": {\n \"fastBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"slowBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n }\n },\n \"rom\": {\n \"fastBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"slowBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n }\n }\n }\n }\n ]\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://studio.edgeimpulse.com/v1/api/{projectId}/target-constraints")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["x-api-key"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n \"targetDevices\": [\n {\n \"processors\": [\n {\n \"part\": \"<string>\",\n \"format\": \"low-end MCU\",\n \"architecture\": \"Cortex-M\",\n \"specificArchitecture\": \"Cortex-M0+\",\n \"accelerator\": \"Arm Cortex-U55\",\n \"fpu\": true,\n \"clockRateMhz\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"memory\": {\n \"ram\": {\n \"fastBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"slowBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n }\n },\n \"rom\": {\n \"fastBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"slowBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n }\n }\n }\n }\n ],\n \"board\": \"<string>\",\n \"name\": \"<string>\",\n \"latencyDevice\": \"cortex-m4f-80mhz\"\n }\n ],\n \"applicationBudgets\": [\n {\n \"latencyPerInferenceMs\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"energyPerInferenceJoules\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"memoryOverhead\": {\n \"ram\": {\n \"fastBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"slowBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n }\n },\n \"rom\": {\n \"fastBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"slowBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n }\n }\n }\n }\n ]\n}"
response = http.request(request)
puts response.read_body{
"success": true,
"error": "<string>"
}Set target constraints
Set target constraints for a project. Use the constraints object to capture hardware attributes of your target device, along with an application budget to allow guidance on performance and resource usage
POST
/
api
/
{projectId}
/
target-constraints
Set target constraints
curl --request POST \
--url https://studio.edgeimpulse.com/v1/api/{projectId}/target-constraints \
--header 'Content-Type: application/json' \
--header 'x-api-key: <api-key>' \
--data '
{
"targetDevices": [
{
"processors": [
{
"part": "<string>",
"format": "low-end MCU",
"architecture": "Cortex-M",
"specificArchitecture": "Cortex-M0+",
"accelerator": "Arm Cortex-U55",
"fpu": true,
"clockRateMhz": {
"minimum": 123,
"maximum": 123
},
"memory": {
"ram": {
"fastBytes": {
"minimum": 123,
"maximum": 123
},
"slowBytes": {
"minimum": 123,
"maximum": 123
}
},
"rom": {
"fastBytes": {
"minimum": 123,
"maximum": 123
},
"slowBytes": {
"minimum": 123,
"maximum": 123
}
}
}
}
],
"board": "<string>",
"name": "<string>",
"latencyDevice": "cortex-m4f-80mhz"
}
],
"applicationBudgets": [
{
"latencyPerInferenceMs": {
"minimum": 123,
"maximum": 123
},
"energyPerInferenceJoules": {
"minimum": 123,
"maximum": 123
},
"memoryOverhead": {
"ram": {
"fastBytes": {
"minimum": 123,
"maximum": 123
},
"slowBytes": {
"minimum": 123,
"maximum": 123
}
},
"rom": {
"fastBytes": {
"minimum": 123,
"maximum": 123
},
"slowBytes": {
"minimum": 123,
"maximum": 123
}
}
}
}
]
}
'import requests
url = "https://studio.edgeimpulse.com/v1/api/{projectId}/target-constraints"
payload = {
"targetDevices": [
{
"processors": [
{
"part": "<string>",
"format": "low-end MCU",
"architecture": "Cortex-M",
"specificArchitecture": "Cortex-M0+",
"accelerator": "Arm Cortex-U55",
"fpu": True,
"clockRateMhz": {
"minimum": 123,
"maximum": 123
},
"memory": {
"ram": {
"fastBytes": {
"minimum": 123,
"maximum": 123
},
"slowBytes": {
"minimum": 123,
"maximum": 123
}
},
"rom": {
"fastBytes": {
"minimum": 123,
"maximum": 123
},
"slowBytes": {
"minimum": 123,
"maximum": 123
}
}
}
}
],
"board": "<string>",
"name": "<string>",
"latencyDevice": "cortex-m4f-80mhz"
}
],
"applicationBudgets": [
{
"latencyPerInferenceMs": {
"minimum": 123,
"maximum": 123
},
"energyPerInferenceJoules": {
"minimum": 123,
"maximum": 123
},
"memoryOverhead": {
"ram": {
"fastBytes": {
"minimum": 123,
"maximum": 123
},
"slowBytes": {
"minimum": 123,
"maximum": 123
}
},
"rom": {
"fastBytes": {
"minimum": 123,
"maximum": 123
},
"slowBytes": {
"minimum": 123,
"maximum": 123
}
}
}
}
]
}
headers = {
"x-api-key": "<api-key>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {'x-api-key': '<api-key>', 'Content-Type': 'application/json'},
body: JSON.stringify({
targetDevices: [
{
processors: [
{
part: '<string>',
format: 'low-end MCU',
architecture: 'Cortex-M',
specificArchitecture: 'Cortex-M0+',
accelerator: 'Arm Cortex-U55',
fpu: true,
clockRateMhz: {minimum: 123, maximum: 123},
memory: {
ram: {
fastBytes: {minimum: 123, maximum: 123},
slowBytes: {minimum: 123, maximum: 123}
},
rom: {
fastBytes: {minimum: 123, maximum: 123},
slowBytes: {minimum: 123, maximum: 123}
}
}
}
],
board: '<string>',
name: '<string>',
latencyDevice: 'cortex-m4f-80mhz'
}
],
applicationBudgets: [
{
latencyPerInferenceMs: {minimum: 123, maximum: 123},
energyPerInferenceJoules: {minimum: 123, maximum: 123},
memoryOverhead: {
ram: {
fastBytes: {minimum: 123, maximum: 123},
slowBytes: {minimum: 123, maximum: 123}
},
rom: {
fastBytes: {minimum: 123, maximum: 123},
slowBytes: {minimum: 123, maximum: 123}
}
}
}
]
})
};
fetch('https://studio.edgeimpulse.com/v1/api/{projectId}/target-constraints', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));<?php
$curl = curl_init();
curl_setopt_array($curl, [
CURLOPT_URL => "https://studio.edgeimpulse.com/v1/api/{projectId}/target-constraints",
CURLOPT_RETURNTRANSFER => true,
CURLOPT_ENCODING => "",
CURLOPT_MAXREDIRS => 10,
CURLOPT_TIMEOUT => 30,
CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
CURLOPT_CUSTOMREQUEST => "POST",
CURLOPT_POSTFIELDS => json_encode([
'targetDevices' => [
[
'processors' => [
[
'part' => '<string>',
'format' => 'low-end MCU',
'architecture' => 'Cortex-M',
'specificArchitecture' => 'Cortex-M0+',
'accelerator' => 'Arm Cortex-U55',
'fpu' => true,
'clockRateMhz' => [
'minimum' => 123,
'maximum' => 123
],
'memory' => [
'ram' => [
'fastBytes' => [
'minimum' => 123,
'maximum' => 123
],
'slowBytes' => [
'minimum' => 123,
'maximum' => 123
]
],
'rom' => [
'fastBytes' => [
'minimum' => 123,
'maximum' => 123
],
'slowBytes' => [
'minimum' => 123,
'maximum' => 123
]
]
]
]
],
'board' => '<string>',
'name' => '<string>',
'latencyDevice' => 'cortex-m4f-80mhz'
]
],
'applicationBudgets' => [
[
'latencyPerInferenceMs' => [
'minimum' => 123,
'maximum' => 123
],
'energyPerInferenceJoules' => [
'minimum' => 123,
'maximum' => 123
],
'memoryOverhead' => [
'ram' => [
'fastBytes' => [
'minimum' => 123,
'maximum' => 123
],
'slowBytes' => [
'minimum' => 123,
'maximum' => 123
]
],
'rom' => [
'fastBytes' => [
'minimum' => 123,
'maximum' => 123
],
'slowBytes' => [
'minimum' => 123,
'maximum' => 123
]
]
]
]
]
]),
CURLOPT_HTTPHEADER => [
"Content-Type: application/json",
"x-api-key: <api-key>"
],
]);
$response = curl_exec($curl);
$err = curl_error($curl);
curl_close($curl);
if ($err) {
echo "cURL Error #:" . $err;
} else {
echo $response;
}package main
import (
"fmt"
"strings"
"net/http"
"io"
)
func main() {
url := "https://studio.edgeimpulse.com/v1/api/{projectId}/target-constraints"
payload := strings.NewReader("{\n \"targetDevices\": [\n {\n \"processors\": [\n {\n \"part\": \"<string>\",\n \"format\": \"low-end MCU\",\n \"architecture\": \"Cortex-M\",\n \"specificArchitecture\": \"Cortex-M0+\",\n \"accelerator\": \"Arm Cortex-U55\",\n \"fpu\": true,\n \"clockRateMhz\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"memory\": {\n \"ram\": {\n \"fastBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"slowBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n }\n },\n \"rom\": {\n \"fastBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"slowBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n }\n }\n }\n }\n ],\n \"board\": \"<string>\",\n \"name\": \"<string>\",\n \"latencyDevice\": \"cortex-m4f-80mhz\"\n }\n ],\n \"applicationBudgets\": [\n {\n \"latencyPerInferenceMs\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"energyPerInferenceJoules\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"memoryOverhead\": {\n \"ram\": {\n \"fastBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"slowBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n }\n },\n \"rom\": {\n \"fastBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"slowBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n }\n }\n }\n }\n ]\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("x-api-key", "<api-key>")
req.Header.Add("Content-Type", "application/json")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := io.ReadAll(res.Body)
fmt.Println(string(body))
}HttpResponse<String> response = Unirest.post("https://studio.edgeimpulse.com/v1/api/{projectId}/target-constraints")
.header("x-api-key", "<api-key>")
.header("Content-Type", "application/json")
.body("{\n \"targetDevices\": [\n {\n \"processors\": [\n {\n \"part\": \"<string>\",\n \"format\": \"low-end MCU\",\n \"architecture\": \"Cortex-M\",\n \"specificArchitecture\": \"Cortex-M0+\",\n \"accelerator\": \"Arm Cortex-U55\",\n \"fpu\": true,\n \"clockRateMhz\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"memory\": {\n \"ram\": {\n \"fastBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"slowBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n }\n },\n \"rom\": {\n \"fastBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"slowBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n }\n }\n }\n }\n ],\n \"board\": \"<string>\",\n \"name\": \"<string>\",\n \"latencyDevice\": \"cortex-m4f-80mhz\"\n }\n ],\n \"applicationBudgets\": [\n {\n \"latencyPerInferenceMs\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"energyPerInferenceJoules\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"memoryOverhead\": {\n \"ram\": {\n \"fastBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"slowBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n }\n },\n \"rom\": {\n \"fastBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"slowBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n }\n }\n }\n }\n ]\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://studio.edgeimpulse.com/v1/api/{projectId}/target-constraints")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["x-api-key"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n \"targetDevices\": [\n {\n \"processors\": [\n {\n \"part\": \"<string>\",\n \"format\": \"low-end MCU\",\n \"architecture\": \"Cortex-M\",\n \"specificArchitecture\": \"Cortex-M0+\",\n \"accelerator\": \"Arm Cortex-U55\",\n \"fpu\": true,\n \"clockRateMhz\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"memory\": {\n \"ram\": {\n \"fastBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"slowBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n }\n },\n \"rom\": {\n \"fastBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"slowBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n }\n }\n }\n }\n ],\n \"board\": \"<string>\",\n \"name\": \"<string>\",\n \"latencyDevice\": \"cortex-m4f-80mhz\"\n }\n ],\n \"applicationBudgets\": [\n {\n \"latencyPerInferenceMs\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"energyPerInferenceJoules\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"memoryOverhead\": {\n \"ram\": {\n \"fastBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"slowBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n }\n },\n \"rom\": {\n \"fastBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n },\n \"slowBytes\": {\n \"minimum\": 123,\n \"maximum\": 123\n }\n }\n }\n }\n ]\n}"
response = http.request(request)
puts response.read_body{
"success": true,
"error": "<string>"
}Authorizations
ApiKeyAuthenticationJWTAuthenticationJWTHttpHeaderAuthenticationOAuth2
Path Parameters
Project ID
Body
application/json
The potential targets for the project, where each entry captures hardware attributes that allow target guidance throughout the Studio workflow. The first target in the list is considered as the selected target for the project.
Show child attributes
Show child attributes
A list of application budgets to be configured based on target device. An application budget enables guidance on performance and resource usage. The first application budget in the list is considered as the selected budget for the project.
Show child attributes
Show child attributes
A type explaining how the target was chosen. If updating this manually, use the 'user-configured' type
Available options:
user-configured, default, default-accepted, recent-project, connected-device Was this page helpful?
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