Prima di aggiungere ufficialmente una immagine alla libreria cloud recognition (CRS), la best practice consiste nel valutarne in anticipo la qualità.
Se l'area riconoscibile della target image è troppo piccola, ad esempio una parete bianca o un blocco di colore uniforme, oppure se la texture è troppo semplice, la percentuale di successo del riconoscimento diminuirà notevolmente. Questo capitolo descrive in dettaglio il meccanismo di rating CRS per aiutare a selezionare materiali di riconoscimento AR di alta qualità.
Ci concentriamo principalmente sulle seguenti due metriche complessive. Entrambe hanno endpoint API separati che forniscono un rating complessivo:
Queste metriche valutano l'immagine dalla dimensione degli algoritmi immagine, e ogni metrica è comunque assegnata da 0 a 4 in base alla difficoltà.
Ogni target image nel database ha un rating dettagliato nei propri dettagli. È possibile ottenere le proprietà della target image tramite API per visualizzarle. È anche possibile visualizzarle tramite EasyAR cloud recognition management.
Come mostrato nella figura, la pagina dei dettagli contiene due metriche complessive principali, e un pentagono mostra cinque metriche dettagliate.
Quando si crea un backend di upload automatizzato, si consiglia di chiamare l'endpoint di rating prima dell'upload ufficiale.
- Convertire prima l'immagine target locale in Base64 (macOS / Linux) e salvare il risultato in image_base64.txt
base64 -i ./target.jpg | tr -d '\n' > image_base64.txt
- Sostituire i segnaposto con i parametri effettivi ed eseguire lo script curl
- Your-Server-side-URL → API Host effettivo
- Your-Token → API Key Authorization Token effettivo
- Your-CRS-AppId → il tuo appId
curl -X POST "https://<Your-Server-side-URL>/grade/detail" \
-H "Content-Type: application/json" \
-H "Authorization: <YOUR-TOKEN>" \
-d '{
"appId": "<Your-CRS-AppId>",
"image": "'"$(cat image_base64.txt)"'"
}'
Scaricare il codice di esempio Java
Importare il progetto tramite Maven
Step 1. Aprire il file di codice correlato Grade.java
Step 2. Modificare le variabili globali e sostituirle con i parametri di autenticazione nella checklist di preparazione
- CRS AppId
- API Key / API Secret
- Server-end URL
- IMAGE_PATH: file immagine target da caricare
import okhttp3.*;
import org.json.JSONObject;
import java.io.IOException;
import java.nio.file.Files;
import java.nio.file.Path;
import java.nio.file.Paths;
import java.util.Base64;
import java.util.HashMap;
import java.util.Map;
public class Grade {
private static final String TARGET_MGMT_URL = "http://cn1.crs.easyar.com:8888";
private static final String CRS_APPID = "--here is your CRS AppId--";
private static final String API_KEY = "--here is your API Key--";
private static final String API_SECRET = "--here is your API Secret--";
private static final String IMAGE_PATH = "test_target_image.jpg";
enum GradeType {
DETAIL,
DETECTION,
TRACKING
}
private static final Map<GradeType, String> GRADE_URL = new HashMap<GradeType, String>(){
{
put(GradeType.DETAIL, "/grade/detail") ;
put(GradeType.DETECTION, "/grade/detection") ;
put(GradeType.TRACKING, "/grade/tracking") ;
}
};
public String grade(Auth auth, String imgPath, GradeType gradeType) throws IOException {
final Path mImagePath = Paths.get(imgPath);
JSONObject params = new JSONObject().put("image", Base64.getEncoder().encodeToString(
Files.readAllBytes(mImagePath)
));
Auth.signParam(params, auth.getAppId(), auth.getApiKey(), auth.getApiSecret());
RequestBody requestBody = FormBody.create(MediaType.parse("application/json; charset=utf-8")
, params.toString());
Request request = new Request.Builder()
.url(auth.getCloudURL() + GRADE_URL.get(gradeType))
.post(requestBody)
.build();
return new OkHttpClient.Builder().build().newCall(request).execute().body().string();
}
public static void main(String[] args) throws IOException {
Auth accessInfo = new Auth(CRS_APPID, API_KEY, API_SECRET, TARGET_MGMT_URL);
System.out.println("================== grade details ==================");
System.out.println(new Grade().grade(accessInfo, IMAGE_PATH, GradeType.DETAIL));
System.out.println("================== grade for detection ==================");
JSONObject gradeResp = new JSONObject(new Grade().grade(accessInfo, IMAGE_PATH, GradeType.DETECTION));
System.out.println("Detection grade: " + gradeResp.getJSONObject(Common.KEY_RESULT).get(Common.KEY_GRADE));
System.out.println("================== grade for tracking =================== ");
gradeResp = new JSONObject(new Grade().grade(accessInfo, IMAGE_PATH, GradeType.TRACKING));
System.out.println("Tracking grade: " + gradeResp.getJSONObject(Common.KEY_RESULT).get(Common.KEY_GRADE));
}
}
Step 3. Eseguire Main
Scaricare il sample code NodeJS
Step 1. Configurare il key file keys.json
- CRS AppId
- API Key / API Secret
{
"appId": "--here is your appId for CRS App Instance for SDK 4--",
"apiKey": "--here is your api key which is create from website and which has crs permission--",
"apiSecret": "--here is your api secret which is create from website--"
}
Step 2. Eseguire specificando test image, key file e Server-end URL
node bin/grade test.jpeg -t <Server-end-URL> -c keys.json
var argv = require('yargs')
.usage('Usage: $0 [image] -t [host] -c [keys]')
.demand(1)
.default('t', 'http://localhost:8888').alias('t', 'host')
.default('c', 'keys.json').alias('c', 'keys')
.help('h').alias('h', 'help')
.epilog('copyright 2015, sightp.com')
.argv;
var fs = require('fs');
var imageFn = argv._[0];
var host = argv.host;
var keys = JSON.parse(fs.readFileSync(argv.keys));
var farmer = require('../farmer')(host, keys);
farmer.getTrackingGrade({
'image': fs.readFileSync(imageFn).toString('base64')
})
.then(function(resp) {
console.log(resp);
})
.fail(function(err) {
console.log(err);
});
Scarica il codice di esempio PHP
Step 1. Apri il codice di ingresso demo.php
Step 2. Modifica le variabili globali e sostituiscile con i parametri di autenticazione nell'elenco preparato
- CRS AppId
- API Key / API Secret
- Server-end URL
- imageFilePath : percorso del file immagine di destinazione da caricare
<?php
include 'EasyARClientSdkCRS.php';
$apiKey = 'API Key';
$apiSecret = 'API Secret';
$crsAppId = 'CRS AppId'
$crsCloudUrl = 'https://cn1-crs.easyar.com';
$imageFilePath = '1.jpg'
$sdk = new EasyARClientSdkCRS($apiKey, $apiSecret, $crsAppId, $crsCloudUrl);
$image = base64_encode(file_get_contents($imageFilePath));
$rs = $sdk->detection($image);
if ($rs->statusCode == 0) {
print_r($rs->result->grade);
} else {
print_r($rs);
}
Step 3. Esegui php demo.php
Creare il file di codice correlato grade.py, modificare le global variables, quindi eseguire
pip install requests
python grade.py
import time
import hashlib
import requests
import base64
# --- Global Configuration ---
API_KEY = "YOUR_API_KEY"
API_SECRET = "YOUR_API_SECRET"
APP_ID = "YOUR_APP_ID"
HOST = "https://crs-cn1.easyar.com"
IMAGE_PATH = "test.jpg"
def main():
# 1. Read and encode image
with open(IMAGE_PATH, "rb") as f:
image_base64 = base64.b64encode(f.read()).decode('utf-8')
timestamp = str(int(time.time() * 1000))
# 2. Build parameter dictionary (including image)
params = {
'apiKey': API_KEY,
'appId': APP_ID,
'timestamp': timestamp,
'image': image_base64
}
# 3. Sort by key and concatenate
sorted_keys = sorted(params.keys())
builder = "".join([f"{k}{params[k]}" for k in sorted_keys])
builder += API_SECRET
# 4. Generate SHA256 Signature
signature = hashlib.sha256(builder.encode('utf-8')).hexdigest()
# 5. Send POST request
payload = {**params, "signature": signature, "timestamp": int(timestamp)}
response = requests.post(f"{HOST}/grade/detection", json=payload)
print(f"Status: {response.status_code}")
print(f"Response: {response.text}")
if __name__ == "__main__":
main()
Creare il file di codice correlato main.go, modificare le variabili globali, quindi eseguire:
go run main.go
main.go:
package main
import (
"bytes"
"crypto/sha256"
"encoding/base64"
"encoding/json"
"fmt"
"io"
"net/http"
"os"
"sort"
"strconv"
"time"
)
var (
ApiKey = "YOUR_API_KEY"
ApiSecret = "YOUR_API_SECRET"
AppId = "YOUR_APP_ID"
Host = "https://crs-cn1.easyar.com"
ImagePath = "test.jpg"
)
func main() {
fileData, _ := os.ReadFile(ImagePath)
imgBase64 := base64.StdEncoding.EncodeToString(fileData)
tsInt := time.Now().UnixNano() / 1e6
tsStr := strconv.FormatInt(tsInt, 10)
params := map[string]string{
"apiKey": ApiKey,
"appId": AppId,
"timestamp": tsStr,
"image": imgBase64,
}
keys := make([]string, 0, len(params))
for k := range params { keys = append(keys, k) }
sort.Strings(keys)
var builder bytes.Buffer
for _, k := range keys {
builder.WriteString(k)
builder.WriteString(params[k])
}
builder.WriteString(ApiSecret)
signature := fmt.Sprintf("%x", sha256.Sum256(builder.Bytes()))
payload := map[string]interface{}{
"image": imgBase64,
"apiKey": ApiKey,
"appId": AppId,
"timestamp": tsInt,
"signature": signature,
}
jsonBytes, _ := json.Marshal(payload)
resp, _ := http.Post(Host+"/grade/detection", "application/json", bytes.NewBuffer(jsonBytes))
defer resp.Body.Close()
body, _ := io.ReadAll(resp.Body)
fmt.Printf("Response: %s\n", string(body))
}
Aggiungere le dipendenze reqwest, tokio, sha2 e hex in Cargo.toml.
Eseguire cargo run.
use sha2::{Sha256, Digest};
use std::collections::BTreeMap;
use std::time::{SystemTime, UNIX_EPOCH};
use base64::{Engine as _, engine::general_purpose};
const API_KEY: &str = "YOUR_API_KEY";
const API_SECRET: &str = "YOUR_API_SECRET";
const APP_ID: &str = "YOUR_APP_ID";
const HOST: &str = "https://crs-cn1.easyar.com";
const IMAGE_PATH: &str = "test.jpg";
#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
let img_bytes = std::fs::read(IMAGE_PATH)?;
let img_b64 = general_purpose::STANDARD.encode(img_bytes);
let ts_raw = SystemTime::now().duration_since(UNIX_EPOCH)?.as_millis();
let ts_str = ts_raw.to_string();
// 1. Collect params in BTreeMap for automatic sorting
let mut params = BTreeMap::new();
params.insert("apiKey", API_KEY);
params.insert("appId", APP_ID);
params.insert("timestamp", &ts_str);
params.insert("image", &img_b64);
// 2. Build sign string
let mut builder = String::new();
for (k, v) in ¶ms {
builder.push_str(k);
builder.push_str(v);
}
builder.push_str(API_SECRET);
// 3. Hash
let mut hasher = Sha256::new();
hasher.update(builder.as_bytes());
let signature = hex::encode(hasher.finalize());
let mut body = serde_json::Map::new();
body.insert("image".into(), img_b64.into());
body.insert("apiKey".into(), API_KEY.into());
body.insert("appId".into(), APP_ID.into());
body.insert("timestamp".into(), ts_raw.into());
body.insert("signature".into(), signature.into());
let client = reqwest::Client::new();
let res = client.post(format!("{}/grade/detection", HOST))
.json(&body)
.send()
.await?;
println!("Response: {}", res.text().await?);
Ok(())
}
Creare un progetto console .NET.
dotnet new console
dotnet run
using System;
using System.Collections.Generic;
using System.IO;
using System.Linq;
using System.Security.Cryptography;
using System.Text;
using System.Net.Http;
using System.Text.Json;
class Program {
static string API_KEY = "YOUR_API_KEY";
static string API_SECRET = "YOUR_API_SECRET";
static string APP_ID = "YOUR_APP_ID";
static string HOST = "https://crs-cn1.easyar.com";
static string IMAGE_PATH = "test.jpg";
static async System.Threading.Tasks.Task Main() {
string timestamp = DateTimeOffset.Now.ToUnixTimeMilliseconds().ToString();
string imageBase64 = Convert.ToBase64String(File.ReadAllBytes(IMAGE_PATH));
// 1. Prepare data for signing
var data = new SortedDictionary<string, string> {
{ "apiKey", API_KEY },
{ "appId", APP_ID },
{ "timestamp", timestamp },
{ "image", imageBase64 }
};
// 2. Concatenate keys and values
StringBuilder sb = new StringBuilder();
foreach (var pair in data) sb.Append(pair.Key).Append(pair.Value);
sb.Append(API_SECRET);
string signature = Sha256(sb.ToString());
// 3. Construct JSON body
var body = new {
image = imageBase64,
apiKey = API_KEY,
appId = APP_ID,
timestamp = long.Parse(timestamp),
signature = signature
};
using var client = new HttpClient();
var content = new StringContent(JsonSerializer.Serialize(body), Encoding.UTF8, "application/json");
var response = await client.PostAsync($"{HOST}/grade/detection", content);
Console.WriteLine($"Response: {await response.Content.ReadAsStringAsync()}");
}
static string Sha256(string str) {
byte[] bytes = SHA256.HashData(Encoding.UTF8.GetBytes(str));
return BitConverter.ToString(bytes).Replace("-", "").ToLower();
}
}
- Ambiente di esecuzione
- Unity 2020 LTS o versione successiva
- Scripting Backend: Mono o IL2CPP sono entrambi validi
- API Compatibility Level: .NET Standard 2.1 (consigliato)
Step 1: Preparare il file immagine
- Creare la directory nel progetto Unity:
Assets/
└── StreamingAssets/
| └── target.jpg
└── Scripts/
└── GrageImage.cs
- Secondo il nome della directory Assets
- Creare lo script GrageImage.cs e copiare il codice di esempio seguente
- Preparare un'immagine di test per l'image target
using System;
using System.IO;
using System.Text;
using UnityEngine;
using UnityEngine.Networking;
using System.Collections;
public class GrageImage : MonoBehaviour
{
[Header("Config")]
public string apiUrl = "https://Your-Server-end-URL" + "/grade/detection";
public string authorizationToken = "YOUR API KEY AUTH TOKEN";
public string imageFilePath = "target.jpg"; // StreamingAssets
public string crsAppId = "<Your-CRS-AppId>";
private void Start()
{
StartCoroutine(Grade());
}
private IEnumerator Grade()
{
// Read image file（Unity StreamingAssets）
string fullPath = Path.Combine(Application.streamingAssetsPath, imageFilePath);
if (!File.Exists(fullPath))
{
Debug.LogError($"Image file not found: {fullPath}");
yield break;
}
byte[] imageBytes = File.ReadAllBytes(fullPath);
string imageBase64 = Convert.ToBase64String(imageBytes);
TargetRequestBody body = new TargetRequestBody
{
appId = crsAppId,
image = imageBase64,
};
string json = JsonUtility.ToJson(body);
// UnityWebRequest
UnityWebRequest request = new UnityWebRequest(apiUrl, "POST");
byte[] jsonBytes = Encoding.UTF8.GetBytes(json);
request.uploadHandler = new UploadHandlerRaw(jsonBytes);
request.downloadHandler = new DownloadHandlerBuffer();
request.SetRequestHeader("Content-Type", "application/json");
request.SetRequestHeader("Authorization", authorizationToken);
yield return request.SendWebRequest();
if (request.result == UnityWebRequest.Result.Success)
{
Debug.Log("Grade detail success:");
Debug.Log(request.downloadHandler.text);
}
else
{
Debug.LogError("Grade detail failed:");
Debug.LogError(request.error);
Debug.LogError(request.downloadHandler.text);
}
}
[Serializable]
private class TargetRequestBody
{
public string appId;
public string image;
}
}
- In Unity Editor:
- Creare un GameObject vuoto
- Nominarlo GradeImage
- Trascinare lo script GrageImage su questo oggetto
Step 3: Configurare i parametri (Inspector)
Step 4: Eseguire
- Fare clic su Play
- Visualizzare il risultato in Console:
- Successo: restituisce JSON (result contiene un oggetto)
- Errore: HTTP / informazioni errore
