Antes de adicionar oficialmente uma imagem à biblioteca de cloud recognition (CRS), a melhor prática é avaliar previamente sua qualidade.
Se a área reconhecível da imagem alvo for pequena demais, como uma parede branca ou bloco de cor sólida, ou se a textura for simples demais, a taxa de sucesso de reconhecimento será bastante reduzida. Este capítulo descreve em detalhes o mecanismo de classificação do CRS para ajudar você a selecionar materiais de reconhecimento AR de alta qualidade.
Focamos principalmente nas duas métricas abrangentes a seguir. Ambas possuem endpoints API separados que fornecem classificação abrangente:
Essas métricas classificam a imagem pela dimensão dos algoritmos de imagem, e cada métrica ainda é fornecida de 0 a 4 conforme a dificuldade.
Cada imagem alvo no banco de dados possui classificação detalhada nos seus detalhes. Você pode obter as propriedades da imagem alvo pela API para visualizar. Também pode visualizar pelo EasyAR cloud recognition management.
Como mostrado na figura, a página de detalhes contém duas métricas abrangentes principais, e um pentágono exibe cinco métricas detalhadas.
Ao construir um backend de upload automatizado, recomenda-se chamar o endpoint de classificação antes do upload oficial.
- Primeiro converta a imagem target local para Base64 (macOS / Linux) e salve o resultado em image_base64.txt
base64 -i ./target.jpg | tr -d '\n' > image_base64.txt
- Substitua os espaços reservados pelos parâmetros reais e execute o script curl
- Your-Server-side-URL → API Host real
- Your-Token → API Key Authorization Token real
- Your-CRS-AppId → seu 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)"'"
}'
Baixar código de exemplo Java
Importar o projeto por Maven
Step 1. Abra o arquivo de código relacionado Grade.java
Step 2. Modifique as variáveis globais e substitua pelos parâmetros de autenticação da checklist de preparação
- CRS AppId
- API Key / API Secret
- Server-end URL
- IMAGE_PATH: arquivo de imagem alvo a ser enviado
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. Execute Main
Baixe o sample code NodeJS
Step 1. Configure o 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. Execute especificando a test image, o key file e a 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);
});
Baixe o codigo de exemplo PHP
Step 1. Abra o codigo de entrada demo.php
Step 2. Modifique as variaveis globais e substitua-as pelos parametros de autenticacao da lista preparada
- CRS AppId
- API Key / API Secret
- Server-end URL
- imageFilePath : caminho do arquivo de imagem de destino a ser enviado
<?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. Execute php demo.php
Crie o arquivo de código relacionado grade.py, modifique as global variables e então execute
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()
Crie o arquivo de código relacionado main.go, modifique as variáveis globais e execute:
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))
}
Adicione as dependências reqwest, tokio, sha2 e hex em Cargo.toml.
Execute 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(())
}
Crie um projeto de 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($"Response: {await response.Content.ReadAsStringAsync()}");
}
static string Sha256(string str) {
byte[] bytes = SHA256.HashData(Encoding.UTF8.GetBytes(str));
return BitConverter.ToString(bytes).Replace("-", "").ToLower();
}
}
- Ambiente de execução
- Unity 2020 LTS ou posterior
- Scripting Backend: Mono ou IL2CPP são aceitos
- API Compatibility Level: .NET Standard 2.1 (recomendado)
Step 1: Preparar o arquivo de imagem
- Crie o diretório no projeto Unity:
Assets/
└── StreamingAssets/
| └── target.jpg
└── Scripts/
└── GrageImage.cs
- De acordo com o nome do diretório Assets
- Crie o script GrageImage.cs e copie o código de exemplo abaixo
- Prepare uma imagem de teste para image target
using System;
using System.IO;
using System.Text;
using UnityEngine;
using UnityEngine.Networking;
using System.Collections;
public class GrageImage : MonoBehaviour
{
[Header("Config")]
public string apiUrl = "https://Your-Server-end-URL" + "/grade/detection";
public string authorizationToken = "YOUR API KEY AUTH TOKEN";
public string imageFilePath = "target.jpg"; // StreamingAssets
public string crsAppId = "<Your-CRS-AppId>";
private void Start()
{
StartCoroutine(Grade());
}
private IEnumerator Grade()
{
// Read image file（Unity StreamingAssets）
string fullPath = Path.Combine(Application.streamingAssetsPath, imageFilePath);
if (!File.Exists(fullPath))
{
Debug.LogError($"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;
}
}
- No Unity Editor:
- Crie um GameObject vazio
- Nomeie como GradeImage
- Arraste o script GrageImage para esse objeto
Step 3: Configurar parâmetros (Inspector)
Step 4: Executar
- Clique em Play
- Veja o resultado no Console:
- Sucesso: retorna JSON (result contém um objeto)
- Falha: HTTP / informações de erro
