metadata detection API
Extract Metadata from images programmatically with a single API call. Built for developers who need accurate labels, confidence scores, and optional metadata fieldes at scale.
Why Use This API
AI metadata detection
Advanced AI models trained on broad visual datasets. Accurately identifies common metadata categories from real-world scenes.
Confidence Scoring
Returns confidence values for each detection so you can filter low-certainty predictions in production pipelines.
metadata field Output
Optionally includes metadata field coordinates so you can draw overlays or crop detected metadata.
Multi-metadata detection
Detect and identify multiple different metadata within a single image. Perfect for analyzing complex designs.
Quick Start
Start identifying metadata in under a minute. Here's how:
- Get your API key — Sign up free to receive your key
- Send a request — POST an image containing one or more metadata to the endpoint
- Get the result — Receive identified metadata as JSON with confidence scores
curl -X POST https://precisioncounter.com/api/v1/extract-image-metadata \
-H "Authorization: Bearer YOUR_API_KEY" \
-F "image=@sample.png"
import requests
response = requests.post(
"https://precisioncounter.com/api/v1/extract-image-metadata",
headers={"Authorization": "Bearer YOUR_API_KEY"},
files={"image": open("sample.png", "rb")}
)
data = response.json()
for metadata in data["metadata"]:
print(f"{metadata['name']} ({metadata['confidence']:.0%})")
const fs = require("fs");
const FormData = require("form-data");
const form = new FormData();
form.append("image", fs.createReadStream("sample.png"));
const response = await fetch(
"https://precisioncounter.com/api/v1/extract-image-metadata",
{
method: "POST",
headers: {
"Authorization": "Bearer YOUR_API_KEY",
...form.getHeaders()
},
body: form
}
);
const data = await response.json();
data.metadata.forEach(f => console.log(`${f.name} (${f.confidence})`));
API Reference
Base URL
https://precisioncounter.com/api/v1
Authentication
All requests require an API key passed in the Authorization header:
Authorization: Bearer YOUR_API_KEY
Extract Metadata
Detects metadata from an uploaded image and returns structured detection results as JSON.
Request Parameters
| Parameter | Type | Description |
|---|---|---|
| image required | file | Image file to analyze for metadata detection. Accepted formats: PNG, JPG, JPEG, WebP. Max size: 10 MB. |
| max_fields optional | integer | Max number of metadata detections to return. Default: 5. Range: 1-20. |
| include_exif optional | boolean | Include metadata field coordinates for each detection. Default: true. |
Response
200 OK — Returns identified metadata data as JSON.
{
"metadata": [
{
"name": "person",
"confidence": 0.94,
"category": "person",
"box": {
"x": 124,
"y": 52,
"width": 300,
"height": 540
}
}
],
"image_width": 1280,
"image_height": 720,
"processing_time_ms": 450
}
Response Headers
| Header | Value |
|---|---|
| Content-Type | application/json |
| X-Credits-Remaining | Number of API credits remaining |
| X-Processing-Time | Processing time in milliseconds |
Code Examples
Full Examples (with error handling)
curl -X POST https://precisioncounter.com/api/v1/extract-image-metadata \
-H "Authorization: Bearer YOUR_API_KEY" \
-F "image=@sample.png" \
-F "max_fields=5" \
-F "include_exif=true"
import requests
import sys
API_KEY = "YOUR_API_KEY"
API_URL = "https://precisioncounter.com/api/v1/extract-image-metadata"
def detect_metadata(input_path, max_fields=5):
"""Extract Metadata from an image file."""
with open(input_path, "rb") as img:
response = requests.post(
API_URL,
headers={"Authorization": f"Bearer {API_KEY}"},
files={"image": img},
data={"max_fields": max_fields, "include_exif": "true"}
)
if response.status_code == 200:
data = response.json()
for metadata in data["metadata"]:
print(f"{metadata['name']} - {metadata['confidence']:.0%} confidence")
print(f" Category: {metadata['category']}")
if metadata.get("box"):
print(f" Box: {metadata['box']}")
print(f"Credits remaining: {response.headers.get('X-Credits-Remaining')}")
else:
print(f"Error {response.status_code}: {response.json()['error']}")
detect_metadata("sample.png")
const fs = require("fs");
const FormData = require("form-data");
const fetch = require("node-fetch");
const API_KEY = "YOUR_API_KEY";
const API_URL = "https://precisioncounter.com/api/v1/extract-image-metadata";
async function detectmetadata(inputPath, maxResults = 5) {
const form = new FormData();
form.append("image", fs.createReadStream(inputPath));
form.append("max_fields", String(maxResults));
form.append("include_exif", "true");
const response = await fetch(API_URL, {
method: "POST",
headers: {
"Authorization": `Bearer ${API_KEY}`,
...form.getHeaders()
},
body: form
});
if (response.ok) {
const data = await response.json();
data.metadata.forEach(metadata => {
console.log(`${metadata.name} - ${(metadata.confidence * 100).toFixed(0)}%`);
console.log(` Category: ${metadata.category}`);
if (metadata.box) console.log(` Box: ${JSON.stringify(metadata.box)}`);
});
console.log(`Credits: ${response.headers.get("x-credits-remaining")}`);
} else {
const error = await response.json();
console.error(`Error ${response.status}: ${error.error}`);
}
}
detectmetadata("sample.png");
<?php
$api_key = "YOUR_API_KEY";
$url = "https://precisioncounter.com/api/v1/extract-image-metadata";
$ch = curl_init();
curl_setopt_array($ch, [
CURLOPT_URL => $url,
CURLOPT_POST => true,
CURLOPT_RETURNTRANSFER => true,
CURLOPT_HTTPHEADER => [
"Authorization: Bearer $api_key"
],
CURLOPT_POSTFIELDS => [
"image" => new CURLFile("sample.png"),
"max_fields" => "5",
"include_exif" => "true"
]
]);
$response = curl_exec($ch);
$httpCode = curl_getinfo($ch, CURLINFO_HTTP_CODE);
curl_close($ch);
if ($httpCode === 200) {
$data = json_decode($response, true);
foreach ($data["metadata"] as $metadata) {
echo $metadata["name"] . " - " . ($metadata["confidence"] * 100) . "% confidence\n";
echo " Category: " . $metadata["category"] . "\n";
if (isset($metadata["box"])) {
echo " Box: " . json_encode($metadata["box"]) . "\n";
}
}
} else {
echo "Error $httpCode: $response\n";
}
?>
package main
import (
"bytes"
"encoding/json"
"fmt"
"io"
"mime/multipart"
"net/http"
"os"
)
type metadataResult struct {
Name string `json:"name"`
Confidence float64 `json:"confidence"`
Category string `json:"category"`
Box map[string]int `json:"box"`
}
type Response struct {
metadata []metadataResult `json:"metadata"`
ImageWidth int `json:"image_width"`
ImageHeight int `json:"image_height"`
ProcessingTime int `json:"processing_time_ms"`
}
func detectmetadata(inputPath string) error {
file, _ := os.Open(inputPath)
defer file.Close()
body := &bytes.Buffer{}
writer := multipart.NewWriter(body)
part, _ := writer.CreateFormFile("image", inputPath)
io.Copy(part, file)
writer.WriteField("max_fields", "5")
writer.Close()
req, _ := http.NewRequest("POST",
"https://precisioncounter.com/api/v1/extract-image-metadata", body)
req.Header.Set("Authorization", "Bearer YOUR_API_KEY")
req.Header.Set("Content-Type", writer.FormDataContentType())
resp, err := http.DefaultClient.Do(req)
if err != nil {
return err
}
defer resp.Body.Close()
if resp.StatusCode == 200 {
var result Response
json.NewDecoder(resp.Body).Decode(&result)
for _, metadata := range result.metadata {
fmt.Printf("%s - %.0f%% confidence\n", metadata.Name, metadata.Confidence*100)
}
}
return nil
}
func main() {
detectmetadata("sample.png")
}
require "net/http"
require "uri"
require "json"
api_key = "YOUR_API_KEY"
uri = URI("https://precisioncounter.com/api/v1/extract-image-metadata")
form_data = [
["image", File.open("sample.png", "rb")],
["max_fields", "5"],
["include_exif", "true"]
]
req = Net::HTTP::Post.new(uri)
req["Authorization"] = "Bearer #{api_key}"
req.set_form(form_data, "multipart/form-data")
res = Net::HTTP.start(uri.hostname, uri.port, use_ssl: true) do |http|
http.request(req)
end
if res.code == "200"
data = JSON.parse(res.body)
data["metadata"].each do |metadata|
puts "#{metadata['name']} - #{(metadata['confidence'] * 100).round}% confidence"
puts " Category: #{metadata['category']}"
puts " Box: #{metadata['box']}" if metadata['box']
end
else
puts "Error #{res.code}: #{res.body}"
end
using System.Text.Json;
using var client = new HttpClient();
client.DefaultRequestHeaders.Add("Authorization", "Bearer YOUR_API_KEY");
using var form = new MultipartFormDataContent();
var imageContent = new ByteArrayContent(File.ReadAllBytes("sample.png"));
imageContent.Headers.ContentType = new("image/png");
form.Add(imageContent, "image", "sample.png");
form.Add(new StringContent("5"), "max_fields");
form.Add(new StringContent("true"), "include_exif");
var response = await client.PostAsync(
"https://precisioncounter.com/api/v1/extract-image-metadata", form);
if (response.IsSuccessStatusCode)
{
var json = await response.Content.ReadAsStringAsync();
var data = JsonSerializer.Deserialize<JsonElement>(json);
foreach (var metadata in data.GetProperty("metadata").EnumerateArray())
{
Console.WriteLine($"{metadata.GetProperty("name")} - {metadata.GetProperty("confidence")}");
}
}
Error Handling
The API returns standard HTTP status codes with JSON error bodies:
| Status | Meaning | Description |
|---|---|---|
| 200 | Success | metadata identified successfully. Response body contains JSON with metadata data. |
| 400 | Bad Request | Missing image file, unsupported format, or file too large. |
| 401 | Unauthorized | Missing or invalid API key. |
| 429 | Rate Limited | Too many requests. Wait and retry with exponential backoff. |
| 500 | Server Error | Internal processing error. Retry the request. |
Error Response Format
{
"error": "Invalid file format. Accepted: png, jpg, jpeg, webp",
"code": "INVALID_FORMAT",
"status": 400
}
Rate Limits
| Plan | Requests / Minute | Max File Size | Max Resolution |
|---|---|---|---|
| Free | 10 | 10 MB | 4096 x 4096 px |
| Pro | 60 | 25 MB | 8192 x 8192 px |
Rate limit headers are included in every response:
X-RateLimit-Limit: 10 X-RateLimit-Remaining: 7 X-RateLimit-Reset: 1708646400
Use Cases
- Design asset management
- Brand consistency checking
- Web scraping metadata detection
- Accessibility compliance
- Print production
- image analysis research
- Design tool plugins
- detection workflow verification
Pricing
Get free API credits when you sign up. No credit card required.
Frequently Asked Questions
max_fields parameter to control how many metadata detections are returned, up to 20 per request.include_exif parameter set to false.