Calorie Recognition API

API ID 5584

Calorie Recognition API analyzes food images to identify dishes and calculate their calorie content, helping to manage diets and nutrition.

100% uptime 2,636 ms avg response

API Documentation

Endpoints

Request

To use this endpoint, you must specify the URL of a meal.

Endpoint ID: 7732
POST https://zylalabs.com/api/5584/calorie+recognition+api/7732/food+analyzer
INPUT PARAMETERS

Food Analyzer — Endpoint Features

Object Description
Request Body Required Json

Free test requests remaining: 3 of 3.


INPUT PARAMETERS

API EXAMPLE RESPONSE
JSON
{
  "id": "chatcmpl-AfUDMprRUYdHUhorRPkRZTF24DPhi",
  "object": "-",
  "created": 1734450956,
  "model": "zyla-image-recognition",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "Ingredients: Hot dog, bun, ketchup, mustard. Calories: Approximately 250-300 calories.",
        "refusal": null
      },
      "logprobs": null,
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 48194,
    "completion_tokens": 20,
    "total_tokens": 48214,
    "prompt_tokens_details": {
      "cached_tokens": 0,
      "audio_tokens": 0
    },
    "completion_tokens_details": {
      "reasoning_tokens": 0,
      "audio_tokens": 0,
      "accepted_prediction_tokens": 0,
      "rejected_prediction_tokens": 0
    }
  },
  "system_fingerprint": "fp_39a40c96a0"
}
Food Analyzer — CODE SNIPPETS

curl --location --request POST 'https://zylalabs.com/api/5584/calorie+recognition+api/7732/food+analyzer' --header 'Authorization: Bearer YOUR_API_KEY' 

--data-raw '{
  "model": "zyla-image-recognition",
  "messages": [
    {
      "role": "user",
      "content": [
        {
          "type": "text",
          "text": "Counter Calories"
        },
        {
          "type": "image_url",
          "image_url": {
            "url": "https://upload.wikimedia.org/wikipedia/commons/thumb/b/b1/Hot_dog_with_mustard.png/1920px-Hot_dog_with_mustard.png"
          }
        }
      ]
    }
  ],
  "max_tokens": 300
}'

    

API Access Key & Authentication

After signing up, every developer is assigned a personal API access key, a unique combination of letters and digits provided to access to our API endpoint. To authenticate with the Calorie Recognition API simply include your bearer token in the Authorization header.

Headers
Header Description
Authorization Required Should be Bearer access_key. See "Your API Access Key" above when you are subscribed.

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Overview

About the API:  

The Calorie Recognition API simplifies dietary management by analyzing food images to identify dishes and calculate their calorie content. Using state-of-the-art machine learning technology, the API recognizes a wide range of foods with exceptional accuracy, from simple ingredients to complex meals, ensuring accurate calorie estimates.

Designed with versatility in mind, the API adapts to diverse cuisines, providing inclusive and reliable results for users across diverse dietary preferences and cultural backgrounds. Its capabilities go beyond identification, providing comprehensive nutritional information to help individuals and organizations make informed dietary decisions.

The API integrates seamlessly into applications and provides real-time feedback to enhance the user experience. Its robust framework is compatible with popular programming languages and is accompanied by detailed documentation to ensure effortless implementation. 

Calorie Recognition API FAQs

There are different plans to suit all tastes, including a free trial for a small number of requests, but your rate is limited to avoid abuse of the service.

The API uses API keys for authentication. To access the API, include your API key in the request header. The API key is provided upon registration and should be kept secure.

To use this API, users must indicate the URL of a meal to recognize the food and its calories.

Calorie Recognition API identifies foods from images and calculates their caloric content, enabling accurate and efficient nutrition tracking and management.

Calorie Recognition API analyzes food images, identifies dishes and calculates calories, providing accurate data for efficient nutritional management.

The Food Analyzer endpoint returns data that includes identified ingredients, estimated calorie content, and a unique ID for each request. The response also contains metadata about the model used for analysis and token usage details.

Key fields in the response include "id" (unique request identifier), "choices" (which contains the identified ingredients and calorie estimates), and "usage" (detailing token consumption). Each choice provides a structured message with content about the food analyzed.

The Food Analyzer endpoint requires a zip code as a mandatory parameter. Optional parameters include city and state, allowing users to customize their requests based on location for more accurate results.

The response data is organized in a JSON format, with a top-level object containing fields like "id," "object," "created," and "choices." Each choice includes a message detailing the recognized ingredients and calorie information, making it easy to parse.

Typical use cases include dietary tracking apps, meal planning tools, and nutrition analysis platforms. Users can upload food images to receive instant calorie estimates and ingredient breakdowns, aiding in healthier eating decisions.

Data accuracy is maintained through advanced machine learning algorithms trained on diverse food datasets. Continuous updates and quality checks ensure that the API adapts to new food items and variations across different cuisines.

Users can utilize the returned data by extracting the "content" field from the "choices" array to get ingredient and calorie information. This data can be integrated into user interfaces for meal tracking or nutritional analysis.

Standard data patterns include a consistent structure in the response, with multiple choices for complex meals and a clear indication of calorie ranges. Users can expect variations in ingredient lists based on the complexity of the food analyzed.

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