# Restaurant Dish Photo Matcher — Photos to Dishes, No API Key (`nomad-agent/dish-photo-matcher-managed`) Actor
Match restaurant food & drink photos to the menu items they show, using AI vision. Feed it photo URLs — or a Google Maps place to fetch guest photos — plus your menu, and get {photoUrl, dishName} pairs back. Perfect for adding real photos to parsed menus. No API keys needed.
- **URL**: https://apify.com/nomad-agent/dish-photo-matcher-managed.md
- **Developed by:** [Nomad.Dev](https://apify.com/nomad-agent) (community)
- **Categories:** AI, Travel
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $4.00 / 1,000 photo matcheds
This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".
## How to integrate an Actor?
If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md).
For usage examples, see the [API](#api) section below.
For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).
# README
## Restaurant Dish Photo Matcher — Photos → Menu Items
Match restaurant **food & drink photos to the menu items they actually
show**, using AI vision. A menu without photos converts poorly; guest photos
without labels are just noise. This actor joins the two:
- **Input**: your menu (JSON array of items) + food/drink photos — either
direct `photoUrls`, or a Google Maps `placeUrl` whose "Food & drink"
guest photos are fetched automatically.
- **Output**: one record per photo — `{photoUrl, dishName, matched}`, with
`dishName` the exact menu item name or `null` when nothing matches.
Photos are matched in batches of 9 by visual appearance; hallucinated names
(not on your menu) are filtered to `null` automatically. Ported from the
production photo-matching pipeline of a dietary-restrictions travel app.
### No API keys needed
Photo fetching and AI matching both run on our managed keys, and their cost
is already included in the per-photo price. No Google AI Studio signup, no
Outscraper account, no proxy configuration.
### Input example
```json
{
"placeUrl": "https://www.google.com/maps/place/Katz's+Delicatessen,+205+E+Houston+St,+New+York",
"menuItems": [
{"name": "Pastrami on Rye", "category": "Sandwiches"},
{"name": "Matzo Ball Soup", "category": "Soups"}
]
}
````
### Notes
- `menuItems` accepts plain strings too: `["Pastrami on Rye", "Tiramisu"]`.
- Chain it: **Google Maps Menu Scraper** (or **AI Menu Parser**) extracts
the structured menu, then this actor attaches a real photo to each dish.
- Prefer to pay Google and Outscraper directly and control your own quota?
The **Restaurant Dish Photo Matcher (BYO keys)** actor is the same matcher
at a lower per-photo price, with `geminiApiKey` / `outscraperApiKey`
inputs.
# Actor input Schema
## `menuItems` (type: `array`):
The restaurant's menu as a JSON array. Each item needs at least name; originalName, category and description improve match quality. Plain strings also work. Tip: the Google Maps Menu Scraper / AI Menu Parser actors produce compatible records.
## `photoUrls` (type: `array`):
Direct URLs of food/drink photos to match. Leave empty to scrape them from the Google Maps place below instead.
## `placeUrl` (type: `string`):
A Google Maps place URL or bare place ID (ChIJ…). Its "Food & drink" guest photos are scraped and matched. Ignored when photoUrls is set.
## `geminiModel` (type: `string`):
Model used by this actor. Only Flash-Lite is offered here because the AI cost is included in the price; the BYO-key actor exposes the larger models.
## `maxPhotos` (type: `integer`):
Cap on how many photos are matched (photos are processed in batches of 9).
## Actor input object example
```json
{
"menuItems": [
{
"name": "Margherita Pizza",
"category": "Pizza",
"description": "Tomato, mozzarella and basil"
},
{
"name": "Tiramisu",
"category": "Dessert"
}
],
"geminiModel": "gemini-3.1-flash-lite",
"maxPhotos": 27
}
```
# API
You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.
## JavaScript example
```javascript
import { ApifyClient } from 'apify-client';
// Initialize the ApifyClient with your Apify API token
// Replace the '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"menuItems": [
{
"name": "Margherita Pizza",
"category": "Pizza",
"description": "Tomato, mozzarella and basil"
},
{
"name": "Tiramisu",
"category": "Dessert"
}
]
};
// Run the Actor and wait for it to finish
const run = await client.actor("nomad-agent/dish-photo-matcher-managed").call(input);
// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
console.dir(item);
});
// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs
```
## Python example
```python
from apify_client import ApifyClient
# Initialize the ApifyClient with your Apify API token
# Replace '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = { "menuItems": [
{
"name": "Margherita Pizza",
"category": "Pizza",
"description": "Tomato, mozzarella and basil",
},
{
"name": "Tiramisu",
"category": "Dessert",
},
] }
# Run the Actor and wait for it to finish
run = client.actor("nomad-agent/dish-photo-matcher-managed").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"menuItems": [
{
"name": "Margherita Pizza",
"category": "Pizza",
"description": "Tomato, mozzarella and basil"
},
{
"name": "Tiramisu",
"category": "Dessert"
}
]
}' |
apify call nomad-agent/dish-photo-matcher-managed --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=nomad-agent/dish-photo-matcher-managed",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Restaurant Dish Photo Matcher — Photos to Dishes, No API Key",
"description": "Match restaurant food & drink photos to the menu items they show, using AI vision. Feed it photo URLs — or a Google Maps place to fetch guest photos — plus your menu, and get {photoUrl, dishName} pairs back. Perfect for adding real photos to parsed menus. No API keys needed.",
"version": "0.1",
"x-build-id": "NDEGkrQ4qLzTOM495"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/nomad-agent~dish-photo-matcher-managed/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-nomad-agent-dish-photo-matcher-managed",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/nomad-agent~dish-photo-matcher-managed/runs": {
"post": {
"operationId": "runs-sync-nomad-agent-dish-photo-matcher-managed",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/nomad-agent~dish-photo-matcher-managed/run-sync": {
"post": {
"operationId": "run-sync-nomad-agent-dish-photo-matcher-managed",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"required": [
"menuItems"
],
"properties": {
"menuItems": {
"title": "Menu items",
"type": "array",
"description": "The restaurant's menu as a JSON array. Each item needs at least name; originalName, category and description improve match quality. Plain strings also work. Tip: the Google Maps Menu Scraper / AI Menu Parser actors produce compatible records."
},
"photoUrls": {
"title": "Food/drink photo URLs",
"type": "array",
"description": "Direct URLs of food/drink photos to match. Leave empty to scrape them from the Google Maps place below instead.",
"items": {
"type": "string"
}
},
"placeUrl": {
"title": "Google Maps place (alternative to photo URLs)",
"type": "string",
"description": "A Google Maps place URL or bare place ID (ChIJ…). Its \"Food & drink\" guest photos are scraped and matched. Ignored when photoUrls is set."
},
"geminiModel": {
"title": "Gemini model",
"enum": [
"gemini-3.1-flash-lite"
],
"type": "string",
"description": "Model used by this actor. Only Flash-Lite is offered here because the AI cost is included in the price; the BYO-key actor exposes the larger models.",
"default": "gemini-3.1-flash-lite"
},
"maxPhotos": {
"title": "Max photos",
"minimum": 1,
"maximum": 100,
"type": "integer",
"description": "Cap on how many photos are matched (photos are processed in batches of 9).",
"default": 27
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```