# Analyze Image (`yesintelligent/analyze-image`) Actor

Analyze images using NVIDIA NIM's Llama 3.2 90B Vision model for detailed visual understanding and description.

- **URL**: https://apify.com/yesintelligent/analyze-image.md
- **Developed by:** [yesintelligent](https://apify.com/yesintelligent) (community)
- **Categories:** AI, Developer tools, Other
- **Stats:** 21 total users, 0 monthly users, 5.9% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.01 / 1,000 results

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

## NVIDIA NIM Image Analyzer

An Apify Actor that analyzes images using NVIDIA NIM's Llama 3.2 90B Vision model for detailed visual understanding and description.

### Overview

This Actor leverages NVIDIA's powerful NIM (NVIDIA Inference Microservice) platform to perform sophisticated image analysis. Using the Llama 3.2 90B Vision model, it can analyze images and provide detailed descriptions, technical assessments, creative interpretations, and more.

### Features

- **Multimodal Analysis**: Uses NVIDIA NIM's Llama 3.2 90B Vision model for comprehensive image understanding
- **Multiple Analysis Types**: Choose from general, detailed, technical, or creative analysis
- **Structured Output**: Returns detailed analysis with confidence scores, key elements, colors, and sentiment
- **Easy Integration**: Simple input/output schema for seamless integration with other systems
- **Scalable**: Built on Apify's serverless platform for reliable, scalable execution

### How It Works

The NVIDIA NIM Image Analyzer processes images by sending them to NVIDIA's cloud-based inference service. The service uses the Llama 3.2 90B Vision model to analyze the visual content and generate detailed textual descriptions. Users can specify the type of analysis they want, from general descriptions to technical evaluations.

### Input Parameters

| Parameter | Type | Description | Required | Default |
|-----------|------|-------------|----------|---------|
| `imageUrl` | string | URL of the image to analyze (JPEG, PNG, GIF, WebP) | Yes | - |
| `analysisType` | string | Type of analysis: `general`, `detailed`, `technical`, `creative` | No | `general` |

### Output Format

The Actor returns structured data with the following fields:

| Field | Type | Description |
|-------|------|-------------|
| `imageUrl` | string | URL of the analyzed image |
| `analysisType` | string | Type of analysis performed |
| `analysisResult` | string | Detailed description and analysis of the image |
| `confidenceScore` | number | Confidence level of the analysis (0-1) |
| `modelUsed` | string | NVIDIA NIM model used for analysis |
| `processingTime` | number | Time taken to process the image (seconds) |
| `timestamp` | string | When the analysis was performed (ISO format) |

### Usage Examples

#### Basic Analysis
```json
{
  "imageUrl": "https://example.com/image.jpg",
  "analysisType": "general"
}
````

#### Detailed Technical Analysis

```json
{
  "imageUrl": "https://upload.wikimedia.org/wikipedia/commons/thumb/b/b6/Image_created_with_a_mobile_phone.png/640px-Image_created_with_a_mobile_phone.png",
  "analysisType": "technical"
}
```

### Analysis Types

#### General Analysis

Provides a balanced description including main subjects, setting, colors, and composition.

#### Detailed Analysis

Comprehensive analysis covering objects, people, environment, lighting, colors, textures, and symbols.

#### Technical Analysis

Technical assessment of image quality, composition, lighting conditions, and potential camera settings.

#### Creative Analysis

Artistic interpretation focusing on mood, emotions, story, and artistic elements.

### Pricing

This Actor uses pay-per-event pricing:

| Event | Price | Description |
|-------|-------|-------------|
| Actor Start | $0.00005 | Charged once per run |
| Image Processed | $0.005 | Charged for each image processed |
| Analysis Result | $0.002 | Charged for each analysis result pushed to dataset |
| External API Call | $0.01 | Charged for each external API call to NVIDIA NIM |

**Example Costs:**

- Processing 100 images: ~$0.75
- Processing 1,000 images: ~$7.50
- Processing 10,000 images: ~$75.00

This pricing model is user-friendly as you only pay for the actual work performed, without any platform usage costs.

### Benefits

- **High Accuracy**: Leverages NVIDIA's state-of-the-art vision model for precise analysis
- **Flexible Output**: Multiple analysis types to suit different use cases
- **Fast Processing**: Optimized for quick response times
- **Structured Data**: Easy-to-use JSON output for integration with other systems
- **Cost-Effective**: Pay-per-use pricing model with no upfront costs

### SEO Keywords

NVIDIA NIM, image analysis, computer vision, Llama 3.2, visual understanding, AI image processing, Apify Actor, automated image description, technical image analysis, creative image interpretation

### Support

For technical support or feature requests, please contact the maintainer or open an issue in the project repository.

# Actor input Schema

## `imageUrl` (type: `string`):

URL of the image to analyze (supports common image formats: JPEG, PNG, GIF, WebP)

## `customPrompt` (type: `string`):

Custom prompt for image analysis. If provided, this will be used instead of the analysis type.

## Actor input object example

```json
{
  "imageUrl": "https://drive.google.com/file/d/1aifNMWYUMHTrrWNwWK7gKBOLr9cRhnH8/view?usp=drive_link",
  "customPrompt": "Describe this image in detail, including the main subjects, setting, colors, and overall composition."
}
```

# Actor output Schema

## `results` (type: `string`):

Dataset containing all image analysis results

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "imageUrl": "https://drive.google.com/file/d/1aifNMWYUMHTrrWNwWK7gKBOLr9cRhnH8/view?usp=drive_link",
    "customPrompt": "Describe this image in detail, including the main subjects, setting, colors, and overall composition."
};

// Run the Actor and wait for it to finish
const run = await client.actor("yesintelligent/analyze-image").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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "imageUrl": "https://drive.google.com/file/d/1aifNMWYUMHTrrWNwWK7gKBOLr9cRhnH8/view?usp=drive_link",
    "customPrompt": "Describe this image in detail, including the main subjects, setting, colors, and overall composition.",
}

# Run the Actor and wait for it to finish
run = client.actor("yesintelligent/analyze-image").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 '{
  "imageUrl": "https://drive.google.com/file/d/1aifNMWYUMHTrrWNwWK7gKBOLr9cRhnH8/view?usp=drive_link",
  "customPrompt": "Describe this image in detail, including the main subjects, setting, colors, and overall composition."
}' |
apify call yesintelligent/analyze-image --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=yesintelligent/analyze-image",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

```json
{
    "openapi": "3.0.1",
    "info": {
        "title": "Analyze Image",
        "description": "Analyze images using NVIDIA NIM's Llama 3.2 90B Vision model for detailed visual understanding and description.",
        "version": "1.0",
        "x-build-id": "HJifBz4XOsUfB569J"
    },
    "servers": [
        {
            "url": "https://api.apify.com/v2"
        }
    ],
    "paths": {
        "/acts/yesintelligent~analyze-image/run-sync-get-dataset-items": {
            "post": {
                "operationId": "run-sync-get-dataset-items-yesintelligent-analyze-image",
                "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": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        },
        "/acts/yesintelligent~analyze-image/runs": {
            "post": {
                "operationId": "runs-sync-yesintelligent-analyze-image",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor and returns information about the initiated run in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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": {
                                    "$ref": "#/components/schemas/runsResponseSchema"
                                }
                            }
                        }
                    }
                }
            }
        },
        "/acts/yesintelligent~analyze-image/run-sync": {
            "post": {
                "operationId": "run-sync-yesintelligent-analyze-image",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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": [
                    "imageUrl"
                ],
                "properties": {
                    "imageUrl": {
                        "title": "🌅 Image URL",
                        "type": "string",
                        "description": "URL of the image to analyze (supports common image formats: JPEG, PNG, GIF, WebP)"
                    },
                    "customPrompt": {
                        "title": "📝 Custom Prompt",
                        "type": "string",
                        "description": "Custom prompt for image analysis. If provided, this will be used instead of the analysis type."
                    }
                }
            },
            "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
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }
    }
}
```