# Smart Video Analytics AI (YOLOv8) (`visita/smart-video-analytics`) Actor Turn video into intelligence. Detect weapons, analyze traffic, count crowds, and monitor retail behavior. This Actor scans footage frame-by-frame, logs timestamps, and captures evidence screenshots of relevant events automatically. - **URL**: https://apify.com/visita/smart-video-analytics.md - **Developed by:** [Visita Intelligence](https://apify.com/visita) (community) - **Categories:** Automation, Videos, Developer tools - **Stats:** 4 total users, 0 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing from $10.00 / 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. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## Smart Video Analytics AI (YOLOv8) **Turn any video footage into actionable intelligence. Detect weapons, analyze traffic, count crowds, and monitor retail behavior using advanced AI computer vision.** --- ### What is Smart Video Analytics AI? **Smart Video Analytics AI** is a powerful AI tool that processes video files to detect specific objects, behaviors, and security threats. Built on the state-of-the-art **YOLOv8 architecture**, it scans video footage frame-by-frame, identifies relevant objects (like weapons, vehicles, or unattended bags), and generates a detailed report with timestamps and photographic evidence. Unlike generic object detectors, this Actor features **15+ specialized Analysis Modes**. Whether you are a security professional looking for threats, a city planner analyzing traffic, or a business owner tracking store occupancy, this tool filters out the noise and only reports what matters to you. ### Why use this Actor? Video analysis is traditionally expensive and time-consuming. Humans cannot watch 24/7 feeds effectively, and enterprise AI solutions often cost thousands of dollars. **Smart Video Analytics AI solves this by:** * **Automating Surveillance:** Process hours of footage in minutes. * **Reducing False Positives:** Select specific modes (e.g., "Fire Safety") to only look for relevant object combinations (e.g., Cars blocking Fire Hydrants). * **Smart Evidence:** It automatically captures and hosts a screenshot (JPG) for every detection, giving you instant visual proof without downloading the whole video. #### Main Features * **15 Specialized Modes:** From **Threat Detection** to **Retail Analytics** and **Wildlife Monitoring**. * **Multi-Mode Analysis:** Run multiple checks simultaneously (e.g., count cars AND detect weapons in the same pass). * **Configurable Speed:** Adjust the `frameStep` to balance between high-speed scanning and frame-perfect accuracy. * **JSON & Excel Reports:** Get structured data compatible with Tableau, PowerBI, or your own dashboard. ### Analysis Modes Select one or multiple modes in the input to tailor the AI's focus: | Mode | Detects | Best For | | :--- | :--- | :--- | | **🚨 Threat Detection** | Persons, Knives, Bats, Scissors | Security teams, Crime analysis | | **🚗 Traffic Surveillance** | Cars, Trucks, Buses, Bikes | City planning, Road usage stats | | **⛽ Petrol Garage** | Vehicles, Persons, Trucks | Fuel station logistics | | **🛍️ Retail Analytics** | Persons, Handbags, Backpacks | Store heatmaps, Loss prevention | | **🎒 Abandoned Object** | Suitcases, Backpacks | Airports, Train stations | | **🔥 Fire Safety** | Hydrants, Vehicles | Detecting blocked emergency access | | **👥 Crowd Counting** | Persons | Occupancy limits, Queue management | | **🚜 Heavy Machinery** | Trucks | Construction site monitoring | | **👤 Face Logging** | Persons (Body tracking) | Timestamping entry/exit | | **🐶 Pet Behavior** | Cats, Dogs, Furniture | Home monitoring applications | ### How to analyze a video This Actor is designed to be simple. [cite_start]You do not need coding skills to use it[cite: 6]. 1. **Get your Video URL:** Ensure you have a direct link to a video file (`.mp4`, `.avi`, `.mkv`). This can be from cloud storage (Google Cloud, S3, Azure) or a public server. * **⚠️ Note on YouTube:** YouTube and social media video links are **not supported** due to aggressive bot detection. Please use direct media links or cloud storage instead. 2. **Select Analysis Mode:** Choose the logic you want to apply (e.g., "Threat Detection"). You can select multiple. 3. **Set Frame Step:** * Use `30` (default) to check 1 frame per second (assuming 30fps video). * Use `1` for frame-perfect accuracy (slower). 4. **Run:** Click Start. The Actor will output a list of detections as they happen. ### Input Example [cite_start]You can configure the actor using a simple JSON object or the visual interface[cite: 4]. ```json { "videoUrl": "[https://example.com/security_footage.mp4](https://example.com/security_footage.mp4)", "analysisMode": ["threat_detection", "abandoned_object"], "frameStep": 15, "confidenceThreshold": 0.5 } ```` ### Output Example \[cite\_start]The Actor produces a dataset where every item represents a specific frame where a detection occurred\[cite: 5]. ```json { "timestamp_seconds": 12.5, "frame_index": 375, "triggered_modes": ["threat_detection"], "objects_detected": ["person (0.92)", "knife (0.88)"], "object_count": 2, "screenshot_url": "[https://api.apify.com/v2/key-value-stores/](https://api.apify.com/v2/key-value-stores/)..." } ``` ### Pricing & Costs This Actor uses deep learning models which require CPU power. \[cite\_start]Pricing is based on the **duration of the video processed** and the **frame step** you select\[cite: 3]. - **Estimated Cost:** ~$0.05 per 10 minutes of video analysis (at 30 frame step). - **Optimization Tip:** To save costs on long static videos (like overnight security footage), increase the `frameStep` to 60 or 100. This reduces the number of AI inferences required. ### Legal & Licensing #### Open Source Compliance (AGPL-3.0) This Actor utilizes **YOLOv8** by Ultralytics. In compliance with the **AGPL-3.0 License**, the source code for this Actor is publicly available. - **License:** You are free to use this for commercial purposes, provided that if you modify and redistribute this software as a service, you must also share your source code. #### Data Privacy & GDPR We do not store your video files. Videos are processed in volatile memory and discarded immediately after analysis. Screenshots are stored in your private Apify Key-Value store and are accessible only by you (unless you share the public link). \[cite\_start]Do not use this tool to infringe on the privacy rights of others\[cite: 7]. ### Cloud Storage & BYOK (Bring Your Own Key) For professional and high-volume workflows, we highly recommend using your own cloud storage. This ensures full ownership of your data and easier integration with your existing data pipelines. The Actor supports **Amazon S3, Google Cloud Storage, Azure Blob Storage, and Cloudflare R2**. Simply provide your credentials in the Input section to enable direct upload of evidence screenshots to your own buckets. ### Support & Feedback If you encounter any issues or have a request for a new "Mode" (e.g., detecting specific industrial equipment), please reach out! - **Report Bugs:** Use the "Issues" tab on this page. - **Custom Solutions:** We can train custom models (e.g., detecting guns, specific uniforms, or brand logos) for enterprise clients. Contact us for details. ``` ``` # Actor input Schema ## `videoUrl` (type: `string`): Direct link to the video file (e.g. MP4) or a live/streaming URL. ## `analysisMode` (type: `array`): Select one or more analysis pipelines to run on the video. ## `frameStep` (type: `integer`): Analyze every Nth frame. Higher values improve speed but reduce accuracy. ## `confidenceThreshold` (type: `number`): Minimum detection confidence required (0.0 – 1.0). ## `maxVideoDuration` (type: `integer`): Stop processing after this many seconds (0 = no limit). ## `debugMode` (type: `boolean`): Enable verbose logs for debugging and development. ## `storageProvider` (type: `string`): Where evidence screenshots and metadata will be stored. ## `awsAccessKeyId` (type: `string`): Access Key ID for the AWS S3 account. ## `awsSecretAccessKey` (type: `string`): Secret Access Key for the AWS S3 account. ## `awsBucketName` (type: `string`): Name of the S3 bucket where files will be stored. ## `awsRegion` (type: `string`): AWS region of the S3 bucket (e.g. us-east-1). ## `r2AccessKeyId` (type: `string`): Access Key ID for Cloudflare R2. ## `r2SecretAccessKey` (type: `string`): Secret Access Key for Cloudflare R2. ## `r2AccountId` (type: `string`): Cloudflare account identifier. ## `r2BucketName` (type: `string`): Target Cloudflare R2 bucket name. ## `r2PublicDomain` (type: `string`): Optional public domain for accessing stored files. ## `gcsServiceAccountJson` (type: `string`): Full contents of the Google Cloud service account JSON file. ## `gcsBucketName` (type: `string`): Target Google Cloud Storage bucket name. ## `azureConnectionString` (type: `string`): Azure Storage account connection string. ## `azureContainerName` (type: `string`): Azure Blob Storage container name. ## Actor input object example ```json { "analysisMode": [ "threat_detection" ], "frameStep": 30, "confidenceThreshold": 0.5, "maxVideoDuration": 0, "debugMode": false, "storageProvider": "apify", "awsRegion": "us-east-1" } ``` # Actor output Schema ## `detections` (type: `string`): No description # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("visita/smart-video-analytics").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 = {} # Run the Actor and wait for it to finish run = client.actor("visita/smart-video-analytics").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 '{}' | apify call visita/smart-video-analytics --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=visita/smart-video-analytics", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Smart Video Analytics AI (YOLOv8)", "description": "Turn video into intelligence. Detect weapons, analyze traffic, count crowds, and monitor retail behavior. This Actor scans footage frame-by-frame, logs timestamps, and captures evidence screenshots of relevant events automatically.", "version": "0.0", "x-build-id": "8HJe96MSASzpu9Bav" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/visita~smart-video-analytics/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-visita-smart-video-analytics", "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/visita~smart-video-analytics/runs": { "post": { "operationId": "runs-sync-visita-smart-video-analytics", "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/visita~smart-video-analytics/run-sync": { "post": { "operationId": "run-sync-visita-smart-video-analytics", "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": [ "videoUrl" ], "properties": { "videoUrl": { "title": "Video URL", "type": "string", "description": "Direct link to the video file (e.g. MP4) or a live/streaming URL." }, "analysisMode": { "title": "Analysis Modes", "type": "array", "description": "Select one or more analysis pipelines to run on the video.", "items": { "type": "string", "enum": [ "threat_detection", "petrol_garage", "retail_analytics", "traffic_surveillance", "face_logging", "crowd_counting", "abandoned_object", "heavy_machinery", "wildlife_monitoring", "sanitation_hygiene", "fire_safety", "office_occupancy", "bike_lane_safety", "pet_behavior", "parking_lot" ], "enumTitles": [ "🚨 Threat Detection (Weapons)", "⛽ Petrol Garage (Vehicles)", "🛍️ Retail Analytics", "🚗 Traffic Surveillance", "👤 Face / Person Logging", "👥 Crowd Counting", "🎒 Abandoned Object Detection", "🚜 Heavy Machinery", "🐾 Wildlife Monitoring", "🍽️ Sanitation & Hygiene", "🔥 Fire Safety", "💼 Office Occupancy", "🚲 Bike Lane Safety", "🐶 Pet Behavior", "🅿️ Parking Lot Management" ] }, "default": [ "threat_detection" ] }, "frameStep": { "title": "Frame Step", "minimum": 1, "type": "integer", "description": "Analyze every Nth frame. Higher values improve speed but reduce accuracy.", "default": 30 }, "confidenceThreshold": { "title": "Confidence Threshold", "minimum": 0, "maximum": 1, "type": "number", "description": "Minimum detection confidence required (0.0 – 1.0).", "default": 0.5 }, "maxVideoDuration": { "title": "Max Video Duration (Seconds)", "minimum": 0, "type": "integer", "description": "Stop processing after this many seconds (0 = no limit).", "default": 0 }, "debugMode": { "title": "Debug Mode", "type": "boolean", "description": "Enable verbose logs for debugging and development.", "default": false }, "storageProvider": { "title": "Storage Provider", "enum": [ "apify", "aws_s3", "cloudflare_r2", "google_cloud", "azure_blob" ], "type": "string", "description": "Where evidence screenshots and metadata will be stored.", "default": "apify" }, "awsAccessKeyId": { "title": "AWS Access Key ID", "type": "string", "description": "Access Key ID for the AWS S3 account." }, "awsSecretAccessKey": { "title": "AWS Secret Access Key", "type": "string", "description": "Secret Access Key for the AWS S3 account." }, "awsBucketName": { "title": "AWS Bucket Name", "type": "string", "description": "Name of the S3 bucket where files will be stored." }, "awsRegion": { "title": "AWS Region", "type": "string", "description": "AWS region of the S3 bucket (e.g. us-east-1).", "default": "us-east-1" }, "r2AccessKeyId": { "title": "R2 Access Key ID", "type": "string", "description": "Access Key ID for Cloudflare R2." }, "r2SecretAccessKey": { "title": "R2 Secret Access Key", "type": "string", "description": "Secret Access Key for Cloudflare R2." }, "r2AccountId": { "title": "Cloudflare Account ID", "type": "string", "description": "Cloudflare account identifier." }, "r2BucketName": { "title": "R2 Bucket Name", "type": "string", "description": "Target Cloudflare R2 bucket name." }, "r2PublicDomain": { "title": "R2 Public Domain", "type": "string", "description": "Optional public domain for accessing stored files." }, "gcsServiceAccountJson": { "title": "GCS Service Account JSON", "type": "string", "description": "Full contents of the Google Cloud service account JSON file." }, "gcsBucketName": { "title": "GCS Bucket Name", "type": "string", "description": "Target Google Cloud Storage bucket name." }, "azureConnectionString": { "title": "Azure Connection String", "type": "string", "description": "Azure Storage account connection string." }, "azureContainerName": { "title": "Azure Container Name", "type": "string", "description": "Azure Blob Storage container name." } } }, "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 } } } } } } } } } } ```