# AI Image Watermark Popper (`mertcihanbayir/ai-watermark-popper`) Actor

Strip AI provenance metadata (C2PA/EXIF) and apply quality-gated imperceptible watermark disruption. High success vs Instagram/YouTube automatic file-based AI labels; SynthID verifiers are best-effort.

- **URL**: https://apify.com/mertcihanbayir/ai-watermark-popper.md
- **Developed by:** [Mert Cihan Bayır](https://apify.com/mertcihanbayir) (community)
- **Categories:** AI, Other, Social media
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks
- **User rating**: No ratings yet

## Pricing

from $30.00 / 1,000 cleaned images

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 web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — 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

## AI Watermark Popper (Apify Actor)

Strip AI provenance metadata (C2PA / EXIF / PNG text) and apply **quality-gated** imperceptible pixel disruption.

### What you get

- **Social auto-labels (Instagram / YouTube / X / LinkedIn):** high success (~90–95%) against *automatic file-based* AI labels.
- **SynthID-class pixel verifiers:** best-effort — not guaranteed.
- **Style classifiers / disclosure checkboxes:** out of scope.

This Actor is the headless twin of the Chrome extension pipeline. It does **not** inject into ChatGPT/Gemini tabs — you pass image URLs.

### Input

| Field | Type | Default | Notes |
|-------|------|---------|-------|
| `imageUrls` | string\[] | — | Required. Public HTTP(S) image URLs |
| `strength` | `light` | `standard` | `strong` | `standard` | Quality-gated disrupt dose |
| `outputFormat` | `same` | `png` | `jpeg` | `webp` | `same` | Output container |
| `maxImages` | int | `50` | Cap (1–200) |

### Output

- **Key-Value Store:** `cleaned-000.png` (etc.) and `OUTPUT` = last successful file
- **Dataset:** one row per URL with `ok`, `filename`, report summary, or `error`

### Local run

```bash
## from monorepo root — needs Apify CLI + Python 3.11+
cd apps/apify-actor
python -m venv .venv
## Windows:
.\.venv\Scripts\activate
pip install -r requirements.txt
pip install -e ../../packages/py-cleaner

## Put sample input (already under storage/.../INPUT.json) then:
apify run
```

Without Apify CLI you can still smoke-test the pipeline:

```bash
python scripts/smoke_local.py
```

### Deploy (`apify push`)

Apify uploads **only** `apps/apify-actor`. The shared package is vendored at `vendor/py-cleaner`.

After editing `packages/py-cleaner`, refresh the vendor copy before push:

```powershell
## from repo root
Copy-Item -Recurse -Force packages\py-cleaner apps\apify-actor\vendor\py-cleaner
Remove-Item -Recurse -Force apps\apify-actor\vendor\py-cleaner\py_cleaner.egg-info -ErrorAction SilentlyContinue
cd apps\apify-actor
apify push
```

### Monetization

Price this Actor on the Apify Store (rental and/or compute). No Stripe inside the Actor.

### Chrome extension

Unchanged. This package does not modify `apps/extension`.

# Actor input Schema

## `imageUrls` (type: `array`):

Public image URLs to clean (one or many).

## `strength` (type: `string`):

Disruption level. All modes are quality-gated (SSIM/PSNR).

## `outputFormat` (type: `string`):

Container for cleaned bytes. same = keep input family when possible.

## `maxImages` (type: `integer`):

Safety cap on how many URLs to process in one run.

## Actor input object example

```json
{
  "imageUrls": [
    "https://via.placeholder.com/256.png"
  ],
  "strength": "standard",
  "outputFormat": "same",
  "maxImages": 50
}
```

# 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 = {
    "imageUrls": [
        "https://via.placeholder.com/256.png"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("mertcihanbayir/ai-watermark-popper").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 = { "imageUrls": ["https://via.placeholder.com/256.png"] }

# Run the Actor and wait for it to finish
run = client.actor("mertcihanbayir/ai-watermark-popper").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 '{
  "imageUrls": [
    "https://via.placeholder.com/256.png"
  ]
}' |
apify call mertcihanbayir/ai-watermark-popper --silent --output-dataset

```

## MCP server setup

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

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/acts/Mn7P14kkvTozZtaim/builds/tMPXY0H95VeYxPvz2/openapi.json