Skip to main content

Enhance images with Riverflow 2.0 reference-based super-resolution via Replicate

Workflow preview

Workflow preview
100%
Enhance images with Riverflow 2.0 reference-based super-resolution via Replicate preview
Open on n8n.io

1. Workflow Overview

How it works This workflow can take an image URL and enhance said image using Riverflow 2.0 Reference Based Super Resolution . This process involves giving the model an ...

Best for

  • Content Creation automation workflows
  • Multimodal AI automation workflows
  • advanced n8n builders looking for reusable templates

Tools used

n8n-nodes-base.wait, n8n-nodes-base.stopanderror, n8n-nodes-base.stickynote, n8n-nodes-base.formtrigger, n8n-nodes-base.code, n8n-nodes-base.httprequest, n8n-nodes-base.if, n8n-nodes-base.set

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Joel Sage.

Original n8n.io source

1.1 Workflow description

Title
Enhance images with Riverflow 2.0 reference-based super-resolution via Replicate
Workflow name
Enhance images with Riverflow 2.0 reference-based super-resolution via Replicate

How it works

This workflow can take an image URL and enhance said image using Riverflow 2.0 Reference-Based Super-Resolution. This process involves giving the model an image to enhance along with a reference image to specify a certain element to enhance. For example, if we have a photoshoot but the product looks blurry/low quality, we can feed this along with a reference for what the product should look like and it will enhance that element based on the reference we gave. This workflow takes advantage of this and does the following steps:

  1. Input Form takes in the necessary inputs used for Riverflow 2.0
  • Image (required)
  • Super Resolution References (required, max 4)
  1. Inputs are Sanitized using JavaScript to get in a suitable way to be used in API call.
  2. POST request is made to the Replicate API to begin generating the new image.
  3. a GET request is looped over to check the status of the generation; when the generation is done, this loop breaks to output the image or an error if one occurred.
  4. The output is then given as a raw image to be downloaded or viewed within the workflow (or passed on to elsewhere).

Setup

This Workflow requires a Replicate API key which can be accessed from Replicate

Ideal for

  • Restoring things like:
  • product labels and packaging text
  • logos and brand marks
  • printed designs on objects
  • fine text and small UI-like elements inside a scene
  • E-commerce Brands & Retailers - Perfect for product photography where labels, packaging text, or logos must be crisp. Can automatically enhance images for catalogs, online stores, or marketplaces. Reduces the need for re-shooting or manual touch-ups of blurry product images.
  • Design & Creative Teams - Can fix blurry renders or low-res concept images while preserving the overall style. Speeds up repetitive image refinement tasks, letting designers focus on creative decisions.
  • Marketing & Advertising Teams - Helps create high-quality visual assets for ads, social media posts, or campaigns. Allows batch enhancement of multiple creatives using reference images to maintain brand consistency.

Customization

  • Output Customization - The enhanced Images produced in this workflow can be part of a larger one and the output can be taken and sent elsewhere such as a cloud service or through webhooks.
  • Parallelism - This workflow could potentially be adapted to have parallel requests so that various outputs can be generated for the same inputs to increase the chance of better results.
  • Marketing campaign pipeline - designer can trigger and upload creative drafts; refsr can then enhance details and be used part of post processing of the marketing ads.

Reference-Based Super Resolution:

The model will:

  • locate the best matching regions in the original image
  • super-resolve and correct those regions in-place
  • preserve the surrounding scene while improving detail fidelity

To get the best results:

  • Use clean, high-resolution reference images
  • Make sure references are cropped tightly around the detail you want restored
  • Avoid references with glare, motion blur, or heavy perspective distortion
  • Provide multiple references only when they represent different target details

The model can fix up to 4 matched instances in a single run. More about Riverflow 2.0: www.riverflow.ai for more information for API: Sourceful - Replicate API

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - Wait

Type / Role
n8n-nodes-base.wait - wait
Config choices
Version 1.1

Block 2 - Stop and Error

Type / Role
n8n-nodes-base.stopAndError - stopAndError
Config choices
Version 1

Block 3 - Sticky Note

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 4 - Input form

Type / Role
n8n-nodes-base.formTrigger - formTrigger
Config choices
Version 2.5

Block 5 - Input Handling

Type / Role
n8n-nodes-base.code - code
Config choices
Version 2

Block 6 - POST Request to Replicate API

Type / Role
n8n-nodes-base.httpRequest - httpRequest
Config choices
Version 4.4

Block 7 - GET Request to check status

Type / Role
n8n-nodes-base.httpRequest - httpRequest
Config choices
Version 4.4

Block 8 - Check if finished

Type / Role
n8n-nodes-base.if - if
Config choices
Version 2.3

Block 9 - Check for errors

Type / Role
n8n-nodes-base.if - if
Config choices
Version 2.3

Block 10 - Retrieve Image

Type / Role
n8n-nodes-base.httpRequest - httpRequest
Config choices
Version 4.4

Block 11 - Sticky Note1

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 12 - Sticky Note2

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 13 - Sticky Note3

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 14 - Sticky Note4

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 15 - Sticky Note6

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 16 - Sticky Note7

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 17 - Sticky Note10

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 18 - Sticky Note11

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 19 - Isolate output URL

Type / Role
n8n-nodes-base.set - set
Config choices
Version 3.4

3. Summary Table

Workflow Enhance images with Riverflow 2.0 reference-based super-resolution via Replicate
Complexity advanced
Nodes 19
Categories Content Creation, Multimodal AI
Author Joel Sage
Published 11 Feb 2026

4. Reproducing the Workflow from Scratch

  1. 1. Download the workflow JSON

    Use the JSON export at /data/workflows/13306/13306.json as the source template for this automation.

  2. 2. Import the template into n8n

    Open n8n, import the downloaded JSON, and review each node before activating the workflow.

  3. 3. Configure credentials and variables

    Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.

  4. 4. Test with sample data

    Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.

  5. 5. Activate and monitor

    Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Frequently asked questions

What does Enhance images with Riverflow 2.0 reference-based super-resolution via Replicate do?

How it works This workflow can take an image URL and enhance said image using Riverflow 2.0 Reference Based Super Resolution . This process involves giving the model an ...

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Content Creation, Multimodal AI use case.