fofr/color-matcher - AI Image Tools Tool

Overview

fofr/color-matcher is a lightweight image color-correction model hosted on Replicate that provides automated color matching and white-balance correction via an API. The model is designed to automatically adjust an input image's color cast and overall balance so images appear more neutral and visually consistent. According to the Replicate listing (https://replicate.com/fofr/color-matcher), the service is offered as an inference endpoint you can call from web services, batch pipelines, or client applications. The Replicate listing focuses on its core capabilities—automatic white-balance correction and color matching—rather than on extensive configuration or training details. The model is targeted at use cases such as photo post-processing, product photography consistency, and automated preprocessing for computer-vision pipelines. The Replicate page does not list public performance benchmarks or pricing details on the model page, so implementation details (latency, throughput, exact input/output schema) should be validated directly from the model page or by invoking the model in a test environment.

Key Features

• Automatic white-balance correction to neutralize color casts in photos
• Color matching to produce more consistent tones across images
• Accessible via Replicate API for integration into web or backend pipelines
• Simple input/output workflow suitable for single-image processing
• Useful for photography, e-commerce, and preprocessing for vision models

Example Usage

Example (python):

import replicate
import requests

# Replace REPLACE_WITH_MODEL_VERSION with the model version string from the Replicate page
# See: https://replicate.com/fofr/color-matcher for the model version id
MODEL = "fofr/color-matcher:REPLACE_WITH_MODEL_VERSION"
INPUT_IMAGE_URL = "https://example.com/input.jpg"

# Run the model (ensure REPLICATE_API_TOKEN is set in your environment)
# You can also pass api_token to Client if needed.
result = replicate.run(MODEL, input={"image": INPUT_IMAGE_URL})

# The model may return a single URL or a list of URLs. Handle both cases.
output_urls = result if isinstance(result, list) else [result]

for i, url in enumerate(output_urls, start=1):
    r = requests.get(url)
    r.raise_for_status()
    filename = f"output_{i}.jpg"
    with open(filename, "wb") as f:
        f.write(r.content)
    print(f"Saved adjusted image to {filename}")

# Note: Replace the MODEL variable's version id with the specific version shown
# on the Replicate model page. Input/output formats and optional parameters
# may vary; consult the model's Replicate page for exact field names and options.

Key Information

• Category: Image Tools
• Type: AI Image Tools Tool