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Qwen Image Edit Plus Lora Gallery Image to Image

fal-ai/qwen-image-edit-plus-lora-gallery/remove-element
Remove unwanted elements (objects, people, text) while maintaining image consistency
Inference
Commercial use

About

Qwen-Image-Edit-Remover-General-LoRA - Remove unwanted elements from images

This endpoint cleanly removes specified elements (objects, people, text, etc.) from images while:

  • Maintaining the consistency and quality of the rest of the image
  • Automatically filling in the removed areas naturally
  • Preserving the original image style and composition

Perfect for:

  • Removing unwanted objects or people from photos
  • Cleaning up product images (remove text, logos, watermarks)
  • E-commerce image editing (remove background clutter)
  • Photo retouching and restoration

Works with: Objects, people, text, logos, and other visual elements The model maintains high fidelity of the remaining image content.

Based on: https://huggingface.co/starsfriday/Qwen-Image-Edit-Remover-General-LoRA

1. Calling the API#

Install the client#

The client provides a convenient way to interact with the model API.

npm install --save @fal-ai/client

Setup your API Key#

Set FAL_KEY as an environment variable in your runtime.

export FAL_KEY="YOUR_API_KEY"

Submit a request#

The client API handles the API submit protocol. It will handle the request status updates and return the result when the request is completed.

import { fal } from "@fal-ai/client";

const result = await fal.subscribe("fal-ai/qwen-image-edit-plus-lora-gallery/remove-element", {
  input: {
    image_urls: ["https://v3b.fal.media/files/b/elephant/oWup_Q7zuvbfB4en-hneO_5aaa1cb3d3eb44999005159e82e7c9b7.png"]
  },
  logs: true,
  onQueueUpdate: (update) => {
    if (update.status === "IN_PROGRESS") {
      update.logs.map((log) => log.message).forEach(console.log);
    }
  },
});
console.log(result.data);
console.log(result.requestId);

2. Authentication#

The API uses an API Key for authentication. It is recommended you set the FAL_KEY environment variable in your runtime when possible.

API Key#

In case your app is running in an environment where you cannot set environment variables, you can set the API Key manually as a client configuration.
import { fal } from "@fal-ai/client";

fal.config({
  credentials: "YOUR_FAL_KEY"
});

3. Queue#

Submit a request#

The client API provides a convenient way to submit requests to the model.

import { fal } from "@fal-ai/client";

const { request_id } = await fal.queue.submit("fal-ai/qwen-image-edit-plus-lora-gallery/remove-element", {
  input: {
    image_urls: ["https://v3b.fal.media/files/b/elephant/oWup_Q7zuvbfB4en-hneO_5aaa1cb3d3eb44999005159e82e7c9b7.png"]
  },
  webhookUrl: "https://optional.webhook.url/for/results",
});

Fetch request status#

You can fetch the status of a request to check if it is completed or still in progress.

import { fal } from "@fal-ai/client";

const status = await fal.queue.status("fal-ai/qwen-image-edit-plus-lora-gallery/remove-element", {
  requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b",
  logs: true,
});

Get the result#

Once the request is completed, you can fetch the result. See the Output Schema for the expected result format.

import { fal } from "@fal-ai/client";

const result = await fal.queue.result("fal-ai/qwen-image-edit-plus-lora-gallery/remove-element", {
  requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b"
});
console.log(result.data);
console.log(result.requestId);

4. Files#

Some attributes in the API accept file URLs as input. Whenever that's the case you can pass your own URL or a Base64 data URI.

Data URI (base64)#

You can pass a Base64 data URI as a file input. The API will handle the file decoding for you. Keep in mind that for large files, this alternative although convenient can impact the request performance.

Hosted files (URL)#

You can also pass your own URLs as long as they are publicly accessible. Be aware that some hosts might block cross-site requests, rate-limit, or consider the request as a bot.

Uploading files#

We provide a convenient file storage that allows you to upload files and use them in your requests. You can upload files using the client API and use the returned URL in your requests.

import { fal } from "@fal-ai/client";

const file = new File(["Hello, World!"], "hello.txt", { type: "text/plain" });
const url = await fal.storage.upload(file);

Read more about file handling in our file upload guide.

5. Schema#

Input#

image_urls list<string>* required

The URL of the image containing elements to remove.

image_size ImageSize | Enum

The size of the generated image. If not provided, the size of the final input image will be used.

Possible enum values: square_hd, square, portrait_4_3, portrait_16_9, landscape_4_3, landscape_16_9

Note: For custom image sizes, you can pass the width and height as an object:

"image_size": {
  "width": 1280,
  "height": 720
}
guidance_scale float

The CFG (Classifier Free Guidance) scale. Controls how closely the model follows the prompt. Default value: 1

num_inference_steps integer

The number of inference steps to perform. Default value: 6

acceleration AccelerationEnum

Acceleration level for image generation. 'regular' balances speed and quality. Default value: "regular"

Possible enum values: none, regular

negative_prompt string

The negative prompt for the generation Default value: " "

seed integer

Random seed for reproducibility. Same seed with same prompt will produce same result.

sync_mode boolean

If True, the media will be returned as a data URI and won't be saved in history.

enable_safety_checker boolean

Whether to enable the safety checker for the generated image. Default value: true

output_format OutputFormatEnum

The format of the output image Default value: "png"

Possible enum values: png, jpeg, webp

num_images integer

Number of images to generate Default value: 1

prompt string

Specify what element(s) to remove from the image (objects, people, text, etc.). The model will cleanly remove the element while maintaining consistency of the rest of the image. Default value: "Remove the specified element from the scene"

lora_scale float

The scale factor for the LoRA model. Controls the strength of the LoRA effect. Default value: 1

{
  "image_urls": [
    "https://v3b.fal.media/files/b/elephant/oWup_Q7zuvbfB4en-hneO_5aaa1cb3d3eb44999005159e82e7c9b7.png"
  ],
  "guidance_scale": 1,
  "num_inference_steps": 6,
  "acceleration": "regular",
  "negative_prompt": " ",
  "enable_safety_checker": true,
  "output_format": "png",
  "num_images": 1,
  "prompt": "Remove the person from the image",
  "lora_scale": 1
}

Output#

images list<Image>* required

The generated/edited images

seed integer* required

The seed used for generation

{
  "images": [
    {
      "url": "https://v3b.fal.media/files/b/koala/dTldnOpRSFVBvWiyfOeO1.png"
    }
  ]
}

Other types#

Image#

url string* required

The URL where the file can be downloaded from.

content_type string

The mime type of the file.

file_name string

The name of the file. It will be auto-generated if not provided.

file_size integer

The size of the file in bytes.

file_data string

File data

width integer

The width of the image in pixels.

height integer

The height of the image in pixels.

ImageSize#

width integer

The width of the generated image. Default value: 512

height integer

The height of the generated image. Default value: 512

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