QWEN IMAGE LAYERED

Qwen Image Layered is an image-text-to-image model developed by fal.ai, specifically engineered to decompose a single input image into multiple RGBA layers. This model facilitates advanced image processing by breaking down complex visuals into discrete components, each with its own transparency and color information. Such layered decomposition is highly useful in applications that demand granular control over image elements, such as digital art creation, graphic editing, and compositing workflows.

The model operates by accepting both images and text-based captions as inputs. Image inputs are delivered via URL and can be in formats like jpg, jpeg, png, webp, gif, or avif. The text input, referred to as a prompt, serves as a caption or creative guide, while an optional negative prompt can be used to discourage specific features in the output. Qwen Image Layered can be configured to output up to 10 layers per input image, with the default set to 4, thereby allowing users to customize the granularity of the decomposition process.

Technically, the model exposes a range of parameters to fine-tune performance. Users can select the level of acceleration from options like “none,” “regular,” or “high,” influencing the inference speed. The ‘guidance scale’ parameter, with a range from 1 to 20 (default at 5), allows further control over how closely the output follows the input prompt. The ‘number of inference steps’ parameter, defaulted to 28 and adjustable between 1 and 50, determines the iterative refinement process, potentially affecting output quality and detail. An optional ‘seed’ value enables deterministic outputs – using the same image, prompt, and seed will yield the same layered result every time, which is crucial for reproducibility in professional workflows.

Output formats supported are png and webp, ensuring compatibility with standard graphic tools and pipelines. Once the model completes processing, it generates a JSON response containing URLs to each resultant image layer, along with a Boolean array indicating whether any Not Safe For Work (NSFW) content was detected in each layer (if the safety checker is enabled—on by default).

The model includes a safety checker to help ensure outputs meet content safety standards. Users have the option to toggle this feature as required for their use case. Additionally, a synchronous mode is available that returns media as a data URI, which is beneficial for workflows where immediate processing is needed without storing the images in request history.

Qwen Image Layered is designed for flexibility and detailed image analysis, making it a strong fit for creative professionals, graphic designers, and developers who require programmatic access to layered image data. The model is accessible via a web-based playground interface and through a documented API, allowing straightforward integration into diverse digital pipelines. While the model's documentation does not elaborate on performance metrics such as speed or resolution or enumerate limitations beyond configurable parameters and format requirements, users are provided with sufficient options to tailor outputs to their needs within those documented boundaries.

Best practices include selecting appropriate numbers of layers based on the complexity of the source image and desired separation detail, using seeds for reproducible batch processing, and enabling the safety checker when content filtering is necessary. The model's ability to accept a wide range of image formats and its customizable feature set make it a versatile tool for a variety of image editing and analytical scenarios.