infinite-image-browsing
A full-featured image/video management app with AI-powered organization and semantic search. Supports metadata from SD-webui, ComfyUI, Fooocus, NovelAI, StableSwarmUI, and more. Available as standalone app, SD-webui extension, or library.
Stars: 1254
Infinite Image Browsing (IIB) is a versatile tool that offers excellent performance in displaying images, supports image search and favorite functionalities, allows viewing images/videos with various features like full-screen preview and sending to other tabs, provides multiple usage methods including extension installation, standalone Python usage, and desktop application, supports TikTok-style view, walk mode for automatic loading of folders, preview based on file tree structure, image comparison, topic/tag analysis, smart file organization, multilingual support, privacy and security features, packaging/batch download, keyboard shortcuts, and AI integration. The tool also offers natural language categorization and search capabilities, with API endpoints for embedding, clustering, and prompt retrieval. It supports caching and incremental updates for efficient processing and offers various configuration options through environment variables.
README:
๐ i18n Advisory: Some translations may be incomplete or inaccurate. Pull requests are welcome for improvements!
๐ Try our application online at: http://39.105.110.128:0721. This is my idle 2c2g3m cloud server without CDN.
ไธญๆๆๆกฃ Change log Installation / Running
| Software | Support | Provided by |
|---|---|---|
| Stable Diffusion web UI | Supported | Built-in |
| Stable Diffusion web UI (Stealth) | Supported (default: disabled) | Built-in |
| ComfyUI | Partially supported | Built-in |
| Fooocus | Supported | Built-in |
| NovelAI | Supported | Built-in |
| StableSwarmUI | Supported | Built-in |
| Invoke.AI | Supported | Built-in |
| Pixiv | Supported | pixiv_iib_plugin |
If you would like to support more software, please refer to: parsers or pixiv_iib_plugin
- Once caching is generated, images can be displayed in just a few milliseconds.
- Images are displayed with thumbnails by default, with a default size of 512 pixels. You can adjust the thumbnail resolution on the global settings page.
- You can also control the width of the grid images, allowing them to be displayed in widths ranging from 64px to 1024px.
- Supports pre-generating thumbnails and video covers to improve performance using
--generate_video_coverand--generate_image_cache. - Supports specifying the cache directory through the
IIB_CACHE_DIRenvironment variable.
- The prompt, model, Lora, and other information will be converted into tags and sorted by frequency of use for precise searching.
- Supports tag autocomplete, auto-translation, and customization.
- Image favorite can be achieved by toggling custom tags for images in the right-click menu.
- Support for advanced search similar to Google
- Also supports fuzzy search, you can search by a part of the filename or generated information.
- Support adding custom search paths for easy management of folders created by the user.
- Media type filtering, video tag search, and random sort.
- Auto-tagging with custom rules.
- Supports viewing image generation information. Also supported in full-screen preview mode.
- EXIF/metadata is integrated in full-screen preview with nested JSON navigation and highlighting.
- Supports sending images to other tabs and third-party extensions such as ControlNet , openOutpaint.
- Support full-screen preview and enable custom shortcut key operations while in full-screen preview mode.
- Support navigating to the previous or next image in full-screen preview mode by pressing arrow keys or clicking buttons.
- Support playing video files from a remote server.
- You can install it as an extension on SD-webui.
- You can run it independently using Python.
- The desktop app version is also available.
- Supports multiple popular AI software.
- NEW: Use with AI agents (Claude Code, Cursor, OpenClaw, etc.)
- TikTok-style vertical browsing for images and videos.
- Polished info panel with backdrop/preview return improvements.
- Delete events stay in sync across the TikTok view.
- Automatically load the next folder
(similar to os.walk), allowing you to browse all images without paging. - Tested to work properly with over 27,000 files.
- When there are folders, you can switch to walk mode from other modes by clicking the walk button in the upper right corner. It will flatten all the folders, avoiding the tedious operation of going in and out of folders.
- Supports file tree-based preview.
- Supports automatic refreshing.
- Supports basic file operations, such as multiple selection for deleting/moving/copying, and creating new folders.
- Hold down the Ctrl, Shift, or Cmd key to select multiple items.
- Supported multi-select operations include: delete, move, copy, pack download, add tags, remove tags, move to another folder, copy to another folder, drag and drop.
- You can keep the multi-select state by clicking the "Keep Multi-Select" button in the lower right corner, allowing you to perform multiple operations on the selected file collection conveniently.
- Drag-and-drop into folders and safer move/copy (continue on error).
- Provides a side-by-side comparison of two images.
- Provides a comparison of image generation information at the same time.
- Tag relationship graph visualization for topic clusters.
AI-powered automatic file organization
- Semantic Clustering: Automatically groups similar images based on prompt semantics using AI embeddings
- Auto-Generated Folder Names: AI generates meaningful folder names in your preferred language
- Preview Before Action: Review the proposed organization before confirming - skip or adjust as needed
- Background Processing: Large folders are processed in the background, you can continue working
- Flexible Options: Choose between move or copy, set minimum cluster size, include subfolders recursively
Requirements: Same as Topic Search - requires
OPENAI_BASE_URL,OPENAI_API_KEY, and Python dependenciesnumpy,hnswlib๐ธ See Smart Organize Preview below for screenshots and video demo.
- Currently supports Simplified Chinese/Traditional Chinese/English/German.
- If you would like to add a new language, please refer to i18n.ts and submit the relevant code.
- Supports custom secret key for authentication.
- Supports configuring access control for the file system, which will be enabled by default when the service allows public access (Only when used as an extension of sd-webui).
- Supports customizing the allowed paths for access control.
- Supports controlling access permissions. You can run IIB in read-only mode.
- Click here to see details
- Allows you to download multiple images at once.
- The data source can be search results, a regular image grid view page, walk mode, etc. Images can be added to the processing list through drag-and-drop or "Send To".
- Allows for deleting and adding/removing tags, with customizable trigger buttons in the global settings page.
If you like this project and find it helpful, please consider giving it a โญ๏ธ. This would be very important for me to continue developing and maintaining this project. If you have any suggestions or ideas, please feel free to raise them in the issue section, and I will respond as soon as possible. Thank you again for your support!
- Open the
Extensionstab in SD-webui. - Select the
Install from URLoption. - Enter
https://github.com/zanllp/sd-webui-infinite-image-browsing. - Click on the
Installbutton. - Wait for the installation to complete and click on
Apply and restart UI.
Refer to Can the extension function without the web UI?
If you need to view images generated by ComfyUI/Fooocus/NovelAI, please refer to https://github.com/zanllp/sd-webui-infinite-image-browsing/issues/202.
If you need a Dockerfile, you can refer to this link. https://github.com/zanllp/sd-webui-infinite-image-browsing/discussions/366
The executable version also supports ComfyUI/Fooocus/NovelAI.
Download and install the program from the releases section on the right-hand side of the repository page.
If the antivirus detects a virus, it can be ignored as a false positive. There are two versions of the compiled version for Windows, with the pyinstaller version having a lower false positive rate.
If you need to compile it yourself, please refer to https://github.com/zanllp/sd-webui-infinite-image-browsing/blob/main/.github/workflows/tauri_app_build.yml.
Use iframe to access IIB and use it as a file browser for your application. Refer to https://github.com/zanllp/sd-webui-infinite-image-browsing/blob/main/vue/usage.md
IIB can be used with AI agents like Claude Code, Cursor, and OpenClaw. See AI Agents Documentation for details.
During the first use, you need to click and wait for the index generation. For my case with 20,000 images, it took about 45 seconds (with an AMD 5600X CPU and PCIe SSD). For subsequent uses, it will check whether there are changes in the folder, and if so, it needs to regenerate the index. Usually, this process is very fast.
Image search supports translation, see https://github.com/zanllp/sd-webui-infinite-image-browsing/issues/39 for more detail. Feel free to share files for other languages to facilitate everyone's use.

In full-screen preview mode, you can also view image information and perform operations on the context menu. It supports dragging, resizing and expanding/collapsing .
If you, like me, don't need to view the generation information, you can choose to simply minimize this panel, and all contextual operations will still be available.
You can also trigger it by hovering your mouse over the icon in the top right corner.
AI-powered automatic file organization - groups similar images and creates meaningful folders.
https://github.com/user-attachments/assets/c1279556-d255-4e71-b230-48523a4859bf
This feature groups images by semantic similarity of prompts and supports natural-language retrieval (similar to the retrieval stage in RAG). Itโs experimental: results depend on the embedding/chat models and the quality of prompt metadata.
- Open โNatural Language Categorization & Search (Experimental)โ from the startup page
- Click Scope and select one or more folders (from QuickMovePaths)
- Categorize: click Refresh to generate topic cards for the selected scope
- Search: type a natural-language query and click Search (auto-opens the result grid)
The selected scope is persisted in backend KV:
app_fe_setting["topic_search_scope"]. Next time it will auto-restore and auto-refresh once.
-
Build/refresh embeddings:
POST /infinite_image_browsing/db/build_iib_output_embeddings- Request:
folder,model,force,batch_size,max_chars
- Request:
-
Cluster (categorize):
POST /infinite_image_browsing/db/cluster_iib_output_job_startthen pollGET /infinite_image_browsing/db/cluster_iib_output_job_status?job_id=...- Request:
folder_paths(required, array),threshold,min_cluster_size,force_embed,title_model,force_title,use_title_cache,assign_noise_threshold,lang
- Request:
-
Prompt retrieval (RAG-like):
POST /infinite_image_browsing/db/search_iib_output_by_prompt- Request:
query,folder_paths(required, array),top_k,min_score,ensure_embed,model,max_chars
- Request:
-
1) Prompt extraction & normalization
- Reads
image.exifand keeps content beforeNegative prompt: - Optionally removes โboilerplateโ terms (quality/photography parameters, etc.) to focus on topic semantics (
IIB_PROMPT_NORMALIZE*)
- Reads
-
2) Embeddings
- Calls OpenAI-compatible
/embeddings - Stores vectors in SQLite table
image_embedding(incremental, to avoid repeated costs)
- Calls OpenAI-compatible
-
3) Clustering
- Online centroid-sum clustering, plus a post-merge step for highly similar clusters
- Optionally reassigns members of small clusters into the closest large cluster to reduce noise
-
4) Title generation (LLM)
- Calls
/chat/completionswith tool/function calling to force structured JSON output - Stores titles/keywords in SQLite table
topic_title_cache
- Calls
-
5) Retrieval
- Embeds the query and ranks images in the selected scope by cosine similarity, returning TopK
-
Where: table
image_embedding(keyed byimage_id) -
Skip rule (incremental update): an image is skipped if:
- same
model - same
text_hash - existing
vecis present
- same
-
Re-vectorization cache key:
text_hash = sha256(f"{normalize_version}:{prompt_text}")-
prompt_textis the extracted + (optionally) normalized text used for embeddings -
normalize_versionis a code-derived fingerprint of normalization rules/mode (not user-configurable)
-
-
Force rebuild: pass
force=truetobuild_iib_output_embeddingsorforce_embed=truetocluster_iib_output_job_start
-
Where: table
topic_title_cachekeyed bycluster_hash -
Hit rule: when
use_title_cache=trueandforce_title=false, titles/keywords are reused -
Cache key (
cluster_hash) includes:- member image IDs (sorted)
- embedding
model,threshold,min_cluster_size -
title_model, outputlang - normalization fingerprint (
normalize_version) and mode
-
Force title regeneration:
force_title=true
All calls use an OpenAI-compatible provider:
-
OPENAI_BASE_URL: e.g.https://your-host/v1 -
OPENAI_API_KEY: your API key -
EMBEDDING_MODEL: embeddings model used for clustering -
AI_MODEL: default chat model (fallback) -
TOPIC_TITLE_MODEL: chat model used for cluster titles (falls back toAI_MODEL) -
IIB_PROMPT_NORMALIZE:1/0enable prompt normalization -
IIB_PROMPT_NORMALIZE_MODE:balanced(recommended) /theme_only
Note: There is no mock fallback for AI calls. If the provider/model fails or returns invalid output, the API will return an error directly.
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