Mirrors/blakeblackshear.frigate
1
0
Fork 0
mirror of https://github.com/blakeblackshear/frigate.git synced 2024-11-21 19:07:46 +01:00
Code Issues Projects Releases Wiki Activity

clarify semantic search and genai docs (#13637)

Browse Source
This commit is contained in:
Josh Hawkins 2024-09-09 11:23:21 -05:00 committed by GitHub
parent f5dbcd5465
commit 03ff3e639f
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
2 changed files with 14 additions and 10 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

6
docs/docs/configuration/genai.md
View File

@ -3,7 +3,7 @@ id: genai
title: Generative AI
---
Generative AI can be used to automatically generate descriptions based on the thumbnails of your events. This helps with [semantic search](/configuration/semantic_search) in Frigate by providing detailed text descriptions as a basis of the search query.
Generative AI can be used to automatically generate descriptions based on the thumbnails of your tracked objects. This helps with [Semantic Search](/configuration/semantic_search) in Frigate by providing detailed text descriptions as a basis of the search query.
## Configuration
@ -100,7 +100,7 @@ genai:
## Custom Prompts
Frigate sends multiple frames from the detection along with a prompt to your Generative AI provider asking it to generate a description. The default prompt is as follows:
Frigate sends multiple frames from the tracked object along with a prompt to your Generative AI provider asking it to generate a description. The default prompt is as follows:
```
Describe the {label} in the sequence of images with as much detail as possible. Do not describe the background.
@ -108,7 +108,7 @@ Describe the {label} in the sequence of images with as much detail as possible.
:::tip
Prompts can use variable replacements like `{label}`, `{sub_label}`, and `{camera}` to substitute information from the detection as part of the prompt.
Prompts can use variable replacements like `{label}`, `{sub_label}`, and `{camera}` to substitute information from the tracked object as part of the prompt.
:::

18
docs/docs/configuration/semantic_search.md
View File

@ -3,7 +3,9 @@ id: semantic_search
title: Using Semantic Search
---
Semantic search works by embedding images and/or text into a vector representation identified by numbers. Frigate has support for two such models which both run locally: [OpenAI CLIP](https://openai.com/research/clip) and [all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2). Embeddings are then saved to a local instance of [ChromaDB](https://trychroma.com).
The Search feature in Frigate allows you to find tracked objects within your review items using either the image itself, a user-defined text description, or an automatically generated one. This semantic search functionality works by creating _embeddings_ — numerical vector representations — for both the images and text descriptions of your tracked objects. By comparing these embeddings, Frigate assesses their similarities to deliver relevant search results.
Frigate has support for two models to create embeddings, both of which run locally: [OpenAI CLIP](https://openai.com/research/clip) and [all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2). Embeddings are then saved to a local instance of [ChromaDB](https://trychroma.com).
## Configuration
@ -17,22 +19,24 @@ semantic_search:
:::tip
The embeddings database can be re-indexed from the existing detections in your database by adding `reindex: True` to your `semantic_search` configuration. Depending on the number of detections you have, it can take up to 30 minutes to complete and may max out your CPU while indexing. Make sure to set the config back to `False` before restarting Frigate again.
The embeddings database can be re-indexed from the existing tracked objects in your database by adding `reindex: True` to your `semantic_search` configuration. Depending on the number of tracked objects you have, it can take a long while to complete and may max out your CPU while indexing. Make sure to set the config back to `False` before restarting Frigate again.
If you are enabling the Search feature for the first time, be advised that Frigate does not automatically index older tracked objects. You will need to enable the `reindex` feature in order to do that.
:::
### OpenAI CLIP
This model is able to embed both images and text into the same vector space, which allows `image -> image` and `text -> image` similarity searches. Frigate uses this model on detections to encode the thumbnail image and store it in Chroma. When searching detections via text in the search box, frigate will perform a `text -> image` similarity search against this embedding. When clicking "FIND SIMILAR" next to a detection, Frigate will perform an `image -> image` similarity search to retrieve the closest matching thumbnails.
This model is able to embed both images and text into the same vector space, which allows `image -> image` and `text -> image` similarity searches. Frigate uses this model on tracked objects to encode the thumbnail image and store it in Chroma. When searching for tracked objects via text in the search box, Frigate will perform a `text -> image` similarity search against this embedding. When clicking "Find Similar" in the tracked object detail pane, Frigate will perform an `image -> image` similarity search to retrieve the closest matching thumbnails.
### all-MiniLM-L6-v2
This is a sentence embedding model that has been fine tuned on over 1 billion sentence pairs. This model is used to embed detection descriptions and perform searches against them. Descriptions can be created and/or modified on the search page when clicking on the info icon next to a detection. See [the Generative AI docs](/configuration/genai.md) for more information on how to automatically generate event descriptions.
This is a sentence embedding model that has been fine tuned on over 1 billion sentence pairs. This model is used to embed tracked object descriptions and perform searches against them. Descriptions can be created, viewed, and modified on the Search page when clicking on the gray tracked object chip at the top left of each review item. See [the Generative AI docs](/configuration/genai.md) for more information on how to automatically generate event descriptions.
## Usage Tips
## Usage
1. Semantic search is used in conjunction with the other filters available on the search page. Use a combination of traditional filtering and semantic search for the best results.
1. Semantic search is used in conjunction with the other filters available on the Search page. Use a combination of traditional filtering and semantic search for the best results.
2. The comparison between text and image embedding distances generally means that results matching `description` will appear first, even if a `thumbnail` embedding may be a better match. Play with the "Search Type" filter to help find what you are looking for.
3. Make your search language and tone closely match your descriptions. If you are using thumbnail search, phrase your query as an image caption.
4. Semantic search on thumbnails tends to return better results when matching large subjects that take up most of the frame. Small things like "cat" tend to not work well.
5. Experiment! Find a detection you want to test and start typing keywords to see what works for you.
5. Experiment! Find a tracked object you want to test and start typing keywords to see what works for you.