From 82c4ef035af556ce9589bec3a7f86773774aa0f4 Mon Sep 17 00:00:00 2001 From: Loris Sauter Date: Fri, 5 Jul 2024 14:54:43 +0200 Subject: [PATCH] README-ified the README --- README.md | 1037 +++------------------------------------- images/vengine-256.png | Bin 0 -> 12934 bytes images/vengine-512.png | Bin 0 -> 27718 bytes images/vitrivr_256.png | Bin 0 -> 9551 bytes images/vitrivr_512.png | Bin 0 -> 76376 bytes 5 files changed, 55 insertions(+), 982 deletions(-) create mode 100755 images/vengine-256.png create mode 100755 images/vengine-512.png create mode 100755 images/vitrivr_256.png create mode 100755 images/vitrivr_512.png diff --git a/README.md b/README.md index d87b42e8..4f4a8303 100644 --- a/README.md +++ b/README.md @@ -1,12 +1,52 @@ -# vitrivr engine + + + + +
+
+ + vitrivr log


+ vitrivr-engine logo + +
+
+ +[![GitHub Release](https://img.shields.io/github/release/vitrivr/vitrivr-engine?include_prereleases=&sort=semver&color=blue&style=for-the-badge&label=Release)](https://github.com/vitrivr/vitrivr-engine/releases) +[![License](https://img.shields.io/badge/License-MIT-blue?style=for-the-badge)](#license) +[![issues - vitrivr-engine](https://img.shields.io/github/issues/vitrivr/vitrivr-engine?style=for-the-badge)](https://github.com/vitrivr/vitrivr-engine/issues) [vitrivr](https://vitrivr.org)'s next-generation retrieval engine. + +[Read The Docs](https://github.com/vitrivr/vitrivr-engine/wiki) + +
+ +## vitrivr-engine + +vitrivr-engine is [vitrivr](https://vitrivr.org)'s next generation retrieval engine with a flexible, modular architecture. Based on the experiences with its predecessor, [Cineast](https://github.com/vitrivr/cineast), -vitrivr engine's data model, ingestion pipeline and retrieval logic have been reworked. +vitrivr engine's data model, ingestion pipeline and retrieval logic have been reworked from the ground. +Essentially, vitrivr-engine enables the analysis (i.e. ingestion) and querying (i.e. retrieval ) of +multimedia data. + +## Built With + +* [Kotlin](https://kotlinlang.org) for the JVM, e.g. [OpenJDK](https://openjdk.org/) +* [OpenApi](https://www.openapis.org/) +* [CottontailDB](https://github.com/vitrivr/CottontailDB) +* ... and more ... + +## Getting Started + +See [Getting Started](https://github.com/vitrivr/vitrivr-engine/wiki/Getting-Started) + +## Usage + +See [Example](https://github.com/vitrivr/vitrivr-engine/wiki/Example) ## Project Structure -The project is set up as a multimodule Kotlin project: +The project is set up as a multi-module Kotlin project: | Module | Description | Maven Dependency | |-----------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------| @@ -19,987 +59,20 @@ The project is set up as a multimodule Kotlin project: | [`vitrivr-engine-module-fes`](https://github.com/vitrivr/vitrivr-engine//vitrivr-engine-module-fes) | Extension that can be used to harnes feature extraction provided by an external ML model server. **Requires local generation of bindings:** `./gradlew :vitrivr-engine-module-fes:generateFESClient` | Yes | | [`vitrivr-engine-server`](https://github.com/vitrivr/vitrivr-engine//vitrivr-engine-server) | A [Javalin](https://javalin.io) powered server providing an [OpenApi](https://openapis.org) [documented REST API](vitrivr-engine-server/doc/oas.json) for both, ingestion and querying and a CLI, essentially the runtime of the project | No | -## Getting Started: Usage - -vitrivr engine is a Kotlin project and hence requires a JDK (e.g. [OpenJDK](https://openjdk.org/)) to properly run. -Furthermore, we use [Gradle](https://gradle.org) in order to facilitate the building and deployment -through the Gradle wrapper. - -In the context of retrieval, often times a distinction of _indexing_ / _ingestion_ (also known as _offline phase_) -and _querying_ / _retrieval_ (also known as _online phase_) is made. -While the former addresses (multimedia) content to be analysed and indexed, i.e. made ready for search, is the latter's purpose to -search within the previously built index. - -### Indexing / Ingestion - -The most essential prerequisite for the ingestion is the existence of multimedia content. -For the sake of this example, let's assume the existence of such multimedia content in the form of image and video files. - -Also, since vitrivr engine is highly configurable, the first few steps involve the creation of a suitable -configuration. - -#### Schema - -vitrivr-engine operates on the notion of _schema_, similarly to a database or a collection, -essentially providing, among other things, a namespace. -For this guide, we will have a single schema `sandbox`. - -Create a config file `sandbox-config.json` with one named schema in it: - -```json -{ - "schemas": [{ - "name": "sandbox" - }] -} -``` - -#### Database Connection - -The database is an important component of the system, since it allows for the persistence and lookup of descriptors. -The default database used by `vitrivr-engine` is [CottontailDB](https://github.com/vitrivr/cottontaildb) This guide assumes a running [CottontailDB](https://github.com/vitrivr/cottontaildb) -instance on the same machine on the default port `1865`. - ---- -**NOTE this requires [Cottontail 0.16.5](https://github.com/vitrivr/cottontaildb/releases/tag/0.16.5) or newer** ---- - -We address the database with the [`ConnectionConfig`](/vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/config/ConnectionConfig.kt): - -```json -{ - "database": "CottontailConnectionProvider", - "parameters": { - "Host": "127.0.0.1", - "port": "1865" - } -} -``` - -We add the cottontail connection to the schema's connection property: - -```json -{ - "schemas": [{ - "name": "sandbox", - "connection": { - "database": "CottontailConnectionProvider", - "parameters": { - "Host": "127.0.0.1", - "port": "1865" - } - } - }] -} -``` - -#### Schema Analyser - -The [`Analyser`](/vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/model/metamodel/Analyser.kt) -performs analysis to derive a [`Descriptor`](/vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/model/descriptor/Descriptor.kt). -In other words, the _analyser_ produces a _descriptor_ which represents the media content analysed. -However, this is only for _indexing_ / _ingestion_. During _querying_ / _retrieval_ time, -the _analyser_ queries the underlying storage layer to perform a query on said _descriptors_. - -#### Schema Field Configuration - -A schema consists of unique-named _fields_, that have to be backed by an [`Analyser`](/vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/model/metamodel/Analyser.kt), -essentially representing a specific [`Descriptor`](/vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/model/descriptor/Descriptor.kt). -This is configured using the [`FieldConfig`](/vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/config/FieldConfig.kt): - -```json -{ - "name": "uniqueName", - "factory": "FactoryClass", - "parameters":{ - "key": "value" - } -} -``` - -For images (and video frames), it might be worthwhile to use the average colour for representation purposes. -The built-in [`AverageColor`](/vitrivr-engine-plugin-features/src/main/kotlin/org/vitrivr/engine/base/features/averagecolor/AverageColor.kt) -analyser can be facilitated for this endeavour. -To use it, we specifically craft a corresponding _field config_: - -```json -{ - "name": "averagecolor", - "factory": "AverageColor" -} -``` - -There are no additional parameters, unlike, for instance, an [`ExternalAnalyser`](/vitrivr-engine-plugin-features/src/main/kotlin/org/vitrivr/engine/base/features/external/ExternalAnalyser.kt), -which requires the parameter `host` with an endpoint as value. - -For analysers that require a running [Feature Extraction Server](https://github.com/faberf/feature-extraction-server) (FES), the `host` parameter is required. Additionally, the `model` parameter may be used to specify a non-default model which should execute the task. Of course, this requires that the FES has the necessary plugins installed. See the [FES documentation](https://github.com/faberf/feature-extraction-server) for more information. - -- For [`ASR`](/vitrivr-engine-module-fes/src/main/kotlin/org/vitrivr/engine/base/features/external/implementations/ASR.kt) the analyser will perform automatic speech recognition on the audio content. -- For [`OCR`](/vitrivr-engine-module-fes/src/main/kotlin/org/vitrivr/engine/base/features/external/implementations/OCR.kt) the analyser will perform optical character recognition on the image content. -- For [`DenseEmbedding`](/vitrivr-engine-module-fes/src/main/kotlin/org/vitrivr/engine/base/features/external/implementations/DenseEmbedding.kt) the analyser will embed text / images as float vectors. Additionally, the `length` parameter is required to specify the length of the embedding. -- For [`ImageCaption`](/vitrivr-engine-module-fes/src/main/kotlin/org/vitrivr/engine/base/features/external/implementations/ImageCaption.kt) the analyser will generate a caption for the image content. Optionally, a `prompt` parameter can be used to specify a prompt for the caption generation. For example, the prompt could have the form `"Question: What is in the image? Answer:"`. -- For [`ImageClassification`](/vitrivr-engine-module-fes/src/main/kotlin/org/vitrivr/engine/base/features/external/implementations/ImageClassification.kt) the analyser will classify the image content. Additionally, the `classes` parameter is required, which should contain the classes to classify the image into, separated by commas. Optionally, the `top_k` and `threshold` parameters can be used to specify the number of top classes to return and the threshold for the classification. - - -Other fields are for (technical) metadata such as the [`FileSourceMetadata`](/vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/features/metadata/source/file/FileSourceMetadata.kt), -which additionally stores the file's path and size. - -For exif metadata, the [`ExifMetadata`](/vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/features/metadata/source/exif/ExifMetadata.kt) Analyser can be used. For each exif tag that should be included, a parameter with the name "{EXIF_DIRECTORY_NAME}_{TAG_NAME}" must be set to a type. Keys that do not match an exif tag via the aforementioned pattern are interpreted to be custom metadata tags that are stored in the exif UserComment tag in JSON format. Each parameter corresponds to a sub-field. Here is an example with custom "time_zone" metadata: -```json - { - "name": "exif", - "factory": "ExifMetadata", - "parameters": { - "ExifSubIFD_FocalLength": "INT", - "ExifSubIFD_ApertureValue": "FLOAT", - "ExifSubIFD_DateTimeOriginal": "DATETIME", - "ExifSubIFD_MeteringMode": "STRING", - "time_zone": "STRING" - } - } -``` -For extraction, the exif UserComment of images might look like this: -```json -{"time_zone": "Europe/Berlin", "hours_awake": 12} -``` - -Currently, there is no list of available fields and analysers, therefore a quick look into the code -reveals those existent. For basic (metadata), see in [the core module](/vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/features/), -for content-based features, see in [the features' module](/vitrivr-engine-plugin-features/src/main/kotlin/org/vitrivr/engine/base/features/). - -In this guide, we use the _average colour_ and _file source_ fields, which results in the (currently) following -configuration file: - -```json -{ - "schemas": [{ - "name": "sandbox", - "connection": { - "database": "CottontailConnectionProvider", - "parameters": { - "Host": "127.0.0.1", - "port": "1865" - } - }, - "fields": [ - { - "name": "averagecolor", - "factory": "AverageColor" - }, - { - "name": "file", - "factory": "FileSourceMetadata" - } - ] - }] -} -``` - -#### Schema Resolver Configuration - -Some data is stored e.g. on disk during extraction, which later will also be required during query time, -therefore the [`Resolver`](vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/resolver/Resolver.kt) -is configured as the [`ResolverConfig`](vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/config/schema/ResolverConfig.kt) -on the schema with a unique name. - -The [`ResolverConfig`](vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/config/schema/ResolverConfig.kt) describes such a configuration: - -```json -{ - "factory": "FactoryClass", - "parameters": { - "key": "value" - } -} -``` - -Specifically, the [`DiskResolver`](/vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/resolver/impl/DiskResolver.kt) is implemented and configured as such: - -```json -{ - "factory": "DiskResolver", - "parameters": { - "location": "./thumbnails/vitrivr" - } -} -``` - -Therefore, the _schema_ config is expanded with the _disk resolver_, named `disk`: - -```json -{ - "schemas": [{ - "name": "sandbox", - "connection": { - "database": "CottontailConnectionProvider", - "parameters": { - "Host": "127.0.0.1", - "port": "1865" - } - }, - "fields": [ - { - "name": "averagecolor", - "factory": "AverageColor" - }, - { - "name": "file", - "factory": "FileSourceMetadata" - } - ] - }], - "resolvers": { - "disk": { - "factory": "DiskResolver", - "parameters": { - "location": "./thumbnails/vitrivr" - } - } - } -} -``` - -#### Schema Exporter Configuration - -In the context of images and videos, having thumbnails is desirable, which can be generated -during ingestion with the configuration of an _exporter_. -Generally speaking, an _exporter_ exports an artifact based on the media content. - -The [`ExporterConfig`](/vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/config/ExporterConfig.kt) -describes such a configuration: - -```json -{ - "name": "uniqueName", - "factory": "FactoryClass", - "resolverName": "disk", - "parameters": { - "key": "value" - } -} -``` - -Specifically, the [`ThumbnailExporter`](/vitrivr-engine-index/src/main/kotlin/org/vitrivr/engine/index/exporters/ThumbnailExporter.kt), -can be configured as follows, which references a [`DiskResolver`](/vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/resolver/impl/DiskResolver.kt) named `disk`, see the previous section. - -```json -{ - "name": "thumbnail", - "factory": "ThumbnailExporter", - "resolverName": "disk", - "parameters": { - "maxSideResolution": "400", - "mimeType": "JPG" - } -} -``` - -Resulting in the following schema config: - -```json -{ - "schemas": [{ - "name": "sandbox", - "connection": { - "database": "CottontailConnectionProvider", - "parameters": { - "Host": "127.0.0.1", - "port": "1865" - } - }, - "fields": [ - { - "name": "averagecolor", - "factory": "AverageColor" - }, - { - "name": "file", - "factory": "FileSourceMetadata" - } - ], - "resolvers": { - "disk": { - "factory": "DiskResolver", - "parameters": { - "location": "./thumbnails/vitrivr" - } - } - }, - "exporters": [ - { - "name": "thumbnail", - "factory": "ThumbnailExporter", - "resolverName": "disk", - "parameters": { - "maxSideResolution": "400", - "mimeType": "JPG" - } - } - ] - }] -} -``` - -#### Extraction Pipeline Configuration - -In order to effectively support a specific _ingestion_ / _indexing_, we have to provide -a reference to the [`IndexConfig`](/vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/config/IndexConfig.kt), -which is configured as a [`PipelineConfig`](/vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/config/PipelineConfig.kt) within the schema config: - -```json -{ - "name": "pipelineName", - "path": "path/to/vbs-config-pipeline.json" -} -``` - -We will create said _index config_ later as `sandbox-pipeline.json`, hence, our schema config -is as follows: - -```json -{ - "schemas": [{ - "name": "sandbox", - "connection": { - "database": "CottontailConnectionProvider", - "parameters": { - "Host": "127.0.0.1", - "port": "1865" - } - }, - "fields": [ - { - "name": "averagecolor", - "factory": "AverageColor" - }, - { - "name": "file", - "factory": "FileSourceMetadata" - } - ], - "exporters": [ - { - "name": "thumbnail", - "factory": "ThumbnailExporter", - "resolver": { - "factory": "DiskResolver", - "parameters": { - "location": "./thumbnails/sandbox" - } - }, - "parameters": { - "maxSideResolution": "400", - "mimeType": "JPG" - } - } - ], - "extractionPipelines": [ - { - "name": "sandboxpipeline", - "path": "./sandbox-pipeline.json" - } - ] - }] -} -``` - -#### Index Pipeline Configuration - -Let's create a new file `sandbox-pipeline.json` right next to the `sandbox-config.json` in the root of the project. -This file will contain the [`IngestionConfig`](/vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/config/ingest/IngestionConfig.kt). - -In order to address (reference) our schema, we reference it in our index config and provide a _context_ as well as an _enumerator_: - -```json -{ - "schema": "sandbox", - "context": { - - }, - "enumerator": { - - } -} -``` - -#### Index Context Configuration - -An [`IngestionContextConfig`](/vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/context/IngestionContextConfig.kt) -is used to specify the _context_, additional information to the media data. -Specifically, a [`Resolver`](vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/resolver/Resolver.kt), `disk`, is referenced by its name from the _schema_ configuration. - -```json -{ - "contentFactory": "InMemoryContentFactory", - "resolverName": "disk", - "global": { - "key": "global-value" - }, - "local": { - "operator-name": { - "key": "local-value" - } - } -} -``` - -The [`Context`](vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/context/Context.kt) has two properties: `global` and `local`, which -enable local and global configuration in the form of key-value pairs. -However, `local`ly defined key-value pairs override their `global`ly defined counterpart. -In the above example, for the _operator_ (see further below), the key-value pair with the key `key` is also locally defined, -resulting in the value `local-value` to be used. However, a separate operator named other than `operator-name`, would get the value `global-value` -for the key `key`, as no local value is defined. -We refer to this part of the context, to the _context-parameters_. - -The example index pipeline configuration then, the current context looks as follow: - -```json -{ - "schema": "sandbox", - "context": { - "contentFactory": "InMemoryContentFactory", - "resolverName": "disk" - }, - "enumerator": { - - } -} -``` - -There are these special sections for the context-parameters: - -* `content` - For the local context-parameters for the _content factory_. - -#### Index Operators Configuration - -Next up, we declare a list of [operators](vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/operators/Operator.kt) in the form -of [`OperatorConfig`](vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/config/ingest/operator/OperatorConfig.kt)s. -These _operators_ must have a unique name in the `operators` property of the [`IngestionConfig`](vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/config/ingest/IngestionConfig.kt): -These names are used in the local context-parameters to configure them. - -```json -{ - "schema": "sandbox", - "context": { - "contentFactory": "InMemoryContentFactory", - "resolverName": "disk", - "local": { - "enumerator": { - "path": "./sandbox/imgs", - "mediaTypes": "IMAGE;VIDEO", - "depth": "1" - }, - "myoperator1": { - "key1": "a-value", - "key2": "1234" - } - } - }, - "operators": { - "myoperator1": {}, - "myoperator2": {} - } -} -``` - -There are different _types_ of operators: - -* [`Enumerator`](vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/operators/ingest/Enumerator.kt) enumerate and emit `Source`s to ingest from some data source (e.g., the file system). -* [`Decoder`](vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/operators/ingest/Decoder.kt) decode a `Source`s such that the `Content` becomes is available for ingestion (e.g., a video or image decoder). Create and emit `Retrievable`s. -* [`Transformer`](vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/operators/ingest/Segmenter.kt) transform incoming `Retrievable`s and emit 1 to n output `Retrievable`s (e.g., a video segmenter). Result in a 1:1 or 1:n mapping, depending - on the implementation. -* [`Extractor`](vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/operators/ingest/Extractor.kt) extract information from the `Retrievable` and their `Content` and typically append a `Descriptor` before emitting it. -* [`Exporter`](vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/operators/ingest/Exporter.kt) process `Retrievable`s and store external representation thereof (e.g., a preview image). -* [`Aggregator`](vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/operators/ingest/Aggregator.kt) aggregate incoming `Retrievable`s and emit - one [`Retrievable`](vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/model/retrievable/Retrievable.kt)s, resulting in an n:1 mapping. - -A minimal extraction pipeline requires at least an `Enumerator` and a `Decoder`. - -Notably, `Extractor`s are mostly backed by a schema's field, indicating that the `Descriptor` is being persisted. One can also instantiate `Extractor`s through their -factory, in which case the associated `Descriptor` is transient. `Exporter`s are also referenced by name from the _schema_. - -In the following, we briefly introduce these configurations: - -##### Index Operator Configuration: Enumerator - -The _enumerator_ enumerates the content to index and provides it to the indexing pipeline. -It is described with a [`EnumeratorConfig](/vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/config/ingest/operator/OperatorConfig.kt). - -Requires the property `mediaTypes`, a list of [`MediaType`](/vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/source/MediaType.kt)s. - -```json -{ - "type": "ENUMERATOR", - "factory": "FactoryClass", - "mediaTypes": ["IMAGE","VIDEO"] -} -``` - -Currently implemented enumerators are found [in the index module](/vitrivr-engine-index/src/main/kotlin/org/vitrivr/engine/index/enumerate), -of which we will use the [`FileSystemEnumerator`](/vitrivr-engine-index/src/main/kotlin/org/vitrivr/engine/index/enumerate/FileSystemEnumerator.kt). - -The configuration **requires** the context-parameter `path`, the path to the folder containing multimedia content. -Essentially, for still images, use `IMAGE` and for videos `VIDEO`. -Additional context-parameters are `skip` (how many files should be skipped), `limit` (how many files should at max be enumerated over) -and `depth` (the depth to traverse the file system, `1` stands for current folder only, `2` for sub-folders, `3` for sub-sub-folders, ...). -Let's assume we do have in the root project a folder `sandbox`, with two sub-folders `imgs` and `vids`: - -``` -/sandbox - | - - /imgs - | - - img1.png - | - - img2.png - | - - /vids - | - - vid1.mp4 -``` - -For an image only ingestion, we could set up the configuration as follows (`skip` and `limit` have sensible default values of `0` and `Integer.MAX_VALUE`, respectively): - -**Context**: -```json -{ - "contentFactory": "InMemoryContentFactory", - "resolverName": "disk", - "local": { - "enumerator": { - "path": "./your/media/path", - "depth": "1" - } - } -} -``` - -**Enumerator**: -```json -{ - "type": "ENUMERATOR", - "factory": "FileSystemEnumerator", - "mediaTypes": [ - "IMAGE", "VIDEO" - ] -} -``` - -##### Index Operator Configuration: Decoder - -The [`DecoderConfig`](/vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/config/ingest/operator/OperatorConfig.kt) -describes how the media content is decoded. - -```json -{ - "type": "", - "factory": "DecoderClass" -} -``` - -Available decodes can be found [in the index module](/vitrivr-engine-index/src/main/kotlin/org/vitrivr/engine/index/decode). -Since we work with images in this tutorial, we require the [`ImageDecoder`](/vitrivr-engine-index/src/main/kotlin/org/vitrivr/engine/index/decode/ImageDecoder.kt): - -```json -{ - "name": "ImageDecoder" -} -``` - -##### Index Operators Configuration: Segmenter - -A [`Segmenter`](vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/operators/ingest/Segmenter.kt) is a 1:n operator, -its [`OperatorConfig`](vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/config/ingest/operator/OperatorConfig.kt) looks as follows: - -```json -{ - "type": "SEGMENTER", - "factory": "FactoryClass" -} -``` - -The `type` property is mandatory, equally so the `factory`, which has to point to a [`SegmenterFactory`](vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/operators/ingest/SegmenterFactory.kt) implementation. -The context-parameters are optional and implementation dependent. - -See [implementations](vitrivr-engine-index/src/main/kotlin/org/vitrivr/engine/index/segment/) - -##### Index Operators Configuration: Transformer - -A [`Transformer`](vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/operators/ingest/Transformer.kt) is a 1:1 operator, -its [`OperatorConfig`](vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/config/ingest/operator/OperatorConfig.kt) looks as follows: - -```json -{ - "type": "TRANSFORMER", - "factory": "FactoryClass" -} -``` - -The `type` property is mandatory, equally so the `factory`, which has to point to a [`TransformerFactory`](vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/operators/ingest/TransformerFactory.kt) implementation. -The context-parameters are optional and implementation dependent. - -See [implementations](vitrivr-engine-index/src/main/kotlin/org/vitrivr/engine/index/transform) - -##### Index Operators Configuration: Exporter - -A [`Exporter`](vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/operators/ingest/Exporter.kt) is a 1:1 operator, -its [`OperatorConfig`](vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/config/ingest/operator/OperatorConfig.kt) looks as follows: - -```json -{ - "type": "EXPORTER", - "exporterName": "name-from-schema" -} -``` - -The `type` property is mandatory, equally so the `exporterName`, which has to point to an `Exporter` defined on the _schema_. -The context-parameters are optional and implementation dependent and override those present in the _schema_ configuration. - -See [implementations](vitrivr-engine-index/src/main/kotlin/org/vitrivr/engine/index/exporters) - -##### Index Operators Configuration: Extractor - -A [`Extractor`](vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/operators/ingest/Extractor.kt) is a 1:1 operator, -its [`OperatorConfig`](vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/config/ingest/operator/OperatorConfig.kt) looks as follows: - -```json -{ - "type": "EXTRACTOR", - "fieldName": "name-from-schema" -} -``` - -The `type` property is mandatory, equally so the `fieldName`, which has to point to a _field_ as defined on the _schema_. - -See [implementations](vitrivr-engine-module-features/src/main/kotlin/org/vitrivr/engine/base/features/) - -##### Index Operators Configuration: Aggregator - -A [`Aggregator`](vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/operators/ingest/Aggregator.kt) is a 1:n operator, -its [`OperatorConfig`](vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/config/ingest/operator/OperatorConfig.kt) looks as follows: - -```json -{ - "type": "AGGREGATOR", - "factory": "FactoryClass" -} -``` - -The `type` property is mandatory, equally so the `factory`, which has to point to a [`AggregatorFactory`](vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/operators/ingest/AggregatorFactory.kt) implementation. -The context-parameters are optional and implementation dependent. - -See [implementations](vitrivr-engine-index/src/main/kotlin/org/vitrivr/engine/index/aggregators) - -#### Index Operations Configuration: The Pipeline - -So far, we only have _declared_ the operators, with the `operations` property, we define the ingestion pipeline as a tree in the form of -[`OperationsConfig`](vitrivr-engine-core/src/main/kotlin/org/vitrivr/engine/core/config/ingest/operation/OperationsConfig.kt): - -```json -{ - "schema": "sandbox", - "context": { - "contentFactory": "InMemoryContentFactory", - "resolverName": "disk", - "local": { - "enumerator": { - "path": "./sandbox/imgs", - "depth": "1" - }, - "myoperator": { - "key1": "a-avlue", - "key2": "1234" - } - } - }, - "operators": { - "myoperator": {}, - "myoperator1": {}, - "myoperator2": {} - }, - "operations": { - "myOperation": { - "operator": "myoperator" - }, - "myOperation1": { - "operator": "myoperator1", "inputs": ["myOperation"] - }, - "myOperation2": { - "operator": "myoperator2", "inputs": ["myOperation"] - } - }, - "output": ["myOperation2"] -} -``` - -Specifically, the `operator` property must point to a previously declared _operator_ and -the entries in the `inputs` property must point to an _operation_ with that name. -The `output` property of the ingest config then specifies the _operation_ whose results are persisted. - -Currently, there are the following rules to build such a pipeline: - -**Pipeline Rules:** - -1. The first _operation_ **must** be a `ENUMERATOR` -2. Following an `ENUMERATOR`, there **must** come a `DECODER` -3. Following a `DECODER`, there **must** either be a `TRANSFORMER` or `SEGMENTER` -4. `TRANSFORMER`s and `SEGMENTER`s can be daisy-chained -5. A `SEGMENTER` must be followed by one or more `AGGREGATOR`s, multiple `AGGREGATORS` results in branching. -6. An `AGGREGATOR` must be followed by either a `EXTRACTOR` or `EXPORTER` -7. `EXPORTER`s and `EXTRACTOR`s can be daisy-chained -8. The end or the ends, in case of branching, must be of type `EXPORTER` or `EXTRACTOR`. - -Notably, currently multiple `ENUMERATORS` are treated as separate trees, since merging is not yet supported. - -One example, based on the _schema_ further above (without branching), might look as follows: - -```json -{ - "schema": "sandbox", - "context": { - "contentFactory": "InMemoryContentFactory", - "resolverName": "disk", - "local": { - "enumerator": { - "path": "./sandbox/imgs", - "depth": "1" - }, - "thumbs": { - "maxSideResolution": "350", - "mimeType": "JPG" - } - } - }, - "operators": { - "fsenumerator": { - "type": "ENUMERATOR", - "factory": "FileSystemEnumerator", - "mediaTypes": ["IMAGE"] - }, - "decoder": { - "type": "DECODER", - "factory": "ImageDecoder" - }, - "pass": { - "type": "SEGMENTER", - "factory": "PassThroughSegmenter" - }, - "allContent": { - "type": "AGGREGATOR", - "factory": "AllContentAggregator" - }, - "avgColor": { - "type": "EXTRACTOR", - "fieldName": "averagecolor" - }, - "thumbs": { - "type": "EXPORTER", - "exporterName": "thumbnail" - }, - "fileMeta": { - "type": "EXTRACTOR", - "fieldName": "file" - } - }, - "operations": { - "stage2": {"operator": "pass", "inputs": ["stage1"]}, - "stage0": {"operator": "fsenumerator"}, - "stage1": {"operator": "decoder", "inputs": ["stage0"]}, - "stage3": {"operator": "allContent", "inputs": ["stage2"]}, - "stage4": {"operator": "avgColor", "inputs": ["stage3"]}, - "stage5": {"operator": "thumbs", "inputs": ["stage4"]}, - "stage6": {"operator": "fileMeta", "inputs": ["stage5"]} - }, - "output": ["stage6"] -} -``` - -Here, the linear order of the pipeline's operator is: `fsenumerator` -> `decoder` -> `pass` -> `allContent` -> `avgColor` -> `thumbs` -> `fileMeta`. -Note that there are context-parameters defined for the `thumbs` exporter. -Also, note that the `output` property is set up, such that the `stage6` operation is persisted. - -#### Branching and Merging - -By defining the operations accordingly, there are two thing that can happen implicitly. - -**Branching**: If an `operations` is used as input for multiple other `operations`, this results in a branching. This is handled automatically by wrapping the associated `Operator` in a `BroadcastOperator`. - -**Merging**: If an `operation` has multiple inputs, this results in a merging, which combines multiple flows of `Retrievable`s into a single flow. The merging strategy (`MergeType`) must be specified explicitly in the `operation`. - -Currently, `vitrivr-engine` supports three type of merging strategies: - -| MergeType | Description | -|-----------|----------------------------------------------------------------------------------------------------------------------| -| `MERGE` | Merges the `Retrievable`s from the input operations in order the arrive. No deduplication and ordering is performed. | -| `COMBINE` | Merges `Retrievable`s from the input operations and emits a `Retrievable`, once it was received on every input. | -| `CONCAT` | Collects `Retrievable`s from the incoming flows in order of occurence, i.e., operation 1, then operation 2 etc. | - -#### Complete Sandbox Configuration - -After following above's guide on how to build your _schema_ config and your _index pipeline_ config, -the files should be similar as follows. - -The **schema** config: - -```json -{ - "schemas": [{ - "name": "sandbox", - "connection": { - "database": "CottontailConnectionProvider", - "parameters": { - "Host": "127.0.0.1", - "port": "1865" - } - }, - "fields": [ - { - "name": "averagecolor", - "factory": "AverageColor" - }, - { - "name": "file", - "factory": "FileSourceMetadata" - } - ], - "exporters": [ - { - "name": "thumbnail", - "factory": "ThumbnailExporter", - "resolver": { - "factory": "DiskResolver", - "parameters": { - "location": "./thumbnails/sandbox" - } - }, - "parameters": { - "maxSideResolution": "400", - "mimeType": "JPG" - } - } - ], - "extractionPipelines": [ - { - "name": "sandboxpipeline", - "path": "./sandbox-pipeline.json" - } - ] - }] -} -``` - -The **pipeline** config: - -```json -{ - "schema": "sandbox", - "context": { - "contentFactory": "InMemoryContentFactory", - "resolverName": "disk", - "local": { - "fsenumerator": { - "path": "./sandbox/imgs", - "depth": "1" - }, - "thumbs": { - "path": "./sandbox/thumbnails", - "maxSideResolution": "350", - "mimeType": "JPG" - } - } - }, - "operators": { - "fsenumerator": { - "type": "ENUMERATOR", - "factory": "FileSystemEnumerator", - "mediaTypes": ["IMAGE","VIDEO"] - }, - "decoder": { - "type": "DECODER", - "factory": "ImageDecoder" - }, - "pass": { - "type": "SEGMENTER", - "factory": "PassThroughSegmenter" - }, - "allContent": { - "type": "AGGREGATOR", - "factory": "AllContentAggregator" - }, - "avgColor": { - "type": "EXTRACTOR", - "fieldName": "averagecolor" - }, - "thumbs": { - "type": "EXPORTER", - "exporterName": "thumbnail" - }, - "fileMeta": { - "type": "EXTRACTOR", - "fieldName": "file" - } - }, - "operations": { - "stage2": {"operator": "pass", "inputs": ["stage1"]}, - "stage0": {"operator": "fsenumerator"}, - "stage1": {"operator": "decoder", "inputs": ["stage0"]}, - "stage3": {"operator": "allContent", "inputs": ["stage2"]}, - "stage4": {"operator": "avgColor", "inputs": ["stage3"]}, - "stage5": {"operator": "thumbs", "inputs": ["stage4"]}, - "stage6": {"operator": "fileMeta", "inputs": ["stage5"]} - }, - "output" : ["stage6"] -} -``` - ---- - -#### Starting the indexing pipeline - -To start the actual pipeline, we start [the server module](/vitrivr-engine-server)'s [`Main`](vitrivr-engine-server/src/main/kotlin/org/vitrivr/engine/server/Main.kt) -with the path to the schema configuration as argument. - -For this to work you either build the stack or you use an IDE. - -1. Then, when the server is running, we have to first initialise the database (since our schema is named `sandbox`): - -``` -sandbox init -``` - -2. The extraction is started via the CLI by calling: -``` -sandbox extract -c sandbox-pipeline.json -``` - -Which should result in logging messages that confirm the usage of our ThumbnailExporter (including its parameters) and the message: -``` -Started extraction job with UUID -``` - -3. The server (by default) provides an [OpenAPI swagger ui](http://localhost:7070/swagger-ui) with which the job status can be queried. -The same can be achieved by this cURL command, where `` is the UUID printed above (and again, we have named our schema `sandbox`, hence the sandbox path: - -```bash -curl -X 'GET' \ - 'http://localhost:7070/api/sandbox/index/' \ - -H 'accept: application/json' -``` - -### Querying / Retrieval - -## Getting Started: Development - -This is a Gradle-powered Kotlin project, we assume prerequisites are handled accordingly. +## Contributing -1. Generate the OpenApi client code by executing the (top-level) `generateOpenApi` gradle task -2. Start developing +We welcome contributors. Please fork the repo and open a pull-request with your work. +A good starting point are the 'good first issue' issues. -If you develop another module (plugin), please keep in mind that the providers and factories are -exposed in `/resources/META-INF/services/` +## Contributors -``` -./gradlew openApiGenerate -``` +* @ppanopticon +* @lucaro +* @sauterl +* @net-csscience-raphel +* @rahelarnold98 +* @faberf +## Citation +See [Citation](https://github.com/vitrivr/vitrivr-engine/wiki/Home#Citation) diff --git a/images/vengine-256.png b/images/vengine-256.png new file mode 100755 index 0000000000000000000000000000000000000000..a59b8cdd5b04c6227736ba126611da1c404d090f GIT binary patch literal 12934 zcmcgz^z)s*xg2nPNOgK)9IA2ZKVd+-O(UCr1F zTs%bogDt66?ShN6-pWSa`fm2#zSf?0kgu;Vztb}pFI#JOJAOA$hwNQxItXHc)Rp87 z{Bm}3eT@tz#(NiNC2hDKq!dvq$L5wsTkW+L^=6cgrDxk{@Qr0<%{t!y7hLv+UZmD$ z?@crt4+bs|?sN9g*a$A=fLw_MW-kX}2gH+22?u*r-n#TKt;4W|@KEr?^yPMIMzr-? zLN3Z!b+)x>2tT5W(E#G2q=>|aB5b;JUT=;Mu{lbxBQfwU49DJgon>my<@x zHI=7O$I6=Q?{Di3O-&9B7)TFq?iHTJ=?Y!5_z9($2;lPpVWzyucJ*jKB zZrOYy6>0re!^DJ#3dRT?^Glj;^D6dFl3cLE(9jSKgr3{@hfC$+#wzpXuAqy*IU zP4ilux8hzCGfE2XwVn#t@6F3-SX;lGmkUu>C-d5!rL~{>_)a5}-(2l$agg`!?CYtI zcEbAR=4B_xsH;P9TRS`Dss{V-&f_S3ve6xREJQ-FP_CuN)0xIsx8ZU(XNtu$;@%r9 zKdUVl0;F1_qHqp7arT5&6B+Ce4!tB$S|987gk8of?Ipc8bovZKLPG4jSo z;u{)7{859iEGI4{dEj59N}>A)Iy+a1iHSq+9#YchbZXi2F==X^wy7SYfETNO-&EJ2(+EG=oOnA^n4n4LX5SP#ck4~^4`32p_w zO>@yF(?O96#izp}SkeXr15X&9&bMGeqhJxge$7$pOJwvJSJBfW*UE|R-Kri5Z)$29 zuHxnR@$+Y`=PFNlc(@gKsCU2|37zr1-dgL+6IVfD;Xjl2ZshI$g^UinNqcWkk_icMj)6x*9pGRHxlViQ z$;apsP(k41cpWlFhC2dKtWbN=p_t1!p~G;_``iUwooGaz{dcHe*=jgP?60BCZH-`J ztJ7VXENOpyXz|r!3wg6y<6NyX-A|k{GK{T(r^?pWtdP}2Rc_XO?o``~vzG&^kcCCw z6VK95pJ>R{rTcE_dVgR2=ETL%j}2wLe%<-)Tbga$S=ayp!pMjQTdBTv|Zgys@p| zdgHm+A+PcJfX><3nT0%N|C@lE?R?8;@C7N2U~-*TfBH~g&;C*97#rh3X9wS?&bI69 z7)+IQqrz}Vtbe>6D6OiB1kcfyyN>omF7=}D*chjf z{gBat*yURGBcpmp);`03^mMQmB&#C!pV7jwn%Y_zRB6$Q9e3;Q+9c0loVX890=s|!Nt4?`Z>|(=|F>_7PEOqaGBn@Zf0>)hn3Iz;`d-te-gPFU zGM5@Yk}nq(6-7NbIB4bK5;rtN`02|RPuC19!S!jVaPiL{qR14NcX4q9($do64JE8q zmhFk4>PIIeCr>GZLns9tf;1jE9tw7335LsCT7R)-&oI|KX?4` z77r?@ucy3y`*#1pIS%-K*Fp#?p}yYx?c2A%rlbUJ#R&ypiKDC7yiW~!EB6;!A*61x z$}%Xw45l2UpR^wIpB9&whvE?ua`Z^1rj2+#qv-C}cO{`0t=Dpu4GavlAI_N?0-3G8 zoa*e#U)F1--`f6U+t`N(BTk9U{%qfR2<)B&iYYxQPbQH3a+4RKkn{yqhD?TRQCAMR zE91KP#o4^nR5tsuqKIR|xv2&hPJIiD@2WO=fm74d2St873namWPy7e}{Rvs_O`wO6e}9&Ae*c~z zY#My&iqX{_$SN#M0WGerMcy?P{j)t~bhI@wVfCDlW|Y~(!@&bg*e_s^!sW@6CoFt? 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