MediaPipe Solutions fornisce una suite di librerie e strumenti per applicare rapidamente tecniche di intelligenza artificiale (IA) e machine learning (ML) alle tue applicazioni. Puoi collegare immediatamente queste soluzioni alle tue applicazioni, personalizzarle in base alle tue esigenze e utilizzarle su più piattaforme di sviluppo. MediaPipe Solutions fa parte del progetto open source MediaPipe, quindi puoi personalizzare ulteriormente il codice delle soluzioni per soddisfare le esigenze della tua applicazione. La suite MediaPipe Solutions include quanto segue:
Queste librerie e risorse forniscono la funzionalità di base per ogni soluzione MediaPipe:
MediaPipe Tasks: API e librerie multipiattaforma per il deployment di soluzioni. Scopri di più
Modelli MediaPipe: modelli preaddestrati e pronti per l'uso con ogni
soluzione.
Questi strumenti ti consentono di personalizzare e valutare le soluzioni:
MediaPipe Model Maker: personalizza i modelli per le soluzioni con i tuoi dati. Scopri di più
MediaPipe Studio: visualizza, valuta e esegui il benchmarking delle soluzioni nel browser. Scopri di più
Soluzioni disponibili
Le soluzioni MediaPipe sono disponibili su più piattaforme. Ogni soluzione include uno o più modelli e puoi personalizzare i modelli anche per alcune soluzioni. L'elenco seguente mostra le soluzioni disponibili per ogni piattaforma supportata e se puoi utilizzare Model Maker per personalizzare il modello:
Per iniziare a utilizzare MediaPipe Solutions, seleziona una delle attività elencate nella struttura ad albero di navigazione a sinistra, tra cui le attività di visione, testo e audio.
Se hai bisogno di aiuto per configurare un ambiente di sviluppo da utilizzare con MediaPipe tasks, consulta le guide alla configurazione per Android, app web e Python.
Soluzioni legacy
Abbiamo interrotto il supporto delle soluzioni MediaPipe precedenti elencate di seguito a partire dal 1° marzo 2023. Per tutte le altre soluzioni MediaPipe legacy verrà eseguito l'upgrade a una nuova soluzione MediaPipe. Per maggiori dettagli, consulta l'elenco di seguito. Il
repository del codice e
i binari precompilati per tutte le soluzioni MediaPipe Legacy continueranno a essere
forniti così come sono.
[[["Facile da capire","easyToUnderstand","thumb-up"],["Il problema è stato risolto","solvedMyProblem","thumb-up"],["Altra","otherUp","thumb-up"]],[["Mancano le informazioni di cui ho bisogno","missingTheInformationINeed","thumb-down"],["Troppo complicato/troppi passaggi","tooComplicatedTooManySteps","thumb-down"],["Obsoleti","outOfDate","thumb-down"],["Problema di traduzione","translationIssue","thumb-down"],["Problema relativo a esempi/codice","samplesCodeIssue","thumb-down"],["Altra","otherDown","thumb-down"]],["Ultimo aggiornamento 2025-07-24 UTC."],[],[],null,["# MediaPipe Solutions guide\n\nMediaPipe Solutions provides a suite of libraries and tools for you to quickly\napply artificial intelligence (AI) and machine learning (ML) techniques in your\napplications. You can plug these solutions into your applications immediately,\ncustomize them to your needs, and use them across multiple development\nplatforms. MediaPipe Solutions is part of the MediaPipe [open source\nproject](https://github.com/google/mediapipe), so you can further customize the\nsolutions code to meet your application needs. The MediaPipe Solutions suite\nincludes the following:\n\nThese libraries and resources provide the core functionality for each MediaPipe\nSolution:\n\n- **MediaPipe Tasks** : Cross-platform APIs and libraries for deploying solutions. [Learn more](/edge/mediapipe/solutions/tasks)\n- **MediaPipe Models**: Pre-trained, ready-to-run models for use with each solution.\n\nThese tools let you customize and evaluate solutions:\n\n- **MediaPipe Model Maker** : Customize models for solutions with your data. [Learn\n more](/edge/mediapipe/solutions/model_maker)\n- **MediaPipe Studio** : Visualize, evaluate, and benchmark solutions in your browser. [Learn\n more](/edge/mediapipe/solutions/studio)\n\nAvailable solutions\n-------------------\n\nMediaPipe Solutions are available across multiple platforms. Each solution\nincludes one or more models, and you can customize models for some solutions as\nwell. The following list shows what solutions are available for each supported\nplatform and if you can use Model Maker to customize the model:\n\n| Solution | Android | Web | Python | iOS | Customize model |\n|------------------------------------------------------------------------------------|---------|-----|--------|-----|-----------------|\n| [LLM Inference API](/edge/mediapipe/solutions/genai/llm_inference) | | | | | |\n| [Object detection](/edge/mediapipe/solutions/vision/object_detector) | | | | | |\n| [Image classification](/edge/mediapipe/solutions/vision/image_classifier) | | | | | |\n| [Image segmentation](/edge/mediapipe/solutions/vision/image_segmenter) | | | | | |\n| [Interactive segmentation](/edge/mediapipe/solutions/vision/interactive_segmenter) | | | | | |\n| [Hand landmark detection](/edge/mediapipe/solutions/vision/hand_landmarker) | | | | | |\n| [Gesture recognition](/edge/mediapipe/solutions/vision/gesture_recognizer) | | | | | |\n| [Image embedding](/edge/mediapipe/solutions/vision/image_embedder) | | | | | |\n| [Face detection](/edge/mediapipe/solutions/vision/face_detector) | | | | | |\n| [Face landmark detection](/edge/mediapipe/solutions/vision/face_landmarker) | | | | | |\n| [Face stylization](/edge/mediapipe/solutions/vision/face_stylizer) | | | | | |\n| [Pose landmark detection](/edge/mediapipe/solutions/vision/pose_landmarker) | | | | | |\n| [Image generation](/edge/mediapipe/solutions/vision/image_generator) | | | | | |\n| [Text classification](/edge/mediapipe/solutions/text/text_classifier) | | | | | |\n| [Text embedding](/edge/mediapipe/solutions/text/text_embedder) | | | | | |\n| [Language detector](/edge/mediapipe/solutions/text/language_detector) | | | | | |\n| [Audio classification](/edge/mediapipe/solutions/audio/audio_classifier) | | | | | |\n\nGet started\n-----------\n\nYou can get started with MediaPipe Solutions by selecting any of the tasks\nlisted in the left navigation tree, including\n[vision](/edge/mediapipe/solutions/vision/object_detector),\n[text](/edge/mediapipe/solutions/text/text_classifier), and\n[audio](/edge/mediapipe/solutions/audio/audio_classifier) tasks.\nIf you need help setting up a development environment for use with MediaPipe\nTasks, check out the setup guides for\n[Android](/edge/mediapipe/solutions/setup_android),\n[web apps](/edge/mediapipe/solutions/setup_web), and\n[Python](/edge/mediapipe/solutions/setup_python).\n\nLegacy solutions\n----------------\n\nWe have ended support for the MediaPipe Legacy Solutions listed below as of\nMarch 1, 2023. All other MediaPipe Legacy Solutions will be upgraded to a new\nMediaPipe Solution. See the list below for details. The\n[code repository](https://github.com/google/mediapipe/tree/master/mediapipe) and\nprebuilt binaries for all MediaPipe Legacy Solutions will continue to be\nprovided on an as-is basis.\n\n| Legacy Solution | Status | New MediaPipe Solution |\n|-----------------------------------------------------------------------------------------------------------------------------|--------------------------------------|--------------------------------------------------------------|\n| Face Detection ([info](https://github.com/google/mediapipe/blob/master/docs/solutions/face_detection.md)) | [Upgraded](./vision/face_detector) | [Face detection](./vision/face_detector) |\n| Face Mesh ([info](https://github.com/google/mediapipe/blob/master/docs/solutions/face_mesh.md)) | [Upgraded](./vision/face_landmarker) | [Face landmark detection](./vision/face_landmarker) |\n| Iris ([info](https://github.com/google/mediapipe/blob/master/docs/solutions/iris.md)) | [Upgraded](./vision/face_landmarker) | [Face landmark detection](./vision/face_landmarker) |\n| Hands ([info](https://github.com/google/mediapipe/blob/master/docs/solutions/hands.md)) | [Upgraded](./vision/hand_landmarker) | [Hand landmark detection](./vision/hand_landmarker) |\n| Pose ([info](https://github.com/google/mediapipe/blob/master/docs/solutions/pose.md)) | [Upgraded](./vision/pose_landmarker) | [Pose landmark detection](./vision/pose_landmarker) |\n| Holistic ([info](https://github.com/google/mediapipe/blob/master/docs/solutions/holistic.md)) | Upgrade | [Holistic landmarks detection](./vision/holistic_landmarker) |\n| Selfie segmentation ([info](https://github.com/google/mediapipe/blob/master/docs/solutions/selfie_segmentation.md)) | [Upgraded](./vision/image_segmenter) | [Image segmentation](./vision/image_segmenter) |\n| Hair segmentation ([info](https://github.com/google/mediapipe/blob/master/docs/solutions/hair_segmentation.md)) | [Upgraded](./vision/image_segmenter) | [Image segmentation](./vision/image_segmenter) |\n| Object detection ([info](https://github.com/google/mediapipe/blob/master/docs/solutions/object_detection.md)) | [Upgraded](./vision/object_detector) | [Object detection](./vision/object_detector) |\n| Box tracking ([info](https://github.com/google/mediapipe/blob/master/docs/solutions/box_tracking.md)) | Support ended | |\n| Instant motion tracking ([info](https://github.com/google/mediapipe/blob/master/docs/solutions/instant_motion_tracking.md)) | Support ended | |\n| Objectron ([info](https://github.com/google/mediapipe/blob/master/docs/solutions/objectron.md)) | Support ended | |\n| KNIFT ([info](https://github.com/google/mediapipe/blob/master/docs/solutions/knift.md)) | Support ended | |\n| AutoFlip ([info](https://github.com/google/mediapipe/blob/master/docs/solutions/autoflip.md)) | Support ended | |\n| MediaSequence ([info](https://github.com/google/mediapipe/blob/master/docs/solutions/media_sequence.md)) | Support ended | |\n| YouTube 8M ([info](https://github.com/google/mediapipe/blob/master/docs/solutions/youtube_8m.md)) | Support ended | |"]]
