MediaPipe Solutions menyediakan serangkaian library dan alat untuk Anda menerapkan teknik kecerdasan buatan (AI) dan machine learning (ML) dengan cepat di aplikasi Anda. Anda dapat langsung memasukkan solusi ini ke dalam aplikasi,
menyesuaikannya dengan kebutuhan Anda, dan menggunakannya di beberapa platform
pengembangan. Solusi MediaPipe adalah bagian dari project open source
MediaPipe, sehingga Anda dapat menyesuaikan
kode solusi lebih lanjut untuk memenuhi kebutuhan aplikasi Anda. Suite MediaPipe Solutions
meliputi hal berikut:
Library dan resource ini menyediakan fungsi inti untuk setiap Solusi MediaPipe:
MediaPipe Tasks: API dan library lintas platform untuk men-deploy
solusi. Pelajari lebih lanjut
Model MediaPipe: Model terlatih dan siap dijalankan untuk digunakan dengan setiap solusi.
Alat ini memungkinkan Anda menyesuaikan dan mengevaluasi solusi:
MediaPipe Model Maker: Menyesuaikan model untuk solusi dengan data Anda. Pelajari
lebih lanjut
MediaPipe Studio: Visualisasikan, evaluasi, dan lakukan benchmark solusi di browser Anda. Pelajari
lebih lanjut
Solusi yang tersedia
Solusi MediaPipe tersedia di beberapa platform. Setiap solusi
menyertakan satu atau beberapa model, dan Anda juga dapat menyesuaikan model untuk beberapa solusi. Daftar berikut menunjukkan solusi yang tersedia untuk setiap platform
yang didukung dan apakah Anda dapat menggunakan Model Maker untuk menyesuaikan model:
Anda dapat memulai MediaPipe Solutions dengan memilih salah satu tugas
yang tercantum dalam hierarki navigasi sebelah kiri, termasuk
tugas visio,
teks, dan
audio.
Jika Anda memerlukan bantuan untuk menyiapkan lingkungan pengembangan untuk digunakan dengan Tugas MediaPipe, lihat panduan penyiapan untuk Android, aplikasi web, dan Python.
Solusi lama
Kami telah mengakhiri dukungan untuk Solusi MediaPipe Lama yang tercantum di bawah mulai
1 Maret 2023. Semua Solusi MediaPipe Lama lainnya akan diupgrade ke
Solusi MediaPipe baru. Lihat daftar di bawah untuk mengetahui detailnya. Repositori kode dan biner bawaan untuk semua Solusi MediaPipe Lama akan terus disediakan berdasarkan kondisi apa adanya.
[[["Mudah dipahami","easyToUnderstand","thumb-up"],["Memecahkan masalah saya","solvedMyProblem","thumb-up"],["Lainnya","otherUp","thumb-up"]],[["Informasi yang saya butuhkan tidak ada","missingTheInformationINeed","thumb-down"],["Terlalu rumit/langkahnya terlalu banyak","tooComplicatedTooManySteps","thumb-down"],["Sudah usang","outOfDate","thumb-down"],["Masalah terjemahan","translationIssue","thumb-down"],["Masalah kode / contoh","samplesCodeIssue","thumb-down"],["Lainnya","otherDown","thumb-down"]],["Terakhir diperbarui pada 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 | |"]]
