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+# Examples
+
+Below are code samples on how to run MediaPipe on both mobile and desktop. We
+currently support MediaPipe APIs on mobile for Android only but will add support
+for Objective-C shortly.
+
+## Mobile
+
+### Hello World! on Android
+
+[Hello World! on Android](./hello_world_android.md) should be the first mobile
+example users go through in detail. It teaches the following:
+
+*   Introduction of a simple MediaPipe graph running on mobile GPUs for
+    [Sobel edge detection].
+*   Building a simple baseline Android application that displays "Hello World!".
+*   Adding camera preview support into the baseline application using the
+    Android [CameraX] API.
+*   Incorporating the Sobel edge detection graph to process the live camera
+    preview and display the processed video in real-time.
+
+### Object Detection with GPU on Android
+
+[Object Detection on GPU on Android](./object_detection_android_gpu.md)
+illustrates how to use MediaPipe with a TFLite model for object detection in a
+GPU-accelerated pipeline.
+
+### Object Detection with CPU on Android
+
+[Object Detection on CPU on Android](./object_detection_android_cpu.md)
+illustrates using the same TFLite model in a CPU-based pipeline. This example
+highlights how graphs can be easily adapted to run on CPU v.s. GPU.
+
+### Face Detection on Android
+
+[Face Detection on Android](./face_detection_android_gpu.md) illustrates how to
+use MediaPipe with a TFLite model for face detection in a GPU-accelerated
+pipeline.
+
+*   The selfie face detection TFLite model is based on
+    ["BlazeFace: Sub-millisecond Neural Face Detection on Mobile GPUs"](https://sites.google.com/view/perception-cv4arvr/blazeface).
+*   [Model card](https://sites.google.com/corp/view/perception-cv4arvr/blazeface#h.p_21ojPZDx3cqq).
+
+### Hair Segmentation on Android
+
+[Hair Segmentation on Android](./hair_segmentation_android_gpu.md) illustrates
+how to use MediaPipe with a TFLite model for hair segmentation in a
+GPU-accelerated pipeline.
+
+*   The selfie hair segmentation TFLite model is based on
+    ["Real-time Hair segmentation and recoloring on Mobile GPUs"](https://sites.google.com/view/perception-cv4arvr/hair-segmentation).
+*   [Model card](https://sites.google.com/corp/view/perception-cv4arvr/hair-segmentation#h.p_NimuO7PgHxlY).
+
+## Desktop
+
+### Hello World for C++
+
+[Hello World for C++](./hello_world_desktop.md) shows how to run a simple graph
+using the MediaPipe C++ APIs.
+
+### Preparing Data Sets with MediaSequence
+
+[Preparing Data Sets with MediaSequence](./media_sequence.md) shows how to use
+MediaPipe for media processing to prepare video data sets for training a
+TensorFlow model.
+
+### Object Detection on Desktop
+
+[Object Detection on Desktop](./object_detection_desktop.md) shows how to run
+object detection models (TensorFlow and TFLite) using the MediaPipe C++ APIs.
+
+[Sobel edge detection]:https://en.wikipedia.org/wiki/Sobel_operator
+[CameraX]:https://developer.android.com/training/camerax