Hey there, let's tackle your problems one by one to get you up and running with MediaPipe hand tracking smoothly!

Fixing the "No Bazel found" Error #

Installing the Bazel plugin in Android Studio isn't enough—you need the Bazel executable itself on your system. Here's how to fix this:

• First, check if Bazel is installed on your machine: Open Android Studio's Terminal (bottom panel) and run bazel --version. If you get a "command not found" error, Bazel isn't installed.
• Use Bazelisk (Recommended): Bazelisk automatically manages the correct Bazel version for MediaPipe projects, so you don't have to worry about version mismatches. Install Bazelisk (follow official instructions for your OS), then run bazelisk --version in the terminal—it will download the right Bazel version for your MediaPipe project.
• Configure Bazel Path in Android Studio: Go to File > Settings > Bazel (or Preferences > Bazel on Mac). Under "Bazel executable", browse to the location of your Bazel or Bazelisk binary (e.g., /usr/local/bin/bazelisk on macOS/Linux, or the .exe path on Windows).
• Verify: Restart Android Studio, open your MediaPipe project, and try running a build command like bazel build //mediapipe/examples/android/src/java/com/google/mediapipe/apps/handtrackinggpu:handtrackinggpu—the error should be gone.

Easier Way to Implement Hand Tracking in Android Studio #

Forget the complex Bazel setup—use MediaPipe Tasks Vision, a pre-built library that integrates directly with Gradle. It's way simpler:

Step 1: Add Dependencies #

• In your project-level build.gradle, add these repositories:

  repositories {
      mavenCentral()
      maven { url "https://maven.google.com" }
  }
  

• In your app-level build.gradle, add the MediaPipe Tasks dependency:

  dependencies {
      implementation 'com.google.mediapipe:tasks-vision:latest.release'
  }
  

Step 2: Get the Pre-trained Model #

Download the hand_landmarker.task model (pre-trained for hand tracking) and place it in your app's src/main/assets directory.

Step 3: Implement Hand Tracking Code #

Here's a quick Kotlin example to get you started:

import com.google.mediapipe.tasks.vision.core.BaseOptions
import com.google.mediapipe.tasks.vision.handlandmarker.HandLandmarker
import com.google.mediapipe.tasks.vision.handlandmarker.HandLandmarkerOptions
import com.google.mediapipe.tasks.vision.core.BitmapImageBuilder

// Initialize HandLandmarker
val baseOptions = BaseOptions.builder()
    .setModelAssetPath("hand_landmarker.task")
    .build()
val options = HandLandmarkerOptions.builder()
    .setBaseOptions(baseOptions)
    .setNumHands(2) // Track up to 2 hands
    .build()
val handLandmarker = HandLandmarker.createFromOptions(context, options)

// Process a bitmap (e.g., from camera feed)
val image = BitmapImageBuilder(yourBitmap).build()
val result = handLandmarker.detect(image)

// Extract and use hand landmarks
result.handLandmarks().forEach { landmarks ->
    landmarks.forEach { landmark ->
        val x = landmark.x() * yourBitmap.width
        val y = landmark.y() * yourBitmap.height
        // Draw the landmark on your view or use coordinates for interactions
    }
}

Bonus Tips #

• For camera integration, you can use Android's CameraX library to feed frames to the HandLandmarker.
• Check MediaPipe's official Tasks documentation for more details on customizing tracking settings (like confidence thresholds).

内容的提问来源于stack exchange，提问作者Kamlendra Pandey