206 lines
8.1 KiB
Markdown
206 lines
8.1 KiB
Markdown
# MediaPipe Tasks Vision Package
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This package contains the vision tasks for MediaPipe.
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## Face Detector
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The MediaPipe Face Detector task lets you detect the presence and location of
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faces within images or videos.
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```
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const vision = await FilesetResolver.forVisionTasks(
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"https://cdn.jsdelivr.net/npm/@mediapipe/tasks-vision/wasm"
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);
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const faceDetector = await FaceDetector.createFromModelPath(vision,
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"https://storage.googleapis.com/mediapipe-models/face_detector/blaze_face_short_range/float16/1/blaze_face_short_range.tflite"
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);
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const image = document.getElementById("image") as HTMLImageElement;
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const detections = faceDetector.detect(image);
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```
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For more information, refer to the [Face Detector](https://developers.google.com/mediapipe/solutions/vision/face_detector/web_js) documentation.
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## Face Landmarker
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The MediaPipe Face Landmarker task lets you detect the landmarks of faces in
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an image. You can use this Task to localize key points of a face and render
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visual effects over the faces.
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```
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const vision = await FilesetResolver.forVisionTasks(
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"https://cdn.jsdelivr.net/npm/@mediapipe/tasks-vision/wasm"
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);
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const faceLandmarker = await FaceLandmarker.createFromModelPath(vision,
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"https://storage.googleapis.com/mediapipe-models/face_landmarker/face_landmarker/float16/1/face_landmarker.task`"
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);
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const image = document.getElementById("image") as HTMLImageElement;
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const landmarks = faceLandmarker.detect(image);
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```
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For more information, refer to the [Face Landmarker](https://developers.google.com/mediapipe/solutions/vision/face_landmarker/web_js) documentation.
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## Face Stylizer
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The MediaPipe Face Stylizer lets you perform face stylization on images.
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```
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const vision = await FilesetResolver.forVisionTasks(
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"https://cdn.jsdelivr.net/npm/@mediapipe/tasks-vision/wasm"
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);
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const faceStylizer = await FaceStylizer.createFromModelPath(vision,
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"https://storage.googleapis.com/mediapipe-models/face_stylizer/blaze_face_stylizer/float32/1/blaze_face_stylizer.task"
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);
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const image = document.getElementById("image") as HTMLImageElement;
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const stylizedImage = faceStylizer.stylize(image);
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```
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## Gesture Recognizer
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The MediaPipe Gesture Recognizer task lets you recognize hand gestures in real
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time, and provides the recognized hand gesture results along with the landmarks
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of the detected hands. You can use this task to recognize specific hand gestures
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from a user, and invoke application features that correspond to those gestures.
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```
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const vision = await FilesetResolver.forVisionTasks(
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"https://cdn.jsdelivr.net/npm/@mediapipe/tasks-vision/wasm"
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);
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const gestureRecognizer = await GestureRecognizer.createFromModelPath(vision,
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"hhttps://storage.googleapis.com/mediapipe-models/gesture_recognizer/gesture_recognizer/float16/1/gesture_recognizer.task"
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);
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const image = document.getElementById("image") as HTMLImageElement;
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const recognitions = gestureRecognizer.recognize(image);
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```
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For more information, refer to the [Gesture Recognizer](https://developers.google.com/mediapipe/solutions/vision/gesture_recognizer/web_js) documentation.
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## Hand Landmarker
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The MediaPipe Hand Landmarker task lets you detect the landmarks of the hands in
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an image. You can use this Task to localize key points of the hands and render
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visual effects over the hands.
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```
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const vision = await FilesetResolver.forVisionTasks(
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"https://cdn.jsdelivr.net/npm/@mediapipe/tasks-vision/wasm"
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);
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const handLandmarker = await HandLandmarker.createFromModelPath(vision,
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"https://storage.googleapis.com/mediapipe-models/hand_landmarker/hand_landmarker/float16/1/hand_landmarker.task"
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);
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const image = document.getElementById("image") as HTMLImageElement;
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const landmarks = handLandmarker.detect(image);
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```
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For more information, refer to the [Hand Landmarker](https://developers.google.com/mediapipe/solutions/vision/hand_landmarker/web_js) documentation.
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## Image Classifier
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The MediaPipe Image Classifier task lets you perform classification on images.
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You can use this task to identify what an image represents among a set of
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categories defined at training time.
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```
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const vision = await FilesetResolver.forVisionTasks(
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"https://cdn.jsdelivr.net/npm/@mediapipe/tasks-vision/wasm"
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);
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const imageClassifier = await ImageClassifier.createFromModelPath(vision,
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"https://storage.googleapis.com/mediapipe-models/image_classifier/efficientnet_lite0/float32/1/efficientnet_lite0.tflite"
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);
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const image = document.getElementById("image") as HTMLImageElement;
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const classifications = imageClassifier.classify(image);
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```
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For more information, refer to the [Image Classifier](https://developers.google.com/mediapipe/solutions/vision/image_classifier/web_js) documentation.
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## Image Embedder
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The MediaPipe Image Embedder extracts embeddings from an image.
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```
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const vision = await FilesetResolver.forVisionTasks(
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"https://cdn.jsdelivr.net/npm/@mediapipe/tasks-vision/wasm"
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);
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const imageEmbedder = await ImageEmbedder.createFromModelPath(vision,
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"https://storage.googleapis.com/mediapipe-models/image_embedder/mobilenet_v3_small/float32/1/mobilenet_v3_small.tflite"
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);
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const image = document.getElementById("image") as HTMLImageElement;
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const embeddings = imageSegmenter.embed(image);
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```
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## Image Segmenter
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The MediaPipe Image Segmenter lets you segment an image into categories.
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```
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const vision = await FilesetResolver.forVisionTasks(
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"https://cdn.jsdelivr.net/npm/@mediapipe/tasks-vision/wasm"
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);
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const imageSegmenter = await ImageSegmenter.createFromModelPath(vision,
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"https://storage.googleapis.com/mediapipe-models/image_segmenter/deeplab_v3/float32/1/deeplab_v3.tflite"
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);
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const image = document.getElementById("image") as HTMLImageElement;
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imageSegmenter.segment(image, (masks, width, height) => {
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...
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});
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```
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For more information, refer to the [Image Segmenter](https://developers.google.com/mediapipe/solutions/vision/image_segmenter/web_js) documentation.
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## Interactive Segmenter
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The MediaPipe Interactive Segmenter lets you select a region of interest to
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segment an image by.
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```
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const vision = await FilesetResolver.forVisionTasks(
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"https://cdn.jsdelivr.net/npm/@mediapipe/tasks-vision/wasm"
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);
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const interactiveSegmenter = await InteractiveSegmenter.createFromModelPath(
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vision,
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"https://storage.googleapis.com/mediapipe-models/interactive_segmenter/magic_touch/float32/1/magic_touch.tflite"
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);
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const image = document.getElementById("image") as HTMLImageElement;
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interactiveSegmenter.segment(image, { keypoint: { x: 0.1, y: 0.2 } },
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(masks, width, height) => { ... }
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);
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```
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For more information, refer to the [Interactive Segmenter](https://developers.google.com/mediapipe/solutions/vision/interactive_segmenter/web_js) documentation.
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## Object Detector
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The MediaPipe Object Detector task lets you detect the presence and location of
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multiple classes of objects within images or videos.
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```
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const vision = await FilesetResolver.forVisionTasks(
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"https://cdn.jsdelivr.net/npm/@mediapipe/tasks-vision/wasm"
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);
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const objectDetector = await ObjectDetector.createFromModelPath(vision,
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"https://storage.googleapis.com/mediapipe-models/object_detector/efficientdet_lite0/float16/1/efficientdet_lite0.tflite"
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);
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const image = document.getElementById("image") as HTMLImageElement;
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const detections = objectDetector.detect(image);
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```
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For more information, refer to the [Object Detector](https://developers.google.com/mediapipe/solutions/vision/object_detector/web_js) documentation.
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## Pose Landmarker
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The MediaPipe Pose Landmarker task lets you detect the landmarks of body poses
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in an image. You can use this Task to localize key points of a pose and render
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visual effects over the body.
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```
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const vision = await FilesetResolver.forVisionTasks(
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"https://cdn.jsdelivr.net/npm/@mediapipe/tasks-vision/wasm"
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);
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const poseLandmarker = await PoseLandmarker.createFromModelPath(vision,
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"https://storage.googleapis.com/mediapipe-models/pose_landmarker/pose_landmarker_lite/float16/1/pose_landmarker_lite.task
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);
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const image = document.getElementById("image") as HTMLImageElement;
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const landmarks = poseLandmarker.detect(image);
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```
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For more information, refer to the [Pose Landmarker](https://developers.google.com/mediapipe/solutions/vision/pose_landmarker/web_js) documentation.
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