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fixed some typos
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README.md

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@@ -179,7 +179,7 @@ Or simply obtain the tensor (tensor has to be disposed manually):
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const t = recognitionNet.forward('myImg')
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```
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Compute the Face Descriptors for Detected Faces
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Compute the Face Descriptors for Detected Faces:
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``` javascript
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const detections = await detectionNet.locateFaces(input)
@@ -217,14 +217,14 @@ Draw the detected face landmarks to a canvas:
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``` javascript
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// adjust the landmark positions in case your displayed image has a different size then the original
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const landmarksForSize = landmarks.forSize(myImg.width, myImg.height))
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const landmarksForSize = landmarks.forSize(myImg.width, myImg.height)
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const canvas = document.getElementById('overlay')
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canvas.width = myImg.width
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canvas.height = myImg.height
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faceapi.drawLandmarks(canvas, landmarksForSize, { drawLines: true })
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```
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Retrieve the face landmark positions
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Retrieve the face landmark positions:
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``` javascript
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const landmarkPositions = landmarks.getPositions()
@@ -239,14 +239,14 @@ const leftEyeBbrow = landmarks.getLeftEyeBrow()
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const rightEyeBrow = landmarks.getRightEyeBrow()
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```
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Compute the Face Landmarks for Detected Faces
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Compute the Face Landmarks for Detected Faces:
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``` javascript
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const detections = await detectionNet.locateFaces(input)
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// get the face tensors from the image (have to be disposed manually)
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const faceTensors = await faceapi.extractFaceTensors(input, detections)
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const landmarksByFace = await Promise.all(faceTensors.map(t => landmarksNet.detectLandmarks(t)))
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const landmarksByFace = await Promise.all(faceTensors.map(t => faceLandmarkNet.detectLandmarks(t)))
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// free memory for face image tensors after we computed their descriptors
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faceTensors.forEach(t => t.dispose())

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