-
Notifications
You must be signed in to change notification settings - Fork 2.9k
/
FaceDetectionActivity.kt
132 lines (116 loc) · 5.28 KB
/
FaceDetectionActivity.kt
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
/*
* Copyright 2020 Google LLC. All rights reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package com.google.example.mlkit.kotlin
import androidx.appcompat.app.AppCompatActivity
import com.google.mlkit.vision.common.InputImage
import com.google.mlkit.vision.face.*
class FaceDetectionActivity : AppCompatActivity() {
private fun detectFaces(image: InputImage) {
// [START set_detector_options]
val options = FaceDetectorOptions.Builder()
.setPerformanceMode(FaceDetectorOptions.PERFORMANCE_MODE_ACCURATE)
.setLandmarkMode(FaceDetectorOptions.LANDMARK_MODE_ALL)
.setClassificationMode(FaceDetectorOptions.CLASSIFICATION_MODE_ALL)
.setMinFaceSize(0.15f)
.enableTracking()
.build()
// [END set_detector_options]
// [START get_detector]
val detector = FaceDetection.getClient(options)
// Or, to use the default option:
// val detector = FaceDetection.getClient();
// [END get_detector]
// [START run_detector]
val result = detector.process(image)
.addOnSuccessListener { faces ->
// Task completed successfully
// [START_EXCLUDE]
// [START get_face_info]
for (face in faces) {
val bounds = face.boundingBox
val rotY = face.headEulerAngleY // Head is rotated to the right rotY degrees
val rotZ = face.headEulerAngleZ // Head is tilted sideways rotZ degrees
// If landmark detection was enabled (mouth, ears, eyes, cheeks, and
// nose available):
val leftEar = face.getLandmark(FaceLandmark.LEFT_EAR)
leftEar?.let {
val leftEarPos = leftEar.position
}
// If classification was enabled:
if (face.smilingProbability != null) {
val smileProb = face.smilingProbability
}
if (face.rightEyeOpenProbability != null) {
val rightEyeOpenProb = face.rightEyeOpenProbability
}
// If face tracking was enabled:
if (face.trackingId != null) {
val id = face.trackingId
}
}
// [END get_face_info]
// [END_EXCLUDE]
}
.addOnFailureListener { e ->
// Task failed with an exception
// ...
}
// [END run_detector]
}
private fun faceOptionsExamples() {
// [START mlkit_face_options_examples]
// High-accuracy landmark detection and face classification
val highAccuracyOpts = FaceDetectorOptions.Builder()
.setPerformanceMode(FaceDetectorOptions.PERFORMANCE_MODE_ACCURATE)
.setLandmarkMode(FaceDetectorOptions.LANDMARK_MODE_ALL)
.setClassificationMode(FaceDetectorOptions.CLASSIFICATION_MODE_ALL)
.build()
// Real-time contour detection
val realTimeOpts = FaceDetectorOptions.Builder()
.setContourMode(FaceDetectorOptions.CONTOUR_MODE_ALL)
.build()
// [END mlkit_face_options_examples]
}
private fun processFaceList(faces: List<Face>) {
// [START mlkit_face_list]
for (face in faces) {
val bounds = face.boundingBox
val rotY = face.headEulerAngleY // Head is rotated to the right rotY degrees
val rotZ = face.headEulerAngleZ // Head is tilted sideways rotZ degrees
// If landmark detection was enabled (mouth, ears, eyes, cheeks, and
// nose available):
val leftEar = face.getLandmark(FaceLandmark.LEFT_EAR)
leftEar?.let {
val leftEarPos = leftEar.position
}
// If contour detection was enabled:
val leftEyeContour = face.getContour(FaceContour.LEFT_EYE)?.points
val upperLipBottomContour = face.getContour(FaceContour.UPPER_LIP_BOTTOM)?.points
// If classification was enabled:
if (face.smilingProbability != null) {
val smileProb = face.smilingProbability
}
if (face.rightEyeOpenProbability != null) {
val rightEyeOpenProb = face.rightEyeOpenProbability
}
// If face tracking was enabled:
if (face.trackingId != null) {
val id = face.trackingId
}
}
// [END mlkit_face_list]
}
}