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Face Analytics
Zia Face Analytics performs facial detection in images, and analyzes the facial features to provide information such as the gender, age, and emotion of the detected faces.
Face Analytics also provides the confidence levels of each attribute prediction that enables you to make informed decisions. It can detect up to 10 faces in an image, and it provides predictions of the attributes for each detected face.
Execute Face Analytics
Description
You can use this API to perform facial detection and analytics in an image file, and specify the path to it in the API request as shown in the sample request.
You can optionally specify an analysis mode which determines the number of facial landmarks to be detected in a face. You can also enable or disable the attributes to be predicted, such as the emotion, age, and gender.
This API is used to pass input for Face Analytics prediction. You must pass an input image file and the data in a JSON format in the request as described below.
Request Details
Request URL
{api-domain}/baas/v1/project/{project_id}/ml/faceanalytics
Request Headers
Authorization: Zoho-oauthtoken {oauth_token}
content-type: multipart/form-data; boundary=—-WebKitFormBoundary7MA4YWxkTrZu0gW
Optional Headers
CATALYST-ORG: {org_id}
Environment: Development
Scope
ZohoCatalyst.mlkit.READ
Request JSON Properties
The input file to be processed. You must provide the path to it in your local system.
Allowed formats: .webp, .jpeg, .png
Image size limit: 10 MB
Denotes the number of facial landmarks to be detected in a face
Allowed values: basic, moderate, advanced
Default value: advanced
- basic: 0-point landmark detector that detects the boundary of the face alone
- moderate: 5-point landmark detector that detects- Eyes: The center of both eyes, Nose: Nose tip, Lips: The center of both lips
- advanced: 68-point landmark detector that detects- Jawline: Face boundary, Eyebrows: Left and right eyebrow, Eyes: Left and right eye, Nose bridge, Nostril line, Upper lips: Upper and lower edge, Lower lips: Upper and lower edge
Allowed values:
false: Emotion will not be detected
true: Emotion will be detected
Default value: true
Allowed values:
false: Age will not be detected
true: Age will be detected
Default value: true
Allowed values:
false: Gender will not be detected
true: Gender will be detected
Default value: true
Response Details
The response returns the details of the facial landmarks of the detected faces, and the predictions for emotion, age, and gender, based on the parameters and mode set in the API request in the data key.
The overall probability of the co-ordinates of the facial landmark detection, and the probability of the predictions made for the emotion, age, and gender parameters will be returned as confidence scores.
curl -X POST
https://api.catalyst.zoho.com/baas/v1/project/4000000006007/ml/faceanalytics
-H “Authorization: Zoho-oauthtoken 1000.910*************************16.2f*************************57”
-H “Content-Type: multipart/form-data; boundary=—-WebKitFormBoundary7MA4YWxkTrZu0gW”
-F “image=@face.jpeg”
-d ‘{
“mode”: “basic”,
“emotion”: “true”,
“age”: “true”,
“gender”: “true”
}’
{
"status": "success",
"data": {
"faces": [
{
"confidence": 1.0,
"id": 0,
"co_ordinates": [
267,
39,
153,
227
],
"emotion": {
"prediction": "not_smiling",
"confidence": {
"smiling": "0.0",
"not_smiling": "1.0"
}
},
"age": {
"prediction": "3-9",
"confidence": {
"0-2": "0.005",
"10-19": "0.33",
"20-29": "0.12",
"3-9": "0.509",
"30-39": "0.032",
"40-49": "0.003",
"50-59": "0.0",
"60-69": "0.0",
">70": "0.0"
}
},
"gender": {
"prediction": "female",
"confidence": {
"female": "0.92",
"male": "0.08"
}
}
}
]
}
}
curl -X POST
https://api.catalyst.zoho.com/baas/v1/project/4000000006007/ml/faceanalytics
-H “Authorization: Zoho-oauthtoken 1000.910*************************16.2f*************************57”
-H “Content-Type: multipart/form-data; boundary=—-WebKitFormBoundary7MA4YWxkTrZu0gW”
-F “image=@face.jpeg”
-d ‘{
“mode”: “moderate”,
“emotion”: “false”,
“age”: “false”,
“gender”: “true”
}’
{
"status": "success",
"data": {
"faces": [
{
"confidence": 1.0,
"id": 0,
"co_ordinates": [
267,
39,
153,
227
],
"landmarks": {
"left_eye": [337,135],
"right_eye": [400,130],
"nose": [
400,
165
],
"mouth_left": [
353,
217
],
"mouth_right": [
404,
211
]
},
"gender": {
"prediction": "female",
"confidence": {
"female": "0.92",
"male": "0.08"
}
}
}
]
}
}
curl -X POST
https://api.catalyst.zoho.com/baas/v1/project/4000000006007/ml/faceanalytics
-H “Authorization: Zoho-oauthtoken 1000.910*************************16.2f*************************57”
-H “Content-Type: multipart/form-data; boundary=—-WebKitFormBoundary7MA4YWxkTrZu0gW”
-F “image=@face.jpeg”
-d ‘{
“mode”: “advanced”,
“emotion”: “true”,
“age”: “false”,
“gender”: “false”
}’
{
"status": "success",
"data": {
"faces": [
{
"co_ordinates" : [ 185, 96, 275, 18],
"confidence" : 0.99
"landmarks" : {
'mouth': [
[259, 440],
[287, 423],
[312, 413],
[325, 418],
[338, 414],
[354, 424],
[368, 442],
[355, 461],
[339, 470],
[325, 472],
[310, 470],
[285, 460],
[269, 440],
[311, 435],
[324, 436],
[338, 436],
[359, 442],
[339, 440],
[326, 441],
[312, 439]
],
'right_eyebrow': [
[189, 245],
[216, 230],
[244, 227],
[273, 234],
[301, 248]
],
'left_eyebrow': [
[356, 249],
[379, 238],
[401, 232],
[422, 235],
[436, 252]
],
'right_eye': [
[225, 288],
[245, 281],
[265, 282],
[280, 295],
[263, 297],
[244, 297]
],
'left_eye': [
[358, 299],
[376, 288],
[393, 290],
[408, 298],
[393, 305],
[376, 304]
],
'nose': [
[329, 287],
[331, 311],
[334, 336],
[337, 360],
[301, 385],
[315, 389],
[329, 392],
[341, 390],
[352, 385]
],
'jaw': [
[131, 283],
[136, 340],
[145, 393],
[158, 442],
[180, 484],
[212, 513],
[250, 530],
[287, 542],
[319, 545],
[347, 535],
[370, 512],
[393, 487],
[411, 456],
[423, 419],
[432, 381],
[437, 342],
[439, 303]
]
},
"emotion": {
"prediction": "not_smiling",
"confidence": {
"smiling": "0.0",
"not_smiling": "1.0"
}
}
}
]
}
}
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