API Reference
You can use Playment's APIs to access a pool of thousands of human workers to perform data labeling tasks
Introduction
Playment offers fully managed enterprise-grade solutions to build high quality training data for computer vision and vehicle perception models at scale. You just need to send us the raw data and we'll take care of everything else.
Check out the documentation below to see how easy it is to use the API.
You can check out these examples to see how other developers are utilising the Playment API.
Contact us at hello@playment.in to get started.
Authentication
- Authentication: Authenticate your account by including your secret key in API requests. The secret
x-client-keyensures that only you are able to access your projects. We expect the API key to be included in all API requests sent to our server. - Callback Auth: If you’d like to authenticate our callbacks, Playment can send a
x-playment-keyheader with each callback. You will need to share the key with us via a secure channel.
Security
- Network Security: To ensure network security, you can whitelist our IP addresses so that you accept callback requests originating only from our servers
Creating a request
A request represents one piece of work that you would want our workers to do for you.
Hit our Feedline API to create a request, or what we call, a feed line unit (FLU)
Create Feed Line Unit
POST https://staging-api.playment.in/v1/project/ project_id /feedline *
POST https://api.playment.in/v1/project/ project_id /feedline
Parameters
project_id : To be passed in the urlx-client-key : Secret key to be passed as a header
* We'll share the project_id and x-client-key separately with you via a secure channel
Payload
{
"reference_id":"001",
"data":{
"image_url":[
"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1",
"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+2",
"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+3"
]
},
"tag":"categorise_image"
}Check out the examples below to see different types of request structures.
x-client-key
Each request requires authentication with an API-key (x-client-key) which we verify before accepting a request.
reference_id
reference_id is a unique identifier for a request. We'll fail a request if you've sent another request with the same reference_id previously. This helps us ensure that we don't charge you for work which we've already done for you.
tag
Each request should have a tag which tells us what operation needs to be performed on that request. We'll share this tag with you during the integration process.
QPS
The API currently supports up to 20 requests per second.
Sample requests & responses
With error cases
{
"reference_id": "reference_1",
"data": {
"image_url": ["URL_1", "URL_2"],
"image_secondary": "URL_3"
},
"tag": "image_qc"
}{
"data": {
"image_url": ["URL_1", "URL_2"],
"image_secondary": "URL_3"
},
"tag": "image_qc"
}{
"reference_id": "reference_1",
"data": {
"image_url": ["URL_1", "URL_2"],
},
"tag": "image_qc",
}{
"reference_id": "reference_1",
"data": {
"image_url": 1234,
},
"tag": "image_qc"
}{
"feed_line_unit": {
"flu_id": "33abc3fe-9fbc-4d7c-b951-a1d1bfb6f80",
"reference_id": "ref_id_1",
"tag": "image_qc"
},
"success": true
}{
"error": {
"code": "FS_0002",
"message": "Reference Id Missing"
},
"success": false
}
{
"error": {
"code": "GE_0001",
"message": "Malformed json"
},
"success": false
}{
"error": {
"code": "FS_0003",
"message": "Invalid data passed",
"validations": [
{
"validation_code": "WRONG_DATA_TYPE",
"meta_data": {
"fields": [
"image_url"
]
}
}
]
},
"success": false
}
Error codes
Error Code
Reason
FS_0001
Duplicate Reference Id
FS_0002
Reference Id Missing
FS_0004
Data missing
FS_0005
Tag Missing
FS_0006
Feed Line Unit not found
FS_0007
Image urls not valid
GE_0001
Malformed JSON/Invalid UUID passed
GE_0002
Parameter missing
Bounding Boxes
Bounding boxes for object detection and localization in images
Detect Facial attributes
Note:
Note for existing customers: This will be Playment's new data structure. The old data structure will be deprecated and non-functional from September 1st, 2018.
{
"reference_id":"001",
"data":{
"image_url":"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1"
},
"tag":"draw_bounding_boxes"
}curl -X POST \
https://api.playment.in/v1/project/:projectId/feedline \
-H 'Content-Type: application/json' \
-H 'cache-control: no-cache' \
-H 'x-client-key: <your x-client-key here>' \
-d '{
"reference_id":"001",
"data":{
"image_url":"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1"
},
"tag":"draw_bounding_boxes"
}'package main
import (
"fmt"
"strings"
"net/http"
"io/ioutil"
)
func main() {
url := "https://api.playment.in/v1/project/:projectId/feedline"
payload := strings.NewReader("{ \n \"reference_id\":\"001\",\n \"data\":{\n \"image_url\":\"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1\"\n },\n \"tag\":\"draw_bounding_boxes\"\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("x-client-key", "<your x-client-key here>")
req.Header.Add("Content-Type", "application/json")
req.Header.Add("cache-control", "no-cache")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := ioutil.ReadAll(res.Body)
fmt.Println(res)
fmt.Println(string(body))
}import http.client
conn = http.client.HTTPConnection("api,playment,in")
payload = "{ \n \"reference_id\":\"001\",\n \"data\":{\n \"image_url\":\"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1\"\n },\n \"tag\":\"draw_bounding_boxes\"\n}"
headers = {
'x-client-key': "<your x-client-key here>",
'Content-Type': "application/json",
'cache-control': "no-cache"
}
conn.request("POST", "v1,project,:projectId,feedline", payload, headers)
res = conn.getresponse()
data = res.read()
print(data.decode("utf-8"))var request = require("request");
var options = { method: 'POST',
url: 'https://api.playment.in/v1/project/:projectId/feedline',
headers:
{ 'cache-control': 'no-cache',
'Content-Type': 'application/json',
'x-client-key': '<your x-client-key here>' },
body:
{ reference_id: '001',
data: { image_url: 'https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1' },
tag: 'draw_bounding_boxes' },
json: true };
request(options, function (error, response, body) {
if (error) throw new Error(error);
console.log(body);
});
{
"feed_line_units": [{
"reference_id": "001",
"flu_id": "33abc3fe-9fbc-4d7c-b951-a1d1bfb6f840",
"status": "COMPLETED",
"tag": "draw_bounding_boxes",
"result": [
{
"label": "television",
"coordinates": [
{"x": 0.38, "y": 0.19},
{"x": 0.57, "y": 0.19},
{"x": 0.57, "y": 0.44},
{"x": 0.38, "y": 0.44}]
},
{
"label": "plant",
"coordinates": [
{"x": 0.38, "y": 0.19},
{"x": 0.57, "y": 0.19},
{"x": 0.57, "y": 0.44},
{"x": 0.38, "y": 0.44}]
}
]
]
}
LiDAR Annotation
An endpoint to annotate cuboids in LiDAR data and track them across frames
Two cycles on top on the car
The coordinate system for the point cloud are described below:
- positive x-axis : Red(in direction of the ego-car motion)
- positive y-axis : Green(towards the left side of the ego-car)
- positive z-axis : Blue(vertically upwards, follows the right-hand rule)
Notes:
- R|T matrices (in the calibration key) should be with respect to the origin of the point cloud data(i..e LiDAR)
- Calibration and IMU are optional fields.
- Reference: Calibration
Requirement:
Camera matrix
Rotation Matrix
Camera Matrix = [[fx, 0, cx],
[0, fy, cy],
[0, 0, 1]]
Rotation Matrix = [[r11,r12,r13,0],
[r21,r22,r23,0],
[r31,r32,r33,0],
[0, 0, 0, 1]]
Translation Matrix = [[1,0,0,tx],
[0,0,0,ty],
[0,0,0,tz],
[0,0,0,1]]
Distortion Coefficients - [k1,k2,p1,p2, k3]; if not mentioned, assumed to be zeros.
- Definitions:
- (fx, fy) - focal lengths expressed in pixel units.
- (cx, cy) - principal point that is usually at the image center.
- 'rij's - rotation components between LiDAR and camera in LiDAR frame of reference.
- (tx, ty, tz)-translation between LiDAR and camera in LiDAR frame of reference.
- 'k' - radial distortion coefficients.
- 'p' - tangential distortion coefficients.
{
"reference_id":"001",
"data":{
"sensor_data": {
"frames": [
{
"cameras": [
{
"camera_id": "0",
"image_url": "https://s3.amazonaws.com/bucket/____.JPG"
}
],
"frame_id": "000000001",
"point_cloud": "https://s3.amazonaws.com/bucket/____.PCD"
},
{
"cameras": [
{
"camera_id": "0",
"image_url": "https://s3.amazonaws.com/bucket/____.JPG"
}
],
"frame_id": "000000002",
"point_cloud": "https://s3.amazonaws.com/bucket/____.PCD"
},
{}
],
"calibration": {
"cameras": [
{
"id": 0,
"rotation_matrix": [
[r11, r12, r12, 0],
[r21, r22, r23, 0],
[r31, r32, r33, 0],
[0, 0, 0, 1]
],
"camera_origin_3D": [x0,y0,z0], //camera-origin in 3D world
"projection_matrix": [
[fx, 0, cx, 0],
[0, fy, cy, 0],
[0, 0, 1, 0]
],
"translation_matrix": [
[1, 0, 0, -tx],
[0, 1, 0, -ty],
[0, 0, 1, -tz],
[0, 0, 0, 1 ]
]
}
],
"point_cloud": [
{
"type": "pcd",
"format": [
{
"key": "x",
"datatype": "float32"
},
{
"key": "y",
"datatype": "float32"
},
{
"key": "z",
"datatype": "float32"
},
{
"key": "intensity",
"datatype": "float32"
}
],
"hardware": "Velodyne32"
}
]
}
}
},
"tag":"lidar_track_cuboids"
}curl -X POST \
https://api.playment.in/v1/project/:projectId/feedline \
-H 'Content-Type: application/json' \
-H 'cache-control: no-cache' \
-H 'x-client-key: <your x-client-key here>' \
-d '{
"reference_id":"001",
"data":{
"frames": [
{
"imu": {
"delX": 0,
"delY": 0,
"delZ": 0,
"del_rotX": 0, //value in radians
"del_rotY": 0,
"del_rotZ": 0
},
"cameras": [
{
"camera_id": "0",
"image_url": "https://s3.amazonaws.com/bucket/____.JPG"
}
],
"frame_id": 0,
"point_cloud": "https://s3.amazonaws.com/bucket/____.PCD"
},
{},
{}
],
"calibration": {
"cameras": [
{
"id": 0,
"rotation_matrix": [
[r11, r12, r12, 0],
[r21, r22, r23, 0],
[r31, r32, r33, 0],
[0, 0, 0, 1]
],
"camera_origin_3D": [x0,y0,z0], //camera-origin in 3D world
"projection_matrix": [
[fx, 0, cx, 0],
[0, fy, cy, 0],
[0, 0, 1, 0]
],
"translation_matrix": [
[1, 0, 0, -tx],
[0, 1, 0, -ty],
[0, 0, 1, -tz],
[0, 0, 0, 1 ]
]
}
],
"point_cloud": [
{
"type": "pcd",
"format": [
{
"key": "x",
"datatype": "float32"
},
{
"key": "y",
"datatype": "float32"
},
{
"key": "z",
"datatype": "float32"
},
{
"key": "intensity",
"datatype": "float32"
}
],
"hardware": "lidar"
}
]
}
},
"tag":"lidar_track_cuboids"
}'package main
import (
"fmt"
"strings"
"net/http"
"io/ioutil"
)
func main() {
url := "https://api.playment.in/v1/project/:projectId/feedline"
payload := strings.NewReader("{ \n \"reference_id\":\"001\",\n \"data\":{\n \"frames\": [\n {\n \"imu\": {\n \"delX\": 0,\n \"delY\": 0,\n \"delZ\": 0,\n \"del_rotX\": 0, //value in radians \n \"del_rotY\": 0,\n \"del_rotZ\": 0\n },\n \"cameras\": [\n {\n \"camera_id\": \"0\",\n \"image_url\": \"https://s3.amazonaws.com/bucket/____.JPG\"\n }\n ],\n \"frame_id\": 0,\n \"point_cloud\": \"https://s3.amazonaws.com/bucket/____.PCD\"\n },\n {}, \n {}\n ], \n \"calibration\": {\n \"cameras\": [\n {\n \"id\": 0,\n \"rotation_matrix\": [\n [r11, r12, r12, 0],\n [r21, r22, r23, 0],\n [r31, r32, r33, 0],\n [0, 0, 0, 1]\n ],\n \"camera_origin_3D\": [x0,y0,z0], //camera-origin in 3D world\n \"projection_matrix\": [\n [fx, 0, cx, 0],\n [0, fy, cy, 0],\n [0, 0, 1, 0]\n ],\n \"translation_matrix\": [\n [1, 0, 0, -tx],\n [0, 1, 0, -ty],\n [0, 0, 1, -tz],\n [0, 0, 0, 1 ]\n ]\n }\n ],\n \"point_cloud\": [\n {\n \"type\": \"pcd\",\n \"format\": [\n {\n \"key\": \"x\",\n \"datatype\": \"float32\"\n },\n {\n \"key\": \"y\",\n \"datatype\": \"float32\"\n },\n {\n \"key\": \"z\",\n \"datatype\": \"float32\"\n },\n {\n \"key\": \"intensity\",\n \"datatype\": \"float32\"\n }\n ],\n \"hardware\": \"lidar\"\n }\n ]\n }\n },\n \"tag\":\"lidar_track_cuboids\"\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("x-client-key", "<your x-client-key here>")
req.Header.Add("Content-Type", "application/json")
req.Header.Add("cache-control", "no-cache")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := ioutil.ReadAll(res.Body)
fmt.Println(res)
fmt.Println(string(body))
}import http.client
conn = http.client.HTTPConnection("api,playment,in")
payload = "{ \n \"reference_id\":\"001\",\n \"data\":{\n \"frames\": [\n {\n \"imu\": {\n \"delX\": 0,\n \"delY\": 0,\n \"delZ\": 0,\n \"del_rotX\": 0, //value in radians \n \"del_rotY\": 0,\n \"del_rotZ\": 0\n },\n \"cameras\": [\n {\n \"camera_id\": \"0\",\n \"image_url\": \"https://s3.amazonaws.com/bucket/____.JPG\"\n }\n ],\n \"frame_id\": 0,\n \"point_cloud\": \"https://s3.amazonaws.com/bucket/____.PCD\"\n },\n {}, \n {}\n ], \n \"calibration\": {\n \"cameras\": [\n {\n \"id\": 0,\n \"rotation_matrix\": [\n [r11, r12, r12, 0],\n [r21, r22, r23, 0],\n [r31, r32, r33, 0],\n [0, 0, 0, 1]\n ],\n \"camera_origin_3D\": [x0,y0,z0], //camera-origin in 3D world\n \"projection_matrix\": [\n [fx, 0, cx, 0],\n [0, fy, cy, 0],\n [0, 0, 1, 0]\n ],\n \"translation_matrix\": [\n [1, 0, 0, -tx],\n [0, 1, 0, -ty],\n [0, 0, 1, -tz],\n [0, 0, 0, 1 ]\n ]\n }\n ],\n \"point_cloud\": [\n {\n \"type\": \"pcd\",\n \"format\": [\n {\n \"key\": \"x\",\n \"datatype\": \"float32\"\n },\n {\n \"key\": \"y\",\n \"datatype\": \"float32\"\n },\n {\n \"key\": \"z\",\n \"datatype\": \"float32\"\n },\n {\n \"key\": \"intensity\",\n \"datatype\": \"float32\"\n }\n ],\n \"hardware\": \"lidar\"\n }\n ]\n }\n },\n \"tag\":\"lidar_track_cuboids\"\n}"
headers = {
'x-client-key': "<your x-client-key here>",
'Content-Type': "application/json",
'cache-control': "no-cache",
}
conn.request("POST", "v1,project,:projectId,feedline", payload, headers)
res = conn.getresponse()
data = res.read()
print(data.decode("utf-8"))var request = require("request");
var options = { method: 'POST',
url: 'https://api.playment.in/v1/project/:projectId/feedline',
headers:
{ 'cache-control': 'no-cache',
'Content-Type': 'application/json',
'x-client-key': '<your x-client-key here>' },
body: '{ \n "reference_id":"001",\n "data":{\n "frames": [\n {\n "imu": {\n "delX": 0,\n "delY": 0,\n "delZ": 0,\n "del_rotX": 0, //value in radians \n "del_rotY": 0,\n "del_rotZ": 0\n },\n "cameras": [\n {\n "camera_id": "0",\n "image_url": "https://s3.amazonaws.com/bucket/____.JPG"\n }\n ],\n "frame_id": 0,\n "point_cloud": "https://s3.amazonaws.com/bucket/____.PCD"\n },\n {}, \n {}\n ], \n "calibration": {\n "cameras": [\n {\n "id": 0,\n "rotation_matrix": [\n [r11, r12, r12, 0],\n [r21, r22, r23, 0],\n [r31, r32, r33, 0],\n [0, 0, 0, 1]\n ],\n "camera_origin_3D": [x0,y0,z0], //camera-origin in 3D world\n "projection_matrix": [\n [fx, 0, cx, 0],\n [0, fy, cy, 0],\n [0, 0, 1, 0]\n ],\n "translation_matrix": [\n [1, 0, 0, -tx],\n [0, 1, 0, -ty],\n [0, 0, 1, -tz],\n [0, 0, 0, 1 ]\n ]\n }\n ],\n "point_cloud": [\n {\n "type": "pcd",\n "format": [\n {\n "key": "x",\n "datatype": "float32"\n },\n {\n "key": "y",\n "datatype": "float32"\n },\n {\n "key": "z",\n "datatype": "float32"\n },\n {\n "key": "intensity",\n "datatype": "float32"\n }\n ],\n "hardware": "lidar"\n }\n ]\n }\n },\n "tag":"lidar_track_cuboids"\n}' };
request(options, function (error, response, body) {
if (error) throw new Error(error);
console.log(body);
});
{
"feed_line_units": [
{
"reference_id": "001",
"flu_id": "3bcbc3fe-9fbc-4d7c-b951-a1d1bfb6f840",
"status": "COMPLETED",
"tag": "lidar_track_cuboids",
"result": {
"annotations": [
{
"tracking_id": "85164320-42cb-47b7-9f3d-de004d6a5aba",
"type": "cuboid3d",
"label": "Obstruction",
"frames": {
"000000001": {
"center": {
"x": 34.915330335708234,
"y": -2.1073208887785713,
"z": -1.2032084902657283
},
"rotation": {
"x": 0,
"y": 0,
"z": 1
},
"dimensions": {
"width": 0.2260065451,
"height": 0.7935830195,
"length": 0.2046092338
},
"attributes": {
"Object State": {
"value": "Moving"
},
"Occlusion State": {
"value": "Not Occluded"
}
}
},
"000000002": {
"center": {
"x": 34.915330335708234,
"y": -2.1073208887785713,
"z": -1.2032084902657283
},
"rotation": {
"x": 0,
"y": 0,
"z": 1.1
},
"dimensions": {
"width": 0.2260065451,
"height": 0.7935830195,
"length": 0.2046092338
},
"attributes": {
"Object State": {
"value": "Moving"
},
"Occlusion State": {
"value": "Not Occluded"
}
}
},
"000000003": {
"center": {
"x": 34.915330335708234,
"y": -2.1073208887785713,
"z": -1.2032084902657283
},
"rotation": {
"x": 0,
"y": 0,
"z": 1.2
},
"dimensions": {
"width": 0.2260065451,
"height": 0.7935830195,
"length": 0.2046092338
},
"attributes": {
"Object State": {
"value": "Moving"
},
"Occlusion State": {
"value": "Not Occluded"
}
}
}
}
}
]
}
}
]
}Object Tracking
Bounding boxes for object tracking in video across frames.
{
"reference_id": "sample_reference_id",
"data": {
"video_data": {
"frames": [
{
"frame_id": "frame001",
"src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1"
},
{
"frame_id": "frame002",
"src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+2"
},
{
"frame_id": "frame003",
"src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+3"
},
{
"frame_id": "frame004",
"src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+4"
},
{
"frame_id": "frame005",
"src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+5"
}
],
}
},
"tag": "object_tracking"
}curl -X POST \
https://api.playment.in/v1/project/:projectId/feedline \
-H 'Content-Type: application/json' \
-H 'cache-control: no-cache' \
-H 'x-client-key: <your x-client-key here>' \
-d '{
"reference_id": "sample_reference_id",
"data": {
"frames": [
{
"frame_id": "frame001",
"src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1"
},
{
"frame_id": "frame002",
"src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+2"
},
{
"frame_id": "frame003",
"src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+3"
},
{
"frame_id": "frame004",
"src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+4"
},
{
"frame_id": "frame005",
"src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+5"
}
],
},
"tag": "object_tracking"
}'package main
import (
"fmt"
"strings"
"net/http"
"io/ioutil"
)
func main() {
url := "https://api.playment.in/v1/project/:projectId/feedline"
payload := strings.NewReader("{\n \"reference_id\": \"sample_reference_id\",\n \"data\": {\n \"frames\": [\n {\n \"frame_id\": \"frame001\",\n \"src\": \"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1\"\n },\n {\n \"frame_id\": \"frame002\",\n \"src\": \"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+2\"\n },\n {\n \"frame_id\": \"frame003\",\n \"src\": \"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+3\"\n },\n {\n \"frame_id\": \"frame004\",\n \"src\": \"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+4\"\n },\n {\n \"frame_id\": \"frame005\",\n \"src\": \"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+5\"\n }\n ],\n \n },\n \"tag\": \"object_tracking\"\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("x-client-key", "<your x-client-key here>")
req.Header.Add("Content-Type", "application/json")
req.Header.Add("cache-control", "no-cache")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := ioutil.ReadAll(res.Body)
fmt.Println(res)
fmt.Println(string(body))
}import http.client
conn = http.client.HTTPConnection("api,playment,in")
payload = "{\n \"reference_id\": \"sample_reference_id\",\n \"data\": {\n \"frames\": [\n {\n \"frame_id\": \"frame001\",\n \"src\": \"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1\"\n },\n {\n \"frame_id\": \"frame002\",\n \"src\": \"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+2\"\n },\n {\n \"frame_id\": \"frame003\",\n \"src\": \"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+3\"\n },\n {\n \"frame_id\": \"frame004\",\n \"src\": \"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+4\"\n },\n {\n \"frame_id\": \"frame005\",\n \"src\": \"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+5\"\n }\n ],\n \n },\n \"tag\": \"object_tracking\"\n}"
headers = {
'x-client-key': "<your x-client-key here>",
'Content-Type': "application/json",
'cache-control': "no-cache",
}
conn.request("POST", "v1,project,:projectId,feedline", payload, headers)
res = conn.getresponse()
data = res.read()
print(data.decode("utf-8"))var request = require("request");
var options = { method: 'POST',
url: 'https://api.playment.in/v1/project/:projectId/feedline',
headers:
{ 'cache-control': 'no-cache',
'Content-Type': 'application/json',
'x-client-key': '<your x-client-key here>' },
body: '{\n "reference_id": "sample_reference_id",\n "data": {\n "frames": [\n {\n "frame_id": "frame001",\n "src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1"\n },\n {\n "frame_id": "frame002",\n "src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+2"\n },\n {\n "frame_id": "frame003",\n "src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+3"\n },\n {\n "frame_id": "frame004",\n "src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+4"\n },\n {\n "frame_id": "frame005",\n "src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+5"\n }\n ],\n \n },\n "tag": "object_tracking"\n}' };
request(options, function (error, response, body) {
if (error) throw new Error(error);
console.log(body);
});
{
"feed_line_units": [
{
"reference_id": "001",
"flu_id": "sample_reference_id",
"status": "COMPLETED",
"tag": "object_tracking",
"result": [
{
"_id": "555397a8-d916-443d-a973-e04300bb3d59",
"type": "rectangle",
"label": "traffic_light",
"frames": {
"frame001": {
"_id": "555397a8-d916-443d-a973-e04300bb3d59",
"type": "rectangle",
"label": "traffic_light",
"attributes": {
"color": {
"value": "red"
}
},
"coordinates": [
{
"x": 0.5435780444531554,
"y": 0.3925569183910122
},
{
"x": 0.5477217039572666,
"y": 0.3925569183910122
},
{
"x": 0.5477217039572666,
"y": 0.41283176820041856
},
{
"x": 0.5435780444531554,
"y": 0.41283176820041856
}
]
},
"frame002": {
"_id": "555397a8-d916-443d-a973-e04300bb3d59",
"type": "rectangle",
"label": "traffic_light",
"attributes": {
"color": {
"value": "green"
}
},
"coordinates": [
{
"x": 0.5464092560993109,
"y": 0.4103705019588349
},
{
"x": 0.5508899646089167,
"y": 0.4103705019588349
},
{
"x": 0.5508899646089167,
"y": 0.4327607148169202
},
{
"x": 0.5464092560993109,
"y": 0.4327607148169202
}
]
}
}
},
{
"_id": "057cf1f5-6c15-4f29-9775-940cf27643f4",
"type": "rectangle",
"label": "traffic_light",
"frames": {
"frame002": {
"_id": "057cf1f5-6c15-4f29-9775-940cf27643f4",
"type": "rectangle",
"label": "traffic_light",
"attributes": {
"color": {
"value": "off"
}
},
"coordinates": [
{
"x": 0.3480726842916043,
"y": 0.5059539147455372
},
{
"x": 0.3526237778854049,
"y": 0.5059539147455372
},
{
"x": 0.3526237778854049,
"y": 0.5252503794751654
},
{
"x": 0.3480726842916043,
"y": 0.5252503794751654
}
]
},
"frame003": {
"_id": "057cf1f5-6c15-4f29-9775-940cf27643f4",
"type": "rectangle",
"label": "traffic_light",
"attributes": {
"color": {
"value": "off"
}
},
"coordinates": [
{
"x": 0.3418031924762347,
"y": 0.5049184373876437
},
{
"x": 0.3465110233654195,
"y": 0.5049184373876437
},
{
"x": 0.3465110233654195,
"y": 0.5252503794751653
},
{
"x": 0.3418031924762347,
"y": 0.5252503794751653
}
]
}
}
}
]
}
]
}Line Tracking
Lines for object tracking in video across frames.
{
"reference_id": "sample_reference_id",
"data": {
"video_data": {
"frames": [
{
"frame_id": "frame001",
"src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1"
},
{
"frame_id": "frame002",
"src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+2"
},
{
"frame_id": "frame003",
"src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+3"
},
{
"frame_id": "frame004",
"src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+4"
},
{
"frame_id": "frame005",
"src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+5"
}
],
}
},
"tag": "polygon_tracking"
}curl -X POST \
https://api.playment.in/v1/project/:projectId/feedline \
-H 'Content-Type: application/json' \
-H 'cache-control: no-cache' \
-H 'x-client-key: <your x-client-key here>' \
-d '{
"reference_id": "sample_reference_id",
"data": {
"frames": [
{
"frame_id": "frame001",
"src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1"
},
{
"frame_id": "frame002",
"src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+2"
},
{
"frame_id": "frame003",
"src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+3"
},
{
"frame_id": "frame004",
"src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+4"
},
{
"frame_id": "frame005",
"src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+5"
}
],
},
"tag": "polygon_tracking"
}'package main
import (
"fmt"
"strings"
"net/http"
"io/ioutil"
)
func main() {
url := "https://api.playment.in/v1/project/:projectId/feedline"
payload := strings.NewReader("{\n \"reference_id\": \"sample_reference_id\",\n \"data\": {\n \"frames\": [\n {\n \"frame_id\": \"frame001\",\n \"src\": \"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1\"\n },\n {\n \"frame_id\": \"frame002\",\n \"src\": \"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+2\"\n },\n {\n \"frame_id\": \"frame003\",\n \"src\": \"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+3\"\n },\n {\n \"frame_id\": \"frame004\",\n \"src\": \"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+4\"\n },\n {\n \"frame_id\": \"frame005\",\n \"src\": \"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+5\"\n }\n ],\n \n },\n \"tag\": \"polygon_tracking\"\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("x-client-key", "<your x-client-key here>")
req.Header.Add("Content-Type", "application/json")
req.Header.Add("cache-control", "no-cache")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := ioutil.ReadAll(res.Body)
fmt.Println(res)
fmt.Println(string(body))
}import http.client
conn = http.client.HTTPConnection("api,playment,in")
payload = "{\n \"reference_id\": \"sample_reference_id\",\n \"data\": {\n \"frames\": [\n {\n \"frame_id\": \"frame001\",\n \"src\": \"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1\"\n },\n {\n \"frame_id\": \"frame002\",\n \"src\": \"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+2\"\n },\n {\n \"frame_id\": \"frame003\",\n \"src\": \"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+3\"\n },\n {\n \"frame_id\": \"frame004\",\n \"src\": \"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+4\"\n },\n {\n \"frame_id\": \"frame005\",\n \"src\": \"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+5\"\n }\n ],\n \n },\n \"tag\": \"polygon_tracking\"\n}"
headers = {
'x-client-key': "<your x-client-key here>",
'Content-Type': "application/json",
'cache-control': "no-cache",
}
conn.request("POST", "v1,project,:projectId,feedline", payload, headers)
res = conn.getresponse()
data = res.read()
print(data.decode("utf-8"))var request = require("request");
var options = { method: 'POST',
url: 'https://api.playment.in/v1/project/:projectId/feedline',
headers:
{ 'cache-control': 'no-cache',
'Content-Type': 'application/json',
'x-client-key': '<your x-client-key here>' },
body: '{\n "reference_id": "sample_reference_id",\n "data": {\n "frames": [\n {\n "frame_id": "frame001",\n "src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1"\n },\n {\n "frame_id": "frame002",\n "src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+2"\n },\n {\n "frame_id": "frame003",\n "src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+3"\n },\n {\n "frame_id": "frame004",\n "src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+4"\n },\n {\n "frame_id": "frame005",\n "src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+5"\n }\n ],\n \n },\n "tag": "polygon_tracking"\n}' };
request(options, function (error, response, body) {
if (error) throw new Error(error);
console.log(body);
});
{
"feed_line_units": [
{
"reference_id": "001",
"flu_id": "sample_reference_id",
"status": "COMPLETED",
"tag": "polygon_tracking",
"result": [
{
"type": "line",
"label": "Lane",
"frames": {
"frame001": {
"points": {
"p1": {
"x": 0.5976247987117552,
"y": 0.7766666666666666
},
"p2": {
"x": 0.5040257648953301,
"y": 0.5233333333333333
}
},
"attributes": {
"Occlusion": {
"value": "10%"
}
}
},
"frame002": {
"points": {
"p1": {
"x": 0.5976247987117552,
"y": 0.7733333333333332
},
"p2": {
"x": 0.5040257648953301,
"y": 0.52
}
},
"attributes": {
"Occlusion": {
"value": "50%"
}
}
},
"frame003": {
"points": {
"p1": {
"x": 0.5976247987117552,
"y": 0.7766666666666666
},
"p2": {
"x": 0.5040257648953301,
"y": 0.5233333333333333
}
},
"attributes": {
"Occlusion": {
"value": "10%"
}
}
},
"frame004": {
"points": {
"p1": {
"x": 0.5976247987117552,
"y": 0.7766666666666666
},
"p2": {
"x": 0.5040257648953301,
"y": 0.5233333333333333
}
},
"attributes": {
"Occlusion": {
"value": "10%"
}
}
},
"frame005": {
"points": {
"p1": {
"x": 0.5976247987117552,
"y": 0.7766666666666666
},
"p2": {
"x": 0.5040257648953301,
"y": 0.5233333333333333
}
},
"attributes": {
"Occlusion": {
"value": "40%"
}
}
}
},
"tracker_id": "cf8ba34a-78ab-402b-b386-daa607cda443"
}
]
}
]
}Cuboid Tracking
2D Cuboids for object tracking in image videos across frames.
{
"reference_id": "sample_reference_id",
"data": {
"video_data": {
"frames": [
{
"frame_id": "frame001",
"src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1"
},
{
"frame_id": "frame002",
"src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+2"
},
{
"frame_id": "frame003",
"src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+3"
},
{
"frame_id": "frame004",
"src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+4"
},
{
"frame_id": "frame005",
"src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+5"
}
],
}
},
"tag": "cuboid_tracking"
}curl -X POST \
https://api.playment.in/v1/project/:projectId/feedline \
-H 'Content-Type: application/json' \
-H 'cache-control: no-cache' \
-H 'x-client-key: <your x-client-key here>' \
-d '{
"reference_id": "sample_reference_id",
"data": {
"frames": [
{
"frame_id": "frame001",
"src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1"
},
{
"frame_id": "frame002",
"src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+2"
},
{
"frame_id": "frame003",
"src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+3"
},
{
"frame_id": "frame004",
"src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+4"
},
{
"frame_id": "frame005",
"src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+5"
}
],
},
"tag": "cuboid_tracking"
}'package main
import (
"fmt"
"strings"
"net/http"
"io/ioutil"
)
func main() {
url := "https://api.playment.in/v1/project/:projectId/feedline"
payload := strings.NewReader("{\n \"reference_id\": \"sample_reference_id\",\n \"data\": {\n \"frames\": [\n {\n \"frame_id\": \"frame001\",\n \"src\": \"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1\"\n },\n {\n \"frame_id\": \"frame002\",\n \"src\": \"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+2\"\n },\n {\n \"frame_id\": \"frame003\",\n \"src\": \"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+3\"\n },\n {\n \"frame_id\": \"frame004\",\n \"src\": \"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+4\"\n },\n {\n \"frame_id\": \"frame005\",\n \"src\": \"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+5\"\n }\n ],\n \n },\n \"tag\": \"cuboid_tracking\"\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("x-client-key", "<your x-client-key here>")
req.Header.Add("Content-Type", "application/json")
req.Header.Add("cache-control", "no-cache")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := ioutil.ReadAll(res.Body)
fmt.Println(res)
fmt.Println(string(body))
}import http.client
conn = http.client.HTTPConnection("api,playment,in")
payload = "{\n \"reference_id\": \"sample_reference_id\",\n \"data\": {\n \"frames\": [\n {\n \"frame_id\": \"frame001\",\n \"src\": \"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1\"\n },\n {\n \"frame_id\": \"frame002\",\n \"src\": \"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+2\"\n },\n {\n \"frame_id\": \"frame003\",\n \"src\": \"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+3\"\n },\n {\n \"frame_id\": \"frame004\",\n \"src\": \"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+4\"\n },\n {\n \"frame_id\": \"frame005\",\n \"src\": \"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+5\"\n }\n ],\n \n },\n \"tag\": \"cuboid_tracking\"\n}"
headers = {
'x-client-key': "<your x-client-key here>",
'Content-Type': "application/json",
'cache-control': "no-cache",
}
conn.request("POST", "v1,project,:projectId,feedline", payload, headers)
res = conn.getresponse()
data = res.read()
print(data.decode("utf-8"))var request = require("request");
var options = { method: 'POST',
url: 'https://api.playment.in/v1/project/:projectId/feedline',
headers:
{ 'cache-control': 'no-cache',
'Content-Type': 'application/json',
'x-client-key': '<your x-client-key here>' },
body: '{\n "reference_id": "sample_reference_id",\n "data": {\n "frames": [\n {\n "frame_id": "frame001",\n "src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1"\n },\n {\n "frame_id": "frame002",\n "src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+2"\n },\n {\n "frame_id": "frame003",\n "src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+3"\n },\n {\n "frame_id": "frame004",\n "src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+4"\n },\n {\n "frame_id": "frame005",\n "src": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+5"\n }\n ],\n \n },\n "tag": "cuboid_tracking"\n}' };
request(options, function (error, response, body) {
if (error) throw new Error(error);
console.log(body);
});
{
"feed_line_units": [
{
"reference_id": "001",
"flu_id": "sample_reference_id",
"status": "COMPLETED",
"tag": "polygon_tracking",
"result": [
{
"type": "cuboid",
"label": "Car",
"frames": {
"frame001": {
"points": {
"p1": {
"x": 0.15982286634460555,
"y": 0.54
},
"p2": {
"x": 0.267512077294686,
"y": 0.54
},
"p3": {
"x": 0.267512077294686,
"y": 0.8
},
"p4": {
"x": 0.15982286634460555,
"y": 0.8
},
"p5": {
"x": 0.3852657004830917,
"y": 0.48833333333333334
},
"p6": {
"x": 0.3852657004830917,
"y": 0.7283333333333334
},
"p7": {
"x": 0.28586027499070976,
"y": 0.48833333333333334
},
"p8": {
"x": 0.28586027499070976,
"y": 0.7283333333333334
}
},
"attributes": {
"Lane": {
"value": "Same as ego car"
}
},
"front": {
"coordinates": [
"p1",
"p2",
"p3",
"p4"
]
},
"side": {
"coordinates": [
"p2",
"p5",
"p6",
"p3"
]
},
"back": {
"coordinates": [
"p5",
"p7",
"p8",
"p6"
]
}
},
"frame002": {
"points": {
"p1": {
"x": 0.11352657004830924,
"y": 0.56
},
"p2": {
"x": 0.22121578099838982,
"y": 0.56
},
"p3": {
"x": 0.22121578099838982,
"y": 0.82
},
"p4": {
"x": 0.11352657004830924,
"y": 0.82
},
"p5": {
"x": 0.33896940418679555,
"y": 0.5083333333333332
},
"p6": {
"x": 0.33896940418679555,
"y": 0.7483333333333332
},
"p7": {
"x": 0.23956397869441343,
"y": 0.5083333333333332
},
"p8": {
"x": 0.23956397869441343,
"y": 0.7483333333333332
}
},
"attributes": {
"Lane": {
"value": "Same as ego car"
}
},
"front": {
"coordinates": [
"p1",
"p2",
"p3",
"p4"
]
},
"side": {
"coordinates": [
"p2",
"p5",
"p6",
"p3"
]
},
"back": {
"coordinates": [
"p5",
"p7",
"p8",
"p6"
]
}
},
"frame003": {
"points": {
"p1": {
"x": 0.036030595813204405,
"y": 0.5966666666666667
},
"p2": {
"x": 0.14371980676328497,
"y": 0.5966666666666667
},
"p3": {
"x": 0.14371980676328497,
"y": 0.8566666666666667
},
"p4": {
"x": 0.036030595813204405,
"y": 0.8566666666666667
},
"p5": {
"x": 0.26147342995169087,
"y": 0.5449999999999999
},
"p6": {
"x": 0.26147342995169087,
"y": 0.7849999999999998
},
"p7": {
"x": 0.16206800445930886,
"y": 0.5449999999999999
},
"p8": {
"x": 0.16206800445930886,
"y": 0.7849999999999998
}
},
"attributes": {
"Lane": {
"value": "Side"
}
},
"front": {
"coordinates": [
"p1",
"p2",
"p3",
"p4"
]
},
"side": {
"coordinates": [
"p2",
"p5",
"p6",
"p3"
]
},
"back": {
"coordinates": [
"p5",
"p7",
"p8",
"p6"
]
}
},
"frame004": {
"points": {
"p1": {
"x": -0.06763285024154582,
"y": 0.6466666666666666
},
"p2": {
"x": 0.04005636070853473,
"y": 0.6466666666666666
},
"p3": {
"x": 0.04005636070853473,
"y": 0.9066666666666666
},
"p4": {
"x": -0.06763285024154582,
"y": 0.9066666666666666
},
"p5": {
"x": 0.15780998389694048,
"y": 0.5949999999999999
},
"p6": {
"x": 0.15780998389694048,
"y": 0.8349999999999999
},
"p7": {
"x": 0.05840455840455844,
"y": 0.5949999999999999
},
"p8": {
"x": 0.05840455840455844,
"y": 0.8349999999999999
}
},
"attributes": {
"Lane": {
"value": "Side"
}
},
"front": {
"coordinates": [
"p1",
"p2",
"p3",
"p4"
]
},
"side": {
"coordinates": [
"p2",
"p5",
"p6",
"p3"
]
},
"back": {
"coordinates": [
"p5",
"p7",
"p8",
"p6"
]
}
},
"frame005": {
"points": {
"p1": {
"x": -0.13103864734299503,
"y": 0.5833333333333334
},
"p2": {
"x": -0.015096618357487952,
"y": 0.5833333333333334
},
"p3": {
"x": -0.015096618357487952,
"y": 0.9
},
"p4": {
"x": -0.13103864734299503,
"y": 0.9
},
"p5": {
"x": 0.1869967793880838,
"y": 0.49833333333333335
},
"p6": {
"x": 0.1869967793880838,
"y": 0.8283333333333334
},
"p7": {
"x": 0.06617298076108166,
"y": 0.49833333333333335
},
"p8": {
"x": 0.06617298076108166,
"y": 0.8283333333333334
}
},
"attributes": {
"Lane": {
"value": "Side"
}
},
"front": {
"coordinates": [
"p1",
"p2",
"p3",
"p4"
]
},
"side": {
"coordinates": [
"p2",
"p5",
"p6",
"p3"
]
},
"back": {
"coordinates": [
"p5",
"p7",
"p8",
"p6"
]
}
}
},
"tracker_id": "bab6690f-c6de-446b-b372-0ef3743abe35"
}
]
}
]
}Semantic Segmentation
Assign a label to each pixel in an image
Full Pixel Semantic Segmentation for Autonomous driving
{
"reference_id":"001",
"data":{
"image_url":"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1"
},
"tag":"semantic_segmentation"
}curl -X POST \
https://api.playment.in/v1/project/:projectId/feedline \
-H 'Content-Type: application/json' \
-H 'cache-control: no-cache' \
-H 'x-client-key: <your x-client-key here>' \
-d '{
"reference_id":"001",
"data":{
"image_url":"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1"
},
"tag":"semantic_segmentation"
}'package main
import (
"fmt"
"strings"
"net/http"
"io/ioutil"
)
func main() {
url := "https://api.playment.in/v1/project/:projectId/feedline"
payload := strings.NewReader("{ \n \"reference_id\":\"001\",\n \"data\":{\n \"image_url\":\"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1\"\n },\n \"tag\":\"semantic_segmentation\"\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("x-client-key", "<your x-client-key here>")
req.Header.Add("Content-Type", "application/json")
req.Header.Add("cache-control", "no-cache")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := ioutil.ReadAll(res.Body)
fmt.Println(res)
fmt.Println(string(body))
}import http.client
conn = http.client.HTTPConnection("api,playment,in")
payload = "{ \n \"reference_id\":\"001\",\n \"data\":{\n \"image_url\":\"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1\"\n },\n \"tag\":\"semantic_segmentation\"\n}"
headers = {
'x-client-key': "<your x-client-key here>",
'Content-Type': "application/json",
'cache-control': "no-cache",
}
conn.request("POST", "v1,project,:projectId,feedline", payload, headers)
res = conn.getresponse()
data = res.read()
print(data.decode("utf-8"))var request = require("request");
var options = { method: 'POST',
url: 'https://api.playment.in/v1/project/:projectId/feedline',
headers:
{ 'cache-control': 'no-cache',
'Content-Type': 'application/json',
'x-client-key': '<your x-client-key here>' },
body:
{ reference_id: '001',
data: { image_url: 'https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1' },
tag: 'semantic_segmentation' },
json: true };
request(options, function (error, response, body) {
if (error) throw new Error(error);
console.log(body);
});
{
"feed_line_units": [
{
"reference_id": "001",
"flu_id": "3bcbc3fe-9fbc-4d7c-b951-a1d1bfb6f840",
"status": "COMPLETED",
"tag": "semantic_segmentation",
"image_url": "https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1",
"result": {
"grayscale_mask": "https://example.playment.io/001_grayscale.png",
"grayscale_label_map": {
"car" : "1",
"pedestrian" : "2"
},
"rgb_mask": "https://example.playment.io/001_rgb.png",
"rgb_label_map": {
"car" : "#001ADE",
"pedestrian" : "#BDF032"
}
}
}
]
}Instance Segmentation
Assign an instanceID to each object present in the image.
Semantic Instance Segmented street scene
{
"reference_id":"001",
"data":{
"image_url":"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1"
},
"tag":"instance_segmentation"
}curl -X POST \
https://api.playment.in/v1/project/:projectId/feedline \
-H 'Content-Type: application/json' \
-H 'cache-control: no-cache' \
-H 'x-client-key: <your x-client-key here>' \
-d '{
"reference_id":"001",
"data":{
"image_url":"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1"
},
"tag":"semantic_segmentation"
}'package main
import (
"fmt"
"strings"
"net/http"
"io/ioutil"
)
func main() {
url := "https://api.playment.in/v1/project/:projectId/feedline"
payload := strings.NewReader("{ \n \"reference_id\":\"001\",\n \"data\":{\n \"image_url\":\"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1\"\n },\n \"tag\":\"instance_segmentation\"\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("x-client-key", "<your x-client-key here>")
req.Header.Add("Content-Type", "application/json")
req.Header.Add("cache-control", "no-cache")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := ioutil.ReadAll(res.Body)
fmt.Println(res)
fmt.Println(string(body))
}import http.client
conn = http.client.HTTPConnection("api,playment,in")
payload = "{ \n \"reference_id\":\"001\",\n \"data\":{\n \"image_url\":\"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1\"\n },\n \"tag\":\"instance_segmentation\"\n}"
headers = {
'x-client-key': "<your x-client-key here>",
'Content-Type': "application/json",
'cache-control': "no-cache",
}
conn.request("POST", "v1,project,:projectId,feedline", payload, headers)
res = conn.getresponse()
data = res.read()
print(data.decode("utf-8"))var request = require("request");
var options = { method: 'POST',
url: 'https://api.playment.in/v1/project/:projectId/feedline',
headers:
{ 'cache-control': 'no-cache',
'Content-Type': 'application/json',
'x-client-key': '<your x-client-key here>' },
body:
{ reference_id: '001',
data: { image_url: 'https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1' },
tag: 'instance_segmentation' },
json: true };
request(options, function (error, response, body) {
if (error) throw new Error(error);
console.log(body);
});
{
"feed_line_units": [
{
"reference_id": "001",
"flu_id": "3bcbc3fe-9fbc-4d7c-b951-a1d1bfb6f840",
"status": "COMPLETED",
"tag": "instance_segmentation",
"result": {
"combined": {
"image_url": "https://example.playment.io/001_rgb.png",
"mapping": [
{
"color": "#fdffd34",
"label": "Car"
},
{
"color": "#f1fd34",
"label": "Car"
},
{
"color": "#f23334",
"label": "Sky"
},
{
"color": "#fd2d34",
"label": "Tree"
}
]
},
"annotations": [
{
"url": "https://example.playment.io/003_rgb.png",
"index_url": "https://example.playment.io/003_index.png",
"label": "Car",
"instances": [
{
"color": "#fdffd34",
"index": "1"
},
{
"color": "#f1fd34",
"index": "2"
}
]
},
{
"url": "https://example.playment.io/004_rgb.png",
"index_url": "https://example.playment.io/004_index.png",
"label": "Tree",
"color": "#fd2d34",
"index": "3"
},
{
"url": "https://example.playment.io/005_rgb.png",
"index_url": "https://example.playment.io/004_index.png",
"label": "Sky",
"color": "#f23334",
"index": "4"
}
]
}
}
]
}Cuboids
Label perspective cuboids with coordinates of 6 vertices for any object in a 2D image for camera based depth perception models
{
"reference_id":"002",
"data":{
"image_url":"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1"
},
"tag":"draw_cuboids"
}curl -X POST \
https://api.playment.in/v1/project/:projectId/feedline \
-H 'Content-Type: application/json' \
-H 'cache-control: no-cache' \
-H 'x-client-key: <your x-client-key here>' \
-d '{
"reference_id":"001",
"data":{
"image_url":"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1"
},
"tag":"draw_cuboids"
}'package main
import (
"fmt"
"strings"
"net/http"
"io/ioutil"
)
func main() {
url := "https://api.playment.in/v1/project/:projectId/feedline"
payload := strings.NewReader("{ \n \"reference_id\":\"001\",\n \"data\":{\n \"image_url\":\"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1\"\n },\n \"tag\":\"draw_cuboids\"\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("x-client-key", "<your x-client-key here>")
req.Header.Add("Content-Type", "application/json")
req.Header.Add("cache-control", "no-cache")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := ioutil.ReadAll(res.Body)
fmt.Println(res)
fmt.Println(string(body))
}import http.client
conn = http.client.HTTPConnection("api,playment,in")
payload = "{ \n \"reference_id\":\"001\",\n \"data\":{\n \"image_url\":\"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1\"\n },\n \"tag\":\"draw_cuboids\"\n}"
headers = {
'x-client-key': "<your x-client-key here>",
'Content-Type': "application/json",
'cache-control': "no-cache"
}
conn.request("POST", "v1,project,:projectId,feedline", payload, headers)
res = conn.getresponse()
data = res.read()
print(data.decode("utf-8"))var request = require("request");
var options = { method: 'POST',
url: 'https://api.playment.in/v1/project/:projectId/feedline',
headers:
{ 'cache-control': 'no-cache',
'Content-Type': 'application/json',
'x-client-key': '<your x-client-key here>' },
body:
{ reference_id: '001',
data: { image_url: 'https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1' },
tag: 'draw_cuboids' },
json: true };
request(options, function (error, response, body) {
if (error) throw new Error(error);
console.log(body);
});
{
"feed_line_units": [{
"reference_id": "002",
"flu_id": "3bcbc3fe-9fbc-4d7c-b951-a1d1bfb6f840",
"status": "COMPLETED",
"tag": "draw_cuboids",
"result": {
"cuboids": [{
"points": {
"p1": {"x": 0.17,"y": 0.58},
"p2": {"x": 0.26,"y": 0.58},
"p3": {"x": 0.26,"y": 0.49},
"p4": {"x": 0.17,"y": 0.49},
"p5": {"x": 0.24,"y": 0.51},
"p6": {"x": 0.35,"y": 0.52},
"p7": {"x": 0.35,"y": 0.36},
"p8": {"x": 0.25,"y": 0.37}
},
"front": {
"coordinates": ["p1","p2","p3","p4"] //clockwise
},
"side": {
"coordinates": ["p2","p3","p5","p6"]
},
"back": {
"coordinates": ["p7","p8","p5","p6"]
},
"label": "Car - Sedan",
"faces_visible": ["right","back"]
}
]
}
}]
}Landmarks
Facial landmark annotations for facial feature understanding
Landmarks on Human Face
{
"reference_id":"001",
"data":{
"image_url":"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1"
},
"tag":"draw_landmarks"
}curl -X POST \
https://api.playment.in/v1/project/:projectId/feedline \
-H 'Content-Type: application/json' \
-H 'cache-control: no-cache' \
-H 'x-client-key: <your x-client-key here>' \
-d '{
"reference_id":"001",
"data":{
"image_url":"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1"
},
"tag":"draw_landmarks"
}'package main
import (
"fmt"
"strings"
"net/http"
"io/ioutil"
)
func main() {
url := "https://api.playment.in/v1/project/:projectId/feedline"
payload := strings.NewReader("{ \n \"reference_id\":\"001\",\n \"data\":{\n \"image_url\":\"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1\"\n },\n \"tag\":\"draw_landmarks\"\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("x-client-key", "<your x-client-key here>")
req.Header.Add("Content-Type", "application/json")
req.Header.Add("cache-control", "no-cache")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := ioutil.ReadAll(res.Body)
fmt.Println(res)
fmt.Println(string(body))
}import http.client
conn = http.client.HTTPConnection("api,playment,in")
payload = "{ \n \"reference_id\":\"001\",\n \"data\":{\n \"image_url\":\"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1\"\n },\n \"tag\":\"draw_landmarks\"\n}"
headers = {
'x-client-key': "<your x-client-key here>",
'Content-Type': "application/json",
'cache-control': "no-cache"
}
conn.request("POST", "v1,project,:projectId,feedline", payload, headers)
res = conn.getresponse()
data = res.read()
print(data.decode("utf-8"))var request = require("request");
var options = { method: 'POST',
url: 'https://api.playment.in/v1/project/:projectId/feedline',
headers:
{ 'cache-control': 'no-cache',
'Content-Type': 'application/json',
'x-client-key': '<your x-client-key here>' },
body:
{ reference_id: '001',
data: { image_url: 'https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1' },
tag: 'draw_landmarks' },
json: true };
request(options, function (error, response, body) {
if (error) throw new Error(error);
console.log(body);
});
{
"feed_line_units": [{
"reference_id": "002",
"flu_id": "3bcbc3fe-9fbc-4d7c-b951-a1d1bfb6f840",
"status": "COMPLETED",
"tag": "draw_landmarks",
"result": {
"landmarks": [{
"points": {
"p1": { "x": 0.17, "y": 0.58, "label": 1 },
"p2": { "x": 0.26, "y": 0.63, "label": 2 },
"p3": { "x": 0.27, "y": 0.63, "label": 3 },
"p4": { "x": 0.29, "y": 0.59, "label": 4 },
"p5": { "x": 0.25, "y": 0.46, "label": 5 },
"p6": { "x": 0.22, "y": 0.42, "label": 6 }
},
"label": "nose"
}, {
"points": {
"p1": { "x": 0.17, "y": 0.58, "label": 7 },
"p2": { "x": 0.26, "y": 0.63, "label": 8 },
"p3": { "x": 0.27, "y": 0.63, "label": 9 },
"p4": { "x": 0.29, "y": 0.59, "label": 10 },
"p5": { "x": 0.25, "y": 0.46, "label": 11 },
"p6": { "x": 0.22, "y": 0.42, "label": 12 }
},
"label": "left-ear"
}]
}
}]
}Polygons
Annotate object instances with polygons instead of pixel segmentation
Detect vehicles on road
{
"reference_id":"001",
"data":{
"image_url":"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1"
},
"tag":"draw_polygons"
}curl -X POST \
https://api.playment.in/v1/project/:projectId/feedline \
-H 'Content-Type: application/json' \
-H 'cache-control: no-cache' \
-H 'x-client-key: <your x-client-key here>' \
-d '{
"reference_id":"001",
"data":{
"image_url":"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1"
},
"tag":"draw_polygons"
}'package main
import (
"fmt"
"strings"
"net/http"
"io/ioutil"
)
func main() {
url := "https://api.playment.in/v1/project/:projectId/feedline"
payload := strings.NewReader("{ \n \"reference_id\":\"001\",\n \"data\":{\n \"image_url\":\"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1\"\n },\n \"tag\":\"draw_polygons\"\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("x-client-key", "<your x-client-key here>")
req.Header.Add("Content-Type", "application/json")
req.Header.Add("cache-control", "no-cache")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := ioutil.ReadAll(res.Body)
fmt.Println(res)
fmt.Println(string(body))
}import http.client
conn = http.client.HTTPConnection("api,playment,in")
payload = "{ \n \"reference_id\":\"001\",\n \"data\":{\n \"image_url\":\"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1\"\n },\n \"tag\":\"draw_polygons\"\n}"
headers = {
'x-client-key': "<your x-client-key here>",
'Content-Type': "application/json",
'cache-control': "no-cache"
}
conn.request("POST", "v1,project,:projectId,feedline", payload, headers)
res = conn.getresponse()
data = res.read()
print(data.decode("utf-8"))var request = require("request");
var options = { method: 'POST',
url: 'https://api.playment.in/v1/project/:projectId/feedline',
headers:
{ 'cache-control': 'no-cache',
'Content-Type': 'application/json',
'x-client-key': '<your x-client-key here>' },
body:
{ reference_id: '001',
data: { image_url: 'https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1' },
tag: 'draw_polygons' },
json: true };
request(options, function (error, response, body) {
if (error) throw new Error(error);
console.log(body);
});
{
"feed_line_units": [{
"reference_id": "001",
"flu_id": "3bcbc3fe-9fbc-4d7c-b951-a1d1bfb6f840",
"status": "COMPLETED",
"tag": "draw_polygons",
"result": {
"polygons": [{
"points": {
"p1": {"x": 0.17,"y": 0.58},
"p2": {"x": 0.26,"y": 0.63},
"p3": {"x": 0.27,"y": 0.63},
"p4": {"x": 0.29,"y": 0.59},
"p5": {"x": 0.25,"y": 0.46},
"p6": {"x": 0.22,"y": 0.42}
},
"edges": {
"e1": ["p1","p2"],
"e2": ["p2","p3"],
"e3": ["p3","p4"],
"e4": ["p4","p5"],
"e5": ["p5","p6"],
"e6": ["p6","p7"],
"e7": ["p8","p9"]
},
"label": "Sofa"
}
]
}
}]
}Bounding Box Validation
Validate the performance of your object detection models
{
"reference_id":"001",
"data":{
"image_url":"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1",
"boxes": [{
"id" : "box_0001",
"label": "car",
"coordinates": [
{"x": 0.38, "y": 0.19},
{"x": 0.57, "y": 0.19},
{"x": 0.57, "y": 0.44},
{"x": 0.38, "y": 0.44}]
},
{
"id" : "box_0002",
"label": "van",
"coordinates": [
{"x": 0.38, "y": 0.19},
{"x": 0.57, "y": 0.19},
{"x": 0.57, "y": 0.44},
{"x": 0.38, "y": 0.44}]
}]
},
"tag":"validate_boxes"
}curl -X POST \
https://api.playment.in/v1/project/:projectId/feedline \
-H 'Content-Type: application/json' \
-H 'cache-control: no-cache' \
-H 'x-client-key: <your x-client-key here>' \
-d '{
"reference_id":"001",
"data":{
"image_url":"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1",
"boxes": [{
"id" : "box_0001",
"label": "car",
"coordinates": [
{"x": 0.38, "y": 0.19},
{"x": 0.57, "y": 0.19},
{"x": 0.57, "y": 0.44},
{"x": 0.38, "y": 0.44}]
},
{
"id" : "box_0002",
"label": "van",
"coordinates": [
{"x": 0.38, "y": 0.19},
{"x": 0.57, "y": 0.19},
{"x": 0.57, "y": 0.44},
{"x": 0.38, "y": 0.44}]
}]
},
"tag":"validate_boxes"
}'package main
import (
"fmt"
"strings"
"net/http"
"io/ioutil"
)
func main() {
url := "https://api.playment.in/v1/project/:projectId/feedline"
payload := strings.NewReader("{ \n \"reference_id\":\"001\",\n \"data\":{\n \"image_url\":\"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1\",\n \"boxes\": [{\n \t \"id\" : \"box_0001\",\n \"label\": \"car\",\n \"coordinates\": [\n {\"x\": 0.38, \"y\": 0.19}, \n {\"x\": 0.57, \"y\": 0.19}, \n {\"x\": 0.57, \"y\": 0.44}, \n {\"x\": 0.38, \"y\": 0.44}]\n },\n {\n \"id\" : \"box_0002\",\n \"label\": \"van\",\n \"coordinates\": [\n {\"x\": 0.38, \"y\": 0.19}, \n {\"x\": 0.57, \"y\": 0.19}, \n {\"x\": 0.57, \"y\": 0.44}, \n {\"x\": 0.38, \"y\": 0.44}]\n }]\n },\n \"tag\":\"validate_boxes\"\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("x-client-key", "<your x-client-key here>")
req.Header.Add("Content-Type", "application/json")
req.Header.Add("cache-control", "no-cache")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := ioutil.ReadAll(res.Body)
fmt.Println(res)
fmt.Println(string(body))
}import http.client
conn = http.client.HTTPConnection("api,playment,in")
payload = "{ \n \"reference_id\":\"001\",\n \"data\":{\n \"image_url\":\"https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1\",\n \"boxes\": [{\n \t \"id\" : \"box_0001\",\n \"label\": \"car\",\n \"coordinates\": [\n {\"x\": 0.38, \"y\": 0.19}, \n {\"x\": 0.57, \"y\": 0.19}, \n {\"x\": 0.57, \"y\": 0.44}, \n {\"x\": 0.38, \"y\": 0.44}]\n },\n {\n \"id\" : \"box_0002\",\n \"label\": \"van\",\n \"coordinates\": [\n {\"x\": 0.38, \"y\": 0.19}, \n {\"x\": 0.57, \"y\": 0.19}, \n {\"x\": 0.57, \"y\": 0.44}, \n {\"x\": 0.38, \"y\": 0.44}]\n }]\n },\n \"tag\":\"validate_boxes\"\n}"
headers = {
'x-client-key': "<your x-client-key here>",
'Content-Type': "application/json",
'cache-control': "no-cache",
}
conn.request("POST", "v1,project,:projectId,feedline", payload, headers)
res = conn.getresponse()
data = res.read()
print(data.decode("utf-8"))var request = require("request");
var options = { method: 'POST',
url: 'https://api.playment.in/v1/project/:projectId/feedline',
headers:
{ 'cache-control': 'no-cache',
'Content-Type': 'application/json',
'x-client-key': '<your x-client-key here>' },
body:
{ reference_id: '001',
data:
{ image_url: 'https://dummyimage.com/600x400/000/fff.jpg&text=Dummy+Image+1',
boxes:
[ { id: 'box_0001',
label: 'car',
coordinates:
[ { x: 0.38, y: 0.19 },
{ x: 0.57, y: 0.19 },
{ x: 0.57, y: 0.44 },
{ x: 0.38, y: 0.44 } ] },
{ id: 'box_0002',
label: 'van',
coordinates:
[ { x: 0.38, y: 0.19 },
{ x: 0.57, y: 0.19 },
{ x: 0.57, y: 0.44 },
{ x: 0.38, y: 0.44 } ] } ] },
tag: 'validate_boxes' },
json: true };
request(options, function (error, response, body) {
if (error) throw new Error(error);
console.log(body);
});
{
"feed_line_units": [
{
"reference_id": "001",
"flu_id": "33abc3fe-9fbc-4d7c-b951-a1d1bfb6f840",
"status": "COMPLETED",
"tag": "validate_boxes",
"result": [
{
"id": "box_0001",
"label": {
"judgement": "valid",
"value": "car"
},
"coordinates": {
"judgement": "invalid",
"value": [
{"x": 0.38, "y": 0.19},
{"x": 0.57, "y": 0.19},
{"x": 0.57, "y": 0.44},
{"x": 0.38, "y": 0.44}]
}
},
{
"id": "box_0002",
"label": {
"judgement": "invalid",
"value": "truck"
},
"coordinates": {
"judgement": "valid",
"value": [
{"x": 0.38, "y": 0.19},
{"x": 0.57, "y": 0.19},
{"x": 0.57, "y": 0.44},
{"x": 0.38, "y": 0.44}]
}
}
]
]
}
}Annotation Attributes
In addition to the basic shape annotations, we provide labelling of any attributes associated with the parent annotations
Check the feed_line_units[0].result.rectangles[0].attributes key in the callback body shown on the right
{
"feed_line_units": [{
"reference_id": "001",
"flu_id": "33abc3fe-9fbc-4d7c-b951-a1d1bfb6f840",
"status": "COMPLETED",
"tag": "draw_bounding_boxes",
"result": {
"rectangles": [
{
"label": "television",
"coordinates": [
{"x": 0.38, "y": 0.19},
{"x": 0.57, "y": 0.19},
{"x": 0.57, "y": 0.44},
{"x": 0.38, "y": 0.44}],
"attributes": {
"occlusion": 0,
"leading_vehicle": True
}
},
{
"label": "plant",
"coordinates": [
{"x": 0.38, "y": 0.19},
{"x": 0.57, "y": 0.19},
{"x": 0.57, "y": 0.44},
{"x": 0.38, "y": 0.44}],
"attributes": {
"occlusion": 1,
"leading_vehicle": False
}
}
]
}
}]
}
What we send
You will be required to configure a callback_url, where we will POST the results of your request once it is completed.
POST https://<some_custom_callback_url>
We send the response as a JSON body, which looks like this:
The result object is a JSON which can contain one or more key-value pairs, depending on your requirements. Check the examples to understand how it can be used in various scenarios.
In case the images shared in the Feedline API are invalid or unavailable, we will retry multiple times before responding asynchronously to the Callback API with "status": "FAILED"
reference_id
reference_id is a unique identifier for a request. We'll fail a request if you've sent another request with the same reference_id previously. This helps us ensure that we don't charge you for work which we've already done for you.
flu_id
This is the unique ID that we generate for every request
status
PENDING : The data is currently being processedCOMPLETED : All the data has been processed and is ready for consumption by clientFAILED : Data validation or file download failed
As of today, you will not receive a response which has a `FAILED' status
tag
Each request should have a tag which tells us what operation needs to be performed on that request. Don't worry, We'll share this tag with you during the integration process.
{
"feed_line_units": [{
"reference_id": "001",
"flu_id": "33abc3fe-9fbc-4d7c-b951-a1d1bfb6f840",
"status": "COMPLETED",
"tag": "cat_or_dog",
"result": {
"category" : "cat"
}]
}{
"feed_line_units": [
{
"reference_id": "001",
"flu_id": "33abc3fe-9fbc-4d7c-b951-a1d1bfb6f840",
"status": "FAILED",
"tag": "cat_or_dog",
"error": {
"code": "FS_0003",
"message": "Invalid data passed",
"meta_data": {
"failures": [
{
"field": "product_image_url",
"type": "INVALID_IMAGE_LINK"
},
{
"field": "review_image_url",
"type": "INVALID_IMAGE_LINK"
}
]
}
}
}
]
}Error codes
On a callback request, you should respond with 200 HttpStatusCode to be considered as a successful request. Any non-200 HttpStatusCode will be considered as unsuccessful. In case of following non-200 HttpStatusCodes, we retry upto 3 times in an interval of 30 seconds:
Error Code
Description
408
Request Timeout
500
Internal Server Error
501
Not Implemented
502
Bad Gateway
503
Service Unavailable
504
Gateway Timeout
505
HTTP Version Not Supported
511
Network Authentication Required
Getting Started
This page will help you get started with Create Flu.
This is where you show your users how to set it up. You can use code samples, like this:
$http.post('/someUrl', data).success(successCallback);
alert('test');Try dragging a block from the right to see how easy it is to add more content!