Apply effects to your photo. Select person on a photo, blur or grayscale background
| Parameter’s name | Parameter’s type | Description |
|---|---|---|
| raw_input | boolean | False - Use Tensorflow protobuf record format fot feeding data to model, True - Use numpy arrays. |
| out_mime_type | string | Optional. Used on a client side to identify content nature. |
| out_filters | string | Optional. Comma separated list of model outputs to return. |
| inputs | bytes | Input image |
| max_objects | int | Max number of objects to detect |
| object_class | string | Object to find |
| effect | string | Effect to apply |
| blur_radius | int | Radius for Blur |
curl -X POST \
-H 'Authorization: Bearer YOUR_USER_TOKEN' \
-H 'Content-Type: multipart/form-data' \
-F "out_filters=output" \
-F "raw_input=true" \
-F "out_mime_type=image/png" \
-F "bytes_inputs=@PATH_TO_INPUTS" \
-F "int_max_objects=max_objects_value" \
-F "string_object_class=object_class_value" \
-F "string_effect=effect_value" \
-F "int_blur_radius=blur_radius_value" \
https://cloud.kibernetika.io/api/v0.2/workspace/kuberlab-demo/serving/photo-robot/tfproxy/9000/any
curl -X POST \
-H 'Authorization: Bearer YOUR_USER_TOKEN' \
-H 'Content-Type: application/json' \
-d '
{
"inputs": {
"blur_radius": {
"data": 86,
"dtype": 9
},
"effect": {
"data": "base64_encoded_effect_value",
"dtype": 7
},
"inputs": {
"data": "base64_encoded_inputs_contents",
"dtype": 7
},
"max_objects": {
"data": 39,
"dtype": 9
},
"object_class": {
"data": "base64_encoded_object_class_value",
"dtype": 7
}
},
"out_filters": "output",
"out_mime_type": "image/png",
"raw_input": true
}
'
https://cloud.kibernetika.io/api/v0.2/workspace/kuberlab-demo/serving/photo-robot/tfproxy/9000/any
{
"output": [
[
"bytes"
]
]
}