Portal
Face API
The Webit Face REST API lets you effortlessly search between millons of YouTube, Dailymotion and Vimeo videos with a single solution.
Introduction
The Webit Face API lets you effortlessly search between millons of YouTube, Dailymotion and Vimeo videos with a single solution. And it includes a FREE plan to get started with.
API testing and usage
If you want to start using the Face service or just want to test it a little, just press the buttons below.
You will need a RapidAPI account for testing production endpoints. However, the whole process is completely FREE of charge and no credit card is required.
Below is an example of a not-easy-to-detect nudity. Neural Machine performs very well and understands the image contains nudity, despite of the confusing perspective.
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{
    "status": "success",
    "data": {
        "input_source": "url",
        "faces": [
            {
                "face_id": 4,
                "confidence": 0.9999003410339355,
                "bounding_box": {
                    "start": {
                        "x": 78.89374090247453,
                        "y": 52.252252252252255
                    },
                    "end": {
                        "x": 88.20960698689956,
                        "y": 59.7972972972973
                    },
                    "relative": {
                        "start": {
                            "x": 78.89374090247453,
                            "y": 52.252252252252255
                        },
                        "end": {
                            "x": 88.20960698689956,
                            "y": 59.7972972972973
                        }
                    },
                    "absolute": {
                        "start": {
                            "x": 542,
                            "y": 464
                        },
                        "end": {
                            "x": 606,
                            "y": 531
                        }
                    }
                },
                "size": {
                    "width": 64,
                    "height": 67
                },
                "coverage": 0.703
            },
            {
                "face_id": 2,
                "confidence": 0.9999812841415405,
                "bounding_box": {
                    "start": {
                        "x": 62.15429403202329,
                        "y": 50.56306306306306
                    },
                    "end": {
                        "x": 70.59679767103349,
                        "y": 57.88288288288288
                    },
                    "relative": {
                        "start": {
                            "x": 62.15429403202329,
                            "y": 50.56306306306306
                        },
                        "end": {
                            "x": 70.59679767103349,
                            "y": 57.88288288288288
                        }
                    },
                    "absolute": {
                        "start": {
                            "x": 427,
                            "y": 449
                        },
                        "end": {
                            "x": 485,
                            "y": 514
                        }
                    }
                },
                "size": {
                    "width": 58,
                    "height": 65
                },
                "coverage": 0.618
            },
            {
                "face_id": 1,
                "confidence": 0.999987006187439,
                "bounding_box": {
                    "start": {
                        "x": 26.637554585152838,
                        "y": 52.7027027027027
                    },
                    "end": {
                        "x": 35.22561863173217,
                        "y": 59.7972972972973
                    },
                    "relative": {
                        "start": {
                            "x": 26.637554585152838,
                            "y": 52.7027027027027
                        },
                        "end": {
                            "x": 35.22561863173217,
                            "y": 59.7972972972973
                        }
                    },
                    "absolute": {
                        "start": {
                            "x": 183,
                            "y": 468
                        },
                        "end": {
                            "x": 242,
                            "y": 531
                        }
                    }
                },
                "size": {
                    "width": 59,
                    "height": 63
                },
                "coverage": 0.609
            },
            {
                "face_id": 5,
                "confidence": 0.9992808699607849,
                "bounding_box": {
                    "start": {
                        "x": 46.57933042212518,
                        "y": 54.054054054054056
                    },
                    "end": {
                        "x": 55.31295487627365,
                        "y": 60.92342342342342
                    },
                    "relative": {
                        "start": {
                            "x": 46.57933042212518,
                            "y": 54.054054054054056
                        },
                        "end": {
                            "x": 55.31295487627365,
                            "y": 60.92342342342342
                        }
                    },
                    "absolute": {
                        "start": {
                            "x": 320,
                            "y": 480
                        },
                        "end": {
                            "x": 380,
                            "y": 541
                        }
                    }
                },
                "size": {
                    "width": 60,
                    "height": 61
                },
                "coverage": 0.6
            },
            {
                "face_id": 3,
                "confidence": 0.9999605417251587,
                "bounding_box": {
                    "start": {
                        "x": 11.644832605531295,
                        "y": 51.23873873873874
                    },
                    "end": {
                        "x": 19.50509461426492,
                        "y": 58.671171171171174
                    },
                    "relative": {
                        "start": {
                            "x": 11.644832605531295,
                            "y": 51.23873873873874
                        },
                        "end": {
                            "x": 19.50509461426492,
                            "y": 58.671171171171174
                        }
                    },
                    "absolute": {
                        "start": {
                            "x": 80,
                            "y": 455
                        },
                        "end": {
                            "x": 134,
                            "y": 521
                        }
                    }
                },
                "size": {
                    "width": 54,
                    "height": 66
                },
                "coverage": 0.584
            }
        ],
        "faces_count": 5
    },
    "message": null
}
Here is an example of a black and white image containing nudity. Neural Machine understands what's depicted in the image despite of skin tone colors.
Face 1
{
    "status": "success",
    "data": {
        "input_source": "url",
        "faces": [
            {
                "face_id": 1,
                "confidence": 0.9992408752441406,
                "bounding_box": {
                    "start": {
                        "x": 31,
                        "y": 18.97142857142857
                    },
                    "end": {
                        "x": 81.71428571428571,
                        "y": 67.88571428571429
                    },
                    "relative": {
                        "start": {
                            "x": 31,
                            "y": 18.97142857142857
                        },
                        "end": {
                            "x": 81.71428571428571,
                            "y": 67.88571428571429
                        }
                    },
                    "absolute": {
                        "start": {
                            "x": 217,
                            "y": 166
                        },
                        "end": {
                            "x": 572,
                            "y": 594
                        }
                    }
                },
                "size": {
                    "width": 355,
                    "height": 428
                },
                "coverage": 24.807
            }
        ],
        "faces_count": 1
    },
    "message": null
}
Here is an example of a black and white image containing nudity. Neural Machine understands what's depicted in the image despite of skin tone colors.
Face 1
Face 2
{
    "status": "success",
    "data": {
        "input_source": "url",
        "faces": [
            {
                "face_id": 2,
                "confidence": 0.993431031703949,
                "bounding_box": {
                    "start": {
                        "x": 50.285714285714285,
                        "y": 14.714285714285714
                    },
                    "end": {
                        "x": 71.71428571428571,
                        "y": 47.714285714285715
                    },
                    "relative": {
                        "start": {
                            "x": 50.285714285714285,
                            "y": 14.714285714285714
                        },
                        "end": {
                            "x": 71.71428571428571,
                            "y": 47.714285714285715
                        }
                    },
                    "absolute": {
                        "start": {
                            "x": 528,
                            "y": 103
                        },
                        "end": {
                            "x": 753,
                            "y": 334
                        }
                    }
                },
                "size": {
                    "width": 225,
                    "height": 231
                },
                "coverage": 7.071
            },
            {
                "face_id": 1,
                "confidence": 0.9998107552528381,
                "bounding_box": {
                    "start": {
                        "x": 36,
                        "y": 19.857142857142858
                    },
                    "end": {
                        "x": 55.714285714285715,
                        "y": 55.285714285714285
                    },
                    "relative": {
                        "start": {
                            "x": 36,
                            "y": 19.857142857142858
                        },
                        "end": {
                            "x": 55.714285714285715,
                            "y": 55.285714285714285
                        }
                    },
                    "absolute": {
                        "start": {
                            "x": 378,
                            "y": 139
                        },
                        "end": {
                            "x": 585,
                            "y": 387
                        }
                    }
                },
                "size": {
                    "width": 207,
                    "height": 248
                },
                "coverage": 6.984
            }
        ],
        "faces_count": 2
    },
    "message": null
}
Here is an example of a black and white image containing nudity. Neural Machine understands what's depicted in the image despite of skin tone colors.
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{
    "status": "success",
    "data": {
        "input_source": "url",
        "faces": [
            {
                "face_id": 5,
                "confidence": 0.9930843114852905,
                "bounding_box": {
                    "start": {
                        "x": 82.57142857142857,
                        "y": 0
                    },
                    "end": {
                        "x": 92,
                        "y": 7.857142857142857
                    },
                    "relative": {
                        "start": {
                            "x": 82.57142857142857,
                            "y": 0
                        },
                        "end": {
                            "x": 92,
                            "y": 7.857142857142857
                        }
                    },
                    "absolute": {
                        "start": {
                            "x": 867,
                            "y": 0
                        },
                        "end": {
                            "x": 966,
                            "y": 55
                        }
                    }
                },
                "size": {
                    "width": 99,
                    "height": 55
                },
                "coverage": 0.741
            },
            {
                "face_id": 3,
                "confidence": 0.9993745684623718,
                "bounding_box": {
                    "start": {
                        "x": 27.333333333333332,
                        "y": 15.857142857142858
                    },
                    "end": {
                        "x": 33.04761904761905,
                        "y": 26
                    },
                    "relative": {
                        "start": {
                            "x": 27.333333333333332,
                            "y": 15.857142857142858
                        },
                        "end": {
                            "x": 33.04761904761905,
                            "y": 26
                        }
                    },
                    "absolute": {
                        "start": {
                            "x": 287,
                            "y": 111
                        },
                        "end": {
                            "x": 347,
                            "y": 182
                        }
                    }
                },
                "size": {
                    "width": 60,
                    "height": 71
                },
                "coverage": 0.58
            },
            {
                "face_id": 1,
                "confidence": 0.9999312162399292,
                "bounding_box": {
                    "start": {
                        "x": 9.333333333333334,
                        "y": 19.142857142857142
                    },
                    "end": {
                        "x": 14.19047619047619,
                        "y": 27.285714285714285
                    },
                    "relative": {
                        "start": {
                            "x": 9.333333333333334,
                            "y": 19.142857142857142
                        },
                        "end": {
                            "x": 14.19047619047619,
                            "y": 27.285714285714285
                        }
                    },
                    "absolute": {
                        "start": {
                            "x": 98,
                            "y": 134
                        },
                        "end": {
                            "x": 149,
                            "y": 191
                        }
                    }
                },
                "size": {
                    "width": 51,
                    "height": 57
                },
                "coverage": 0.396
            },
            {
                "face_id": 4,
                "confidence": 0.9988856911659241,
                "bounding_box": {
                    "start": {
                        "x": 43.904761904761905,
                        "y": 12.571428571428571
                    },
                    "end": {
                        "x": 48.666666666666664,
                        "y": 19.142857142857142
                    },
                    "relative": {
                        "start": {
                            "x": 43.904761904761905,
                            "y": 12.571428571428571
                        },
                        "end": {
                            "x": 48.666666666666664,
                            "y": 19.142857142857142
                        }
                    },
                    "absolute": {
                        "start": {
                            "x": 461,
                            "y": 88
                        },
                        "end": {
                            "x": 511,
                            "y": 134
                        }
                    }
                },
                "size": {
                    "width": 50,
                    "height": 46
                },
                "coverage": 0.313
            }
        ],
        "faces_count": 4
    },
    "message": null
}
Here is an example of a black and white image containing nudity. Neural Machine understands what's depicted in the image despite of skin tone colors.
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