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The Webit FaceNet REST API lets you effortlessly search between millons of YouTube, Dailymotion and Vimeo videos with a single solution.
Introduction
The Webit FaceNet 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 FaceNet 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": 2,
                "confidence": 0.9999761581420898,
                "bounding_box": {
                    "start": {
                        "x": 78.4570596797671,
                        "y": 52.13963963963964
                    },
                    "end": {
                        "x": 88.20960698689956,
                        "y": 59.909909909909906
                    },
                    "relative": {
                        "start": {
                            "x": 78.4570596797671,
                            "y": 52.13963963963964
                        },
                        "end": {
                            "x": 88.20960698689956,
                            "y": 59.909909909909906
                        }
                    },
                    "absolute": {
                        "start": {
                            "x": 539,
                            "y": 463
                        },
                        "end": {
                            "x": 606,
                            "y": 532
                        }
                    }
                },
                "size": {
                    "width": 67,
                    "height": 69
                },
                "coverage": 0.758
            },
            {
                "face_id": 1,
                "confidence": 0.9999819993972778,
                "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": 5,
                "confidence": 0.9992369413375854,
                "bounding_box": {
                    "start": {
                        "x": 46.57933042212518,
                        "y": 54.054054054054056
                    },
                    "end": {
                        "x": 55.31295487627365,
                        "y": 61.03603603603604
                    },
                    "relative": {
                        "start": {
                            "x": 46.57933042212518,
                            "y": 54.054054054054056
                        },
                        "end": {
                            "x": 55.31295487627365,
                            "y": 61.03603603603604
                        }
                    },
                    "absolute": {
                        "start": {
                            "x": 320,
                            "y": 480
                        },
                        "end": {
                            "x": 380,
                            "y": 542
                        }
                    }
                },
                "size": {
                    "width": 60,
                    "height": 62
                },
                "coverage": 0.61
            },
            {
                "face_id": 3,
                "confidence": 0.9999562501907349,
                "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
            },
            {
                "face_id": 4,
                "confidence": 0.999932050704956,
                "bounding_box": {
                    "start": {
                        "x": 26.92867540029112,
                        "y": 52.7027027027027
                    },
                    "end": {
                        "x": 35.080058224163025,
                        "y": 59.7972972972973
                    },
                    "relative": {
                        "start": {
                            "x": 26.92867540029112,
                            "y": 52.7027027027027
                        },
                        "end": {
                            "x": 35.080058224163025,
                            "y": 59.7972972972973
                        }
                    },
                    "absolute": {
                        "start": {
                            "x": 185,
                            "y": 468
                        },
                        "end": {
                            "x": 241,
                            "y": 531
                        }
                    }
                },
                "size": {
                    "width": 56,
                    "height": 63
                },
                "coverage": 0.578
            }
        ],
        "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": 0.999204695224762,
                "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": 0.9937923550605774,
                "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": 0.9998096823692322,
                "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": 0.9926742911338806,
                "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": 2,
                "confidence": 0.999859094619751,
                "bounding_box": {
                    "start": {
                        "x": 27.428571428571427,
                        "y": 15.857142857142858
                    },
                    "end": {
                        "x": 33.23809523809524,
                        "y": 25.714285714285715
                    },
                    "relative": {
                        "start": {
                            "x": 27.428571428571427,
                            "y": 15.857142857142858
                        },
                        "end": {
                            "x": 33.23809523809524,
                            "y": 25.714285714285715
                        }
                    },
                    "absolute": {
                        "start": {
                            "x": 288,
                            "y": 111
                        },
                        "end": {
                            "x": 349,
                            "y": 180
                        }
                    }
                },
                "size": {
                    "width": 61,
                    "height": 69
                },
                "coverage": 0.573
            },
            {
                "face_id": 1,
                "confidence": 0.999992847442627,
                "bounding_box": {
                    "start": {
                        "x": 9.523809523809524,
                        "y": 19.142857142857142
                    },
                    "end": {
                        "x": 14.285714285714286,
                        "y": 26.857142857142858
                    },
                    "relative": {
                        "start": {
                            "x": 9.523809523809524,
                            "y": 19.142857142857142
                        },
                        "end": {
                            "x": 14.285714285714286,
                            "y": 26.857142857142858
                        }
                    },
                    "absolute": {
                        "start": {
                            "x": 100,
                            "y": 134
                        },
                        "end": {
                            "x": 150,
                            "y": 188
                        }
                    }
                },
                "size": {
                    "width": 50,
                    "height": 54
                },
                "coverage": 0.367
            },
            {
                "face_id": 4,
                "confidence": 0.9987057447433472,
                "bounding_box": {
                    "start": {
                        "x": 59.904761904761905,
                        "y": 26.428571428571427
                    },
                    "end": {
                        "x": 64.66666666666667,
                        "y": 33
                    },
                    "relative": {
                        "start": {
                            "x": 59.904761904761905,
                            "y": 26.428571428571427
                        },
                        "end": {
                            "x": 64.66666666666667,
                            "y": 33
                        }
                    },
                    "absolute": {
                        "start": {
                            "x": 629,
                            "y": 185
                        },
                        "end": {
                            "x": 679,
                            "y": 231
                        }
                    }
                },
                "size": {
                    "width": 50,
                    "height": 46
                },
                "coverage": 0.313
            },
            {
                "face_id": 3,
                "confidence": 0.9990041851997375,
                "bounding_box": {
                    "start": {
                        "x": 44,
                        "y": 12.571428571428571
                    },
                    "end": {
                        "x": 48.666666666666664,
                        "y": 19.142857142857142
                    },
                    "relative": {
                        "start": {
                            "x": 44,
                            "y": 12.571428571428571
                        },
                        "end": {
                            "x": 48.666666666666664,
                            "y": 19.142857142857142
                        }
                    },
                    "absolute": {
                        "start": {
                            "x": 462,
                            "y": 88
                        },
                        "end": {
                            "x": 511,
                            "y": 134
                        }
                    }
                },
                "size": {
                    "width": 49,
                    "height": 46
                },
                "coverage": 0.307
            }
        ],
        "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.
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