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NudeNet: NSFW Object Detection for TFJS and NodeJS

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NudeNet: NSFW Object Detection for TFJS and NodeJS

Notes

  • Model included in /model/ were converted to TFJS Graph model format from the original repository
    Model descriptors and signature have been additionally parsed for readability
  • Model itself uses dynamic input sizes
  • Parsing implementation in nudenet.js does not follow original
    and is implemented using native TFJS ops and optimized for JavaScript execution
  • Code also includes simple bluring function for exposed body parts in the input image
  • Example implementation is for NodeJS
    but can be used in Browser environments by changing tfjs dependencies and image loader function

Output

Structure of the return object:

{
  input: {
    file: String,
    width: Number,
    height: Number,
  },
  person: Boolean, // is person detected?
  sexy: Boolean, // is person considered sexy?
  nude: Boolean, // is person considered nude?
  parts: Array<{ // array of detected body parts
    score: Number, // confidence in detection
    id: Number,
    class: String, // label for body part
    box: Number[], // [x, y, width, height]
  }>,
}

Where class can be :

const labels = [ // class labels
  'exposed anus',
  'exposed armpits',
  'belly',
  'exposed belly',
  'buttocks',
  'exposed buttocks',
  'female face',
  'male face',
  'feet',
  'exposed feet',
  'breast',
  'exposed breast',
  'vagina',
  'exposed vagina',
  'male breast',
  'exposed male breast',
];

Example

Example Image


node nudenet.js samples/nude.jpg samples/nude-out.jpg

2021-10-20 11:11:11 INFO:  nudenet version 0.0.1
2021-10-20 11:11:11 INFO:  User: vlado Platform: linux Arch: x64 Node: v16.8.0
2021-10-20 11:11:11 INFO:  tfjs version: 3.9.0 backend: tensorflow
2021-10-20 11:11:11 INFO:  options: { debug: true, modelPath: 'file://model/model.json', minScore: 0.3, maxResults: 50, iouThreshold: 0.5, outputNodes: [ 'output1', 'output2', 'output3' ], blurNude: true, blurRadius: 25 }
2021-10-20 11:11:11 STATE: loaded graph model: file://model/model.json
2021-10-20 11:11:11 INFO:  loaded image: samples/nude.jpg width: 801 height: 1112
2021-10-20 11:11:13 DATA:  result: {
  input: { file: 'samples/nude.jpg', width: 801, height: 1112 },
  person: true,
  sexy: true,
  nude: true,
  parts: [
    { score: 0.8839950561523438, id: 3, class: 'exposed belly', box: [ 194, 639, 244, 221 ] },
    { score: 0.7332422137260437, id: 11, class: 'exposed breast', box: [ 371, 450, 142, 154 ] },
    { score: 0.566450834274292, id: 6, class: 'female face', box: [ 282, 164, 169, 155 ] },
    { score: 0.5646520256996155, id: 11, class: 'exposed breast', box: [ 202, 430, 134, 156 ] },
    { score: 0.5579367876052856, id: 12, class: 'vagina', box: [ 187, 908, 92, 96 ] }
  ]
}
2021-10-20 11:11:13 STATE: created output image: samples/nude-out.jpg
2021-10-20 11:11:13 STATE: done: model:file://model/model.json input:samples/nude.jpg output:samples/nude-out.jpg objects: 5

Conversion Notes

tensorflowjs_converter \
  --input_format tf_saved_model \
  --output_format tfjs_graph_model \
  --control_flow_v2=true --strip_debug_ops=true --signature_name=predict \
  --weight_shard_size_bytes=16777216 --quantize_float16=* \
  model/saved model/

Model Signature

2021-10-20 11:28:12 INFO:  graph model: /home/vlado/dev/nudenet/model/model.json
2021-10-20 11:28:12 INFO:  size: { numTensors: 843, numDataBuffers: 843, numBytes: 146462740 }
2021-10-20 11:28:12 DATA:  inputs: [
  { name: 'images', dtype: 'DT_FLOAT', shape: [ -1, -1, -1, 3 ] },
]
2021-10-20 11:28:13 DATA:  outputs: [
  { id: 0, name: 'output1', dytpe: 'DT_FLOAT', shape: [ -1, 300, 4 ] },
  { id: 1, name: 'output3', dytpe: 'DT_INT32', shape: [ -1, 300 ] },
  { id: 2, name: 'output2', dytpe: 'DT_FLOAT', shape: [ -1, 300 ] },
]

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