human/dist/human.ts.map

{
  "version": 3,
  "sources": ["../src/blazeface/facemesh.ts", "../src/posenet/keypoints.ts", "../src/human.ts", "../src/log.ts", "../src/sysinfo.ts", "../node_modules/node-fetch/browser.js", "../node_modules/@tensorflow/tfjs-core/node_modules/seedrandom/lib/alea.js", "../node_modules/@tensorflow/tfjs-core/node_modules/seedrandom/lib/xor128.js", "../node_modules/@tensorflow/tfjs-core/node_modules/seedrandom/lib/xorwow.js", "../node_modules/@tensorflow/tfjs-core/node_modules/seedrandom/lib/xorshift7.js", "../node_modules/@tensorflow/tfjs-core/node_modules/seedrandom/lib/xor4096.js", "../node_modules/@tensorflow/tfjs-core/node_modules/seedrandom/lib/tychei.js", "(disabled):crypto", "../node_modules/@tensorflow/tfjs-core/node_modules/seedrandom/seedrandom.js", "../node_modules/@tensorflow/tfjs-core/node_modules/seedrandom/index.js", "../node_modules/@tensorflow/tfjs-backend-cpu/node_modules/seedrandom/lib/alea.js", "../node_modules/@tensorflow/tfjs-backend-cpu/node_modules/seedrandom/lib/xor128.js", "../node_modules/@tensorflow/tfjs-backend-cpu/node_modules/seedrandom/lib/xorwow.js", "../node_modules/@tensorflow/tfjs-backend-cpu/node_modules/seedrandom/lib/xorshift7.js", "../node_modules/@tensorflow/tfjs-backend-cpu/node_modules/seedrandom/lib/xor4096.js", "../node_modules/@tensorflow/tfjs-backend-cpu/node_modules/seedrandom/lib/tychei.js", "../node_modules/@tensorflow/tfjs-backend-cpu/node_modules/seedrandom/seedrandom.js", "../node_modules/@tensorflow/tfjs-backend-cpu/node_modules/seedrandom/index.js", "(disabled):path", "(disabled):worker_threads", "(disabled):perf_hooks", "../node_modules/@tensorflow/tfjs-backend-wasm/wasm-out/tfjs-backend-wasm-threaded-simd.js", "../node_modules/@tensorflow/tfjs-backend-wasm/wasm-out/tfjs-backend-wasm.js", "../node_modules/seedrandom/lib/alea.js", "../node_modules/seedrandom/lib/xor128.js", "../node_modules/seedrandom/lib/xorwow.js", "../node_modules/seedrandom/lib/xorshift7.js", "../node_modules/seedrandom/lib/xor4096.js", "../node_modules/seedrandom/lib/tychei.js", "../node_modules/seedrandom/seedrandom.js", "../node_modules/seedrandom/index.js", "../node_modules/string_decoder/lib/string_decoder.js", "../node_modules/@tensorflow/tfjs-core/src/backends/backend.ts", "../node_modules/@tensorflow/tfjs-core/src/util_base.ts", "../node_modules/@tensorflow/tfjs-core/src/environment.ts", "../node_modules/@tensorflow/tfjs-core/src/global_util.ts", "../node_modules/@tensorflow/tfjs-core/src/kernel_names.ts", "../node_modules/@tensorflow/tfjs-core/src/kernel_registry.ts", "../node_modules/@tensorflow/tfjs-core/src/util.ts", "../node_modules/@tensorflow/tfjs-core/src/profiler.ts", "../node_modules/@tensorflow/tfjs-core/src/tape.ts", "../node_modules/@tensorflow/tfjs-core/src/tensor_format.ts", "../node_modules/@tensorflow/tfjs-core/src/tensor.ts", "../node_modules/@tensorflow/tfjs-core/src/tensor_util.ts", "../node_modules/@tensorflow/tfjs-core/src/types.ts", "../node_modules/@tensorflow/tfjs-core/src/engine.ts", "../node_modules/@tensorflow/tfjs-core/src/device_util.ts", "../node_modules/@tensorflow/tfjs-core/src/flags.ts", "../node_modules/@tensorflow/tfjs-core/src/tensor_util_env.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/operation.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/complex.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/tensor_ops_util.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/tensor.ts", "../node_modules/@tensorflow/tfjs-core/src/io/types.ts", "../node_modules/@tensorflow/tfjs-core/src/io/io_utils.ts", "../node_modules/@tensorflow/tfjs-core/src/io/router_registry.ts", "../node_modules/@tensorflow/tfjs-core/src/io/indexed_db.ts", "../node_modules/@tensorflow/tfjs-core/src/io/local_storage.ts", "../node_modules/@tensorflow/tfjs-core/src/io/model_management.ts", "../node_modules/@tensorflow/tfjs-core/src/platforms/platform_browser.ts", "../node_modules/@tensorflow/tfjs-core/src/platforms/platform_node.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/buffer.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/cast.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/cl
  "sourcesContent": ["import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as blazeface from './blazeface';\nimport * as facepipeline from './facepipeline';\nimport * as coords from './coords';\n\nexport class MediaPipeFaceMesh {\n  facePipeline: any;\n  config: any;\n\n  constructor(blazeFace, blazeMeshModel, irisModel, config) {\n    this.facePipeline = new facepipeline.Pipeline(blazeFace, blazeMeshModel, irisModel, config);\n    this.config = config;\n  }\n\n  async estimateFaces(input, config) {\n    const predictions = await this.facePipeline.predict(input, config);\n    const results: Array<{}> = [];\n    for (const prediction of (predictions || [])) {\n      if (prediction.isDisposedInternal) continue; // guard against disposed tensors on long running operations such as pause in middle of processing\n      const mesh = prediction.coords ? prediction.coords.arraySync() : null;\n      const meshRaw = prediction.rawCoords;\n      const annotations = {};\n      if (mesh && mesh.length > 0) {\n        for (const key of Object.keys(coords.MESH_ANNOTATIONS)) annotations[key] = coords.MESH_ANNOTATIONS[key].map((index) => mesh[index]);\n      }\n      const boxRaw = (prediction.box) ? { topLeft: prediction.box.startPoint, bottomRight: prediction.box.endPoint } : null;\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.startPoint[0]),\n        Math.max(0, prediction.box.startPoint[1]),\n        Math.min(input.shape[2], prediction.box.endPoint[0]) - prediction.box.startPoint[0],\n        Math.min(input.shape[1], prediction.box.endPoint[1]) - prediction.box.startPoint[1],\n      ] : 0;\n      results.push({\n        confidence: prediction.faceConfidence || prediction.boxConfidence || 0,\n        boxConfidence: prediction.boxConfidence,\n        faceConfidence: prediction.faceConfidence,\n        box,\n        mesh,\n        boxRaw,\n        meshRaw,\n        annotations,\n        image: prediction.image ? tf.clone(prediction.image) : null,\n      });\n      if (prediction.coords) prediction.coords.dispose();\n      if (prediction.image) prediction.image.dispose();\n    }\n    return results;\n  }\n}\n\nlet faceModels = [null, null, null];\nexport async function load(config) {\n  // @ts-ignore\n  faceModels = await Promise.all([\n    (!faceModels[0] && config.face.enabled) ? blazeface.load(config) : null,\n    (!faceModels[1] && config.face.mesh.enabled) ? tf.loadGraphModel(config.face.mesh.modelPath, { fromTFHub: config.face.mesh.modelPath.includes('tfhub.dev') }) : null,\n    (!faceModels[2] && config.face.iris.enabled) ? tf.loadGraphModel(config.face.iris.modelPath, { fromTFHub: config.face.iris.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const faceMesh = new MediaPipeFaceMesh(faceModels[0], faceModels[1], faceModels[2], config);\n  if (config.face.mesh.enabled && config.debug) log(`load model: ${config.face.mesh.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.face.iris.enabled && config.debug) log(`load model: ${config.face.iris.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return faceMesh;\n}\n\nexports.triangulation = coords.TRI468;\n", "export const partNames = [\n  'nose', 'leftEye', 'rightEye', 'leftEar', 'rightEar', 'leftShoulder',\n  'rightShoulder', 'leftElbow', 'rightElbow', 'leftWrist', 'rightWrist',\n  'leftHip', 'rightHip', 'leftKnee', 'rightKnee', 'leftAnkle', 'rightAnkle',\n];\n\nexport const NUM_KEYPOINTS = exports.partNames.length; // 17 keypoints\n\nexport const partIds = exports.partNames.reduce((result, jointName, i) => {\n  result[jointName] = i;\n  return result;\n}, {});\n\nconst connectedPartNames = [\n  ['leftHip', 'leftShoulder'], ['leftElbow', 'leftShoulder'],\n  ['leftElbow', 'leftWrist'], ['leftHip', 'leftKnee'],\n  ['leftKnee', 'leftAnkle'], ['rightHip', 'rightShoulder'],\n  ['rightElbow', 'rightShoulder'], ['rightElbow', 'rightWrist'],\n  ['rightHip', 'rightKnee'], ['rightKnee', 'rightAnkle'],\n  ['leftShoulder', 'rightShoulder'], ['leftHip', 'rightHip'],\n];\nexport const connectedPartIndices = connectedPartNames.map(([jointNameA
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