| <!DOCTYPE html><html lang="en"><head><meta charset="utf-8"><meta name="viewport" content="width=device-width, initial-scale=1.0"><meta name="generator" content="rustdoc"><meta name="description" content="Source of the Rust file `/root/.cargo/git/checkouts/incubator-teaclave-crates-c8106113f74feefc/ede1f68/rustface/src/model/mod.rs`."><meta name="keywords" content="rust, rustlang, rust-lang"><title>mod.rs - source</title><link rel="preload" as="font" type="font/woff2" crossorigin href="../../../SourceSerif4-Regular.ttf.woff2"><link rel="preload" as="font" type="font/woff2" crossorigin href="../../../FiraSans-Regular.woff2"><link rel="preload" as="font" type="font/woff2" crossorigin href="../../../FiraSans-Medium.woff2"><link rel="preload" as="font" type="font/woff2" crossorigin href="../../../SourceCodePro-Regular.ttf.woff2"><link rel="preload" as="font" type="font/woff2" crossorigin href="../../../SourceSerif4-Bold.ttf.woff2"><link rel="preload" as="font" type="font/woff2" crossorigin href="../../../SourceCodePro-Semibold.ttf.woff2"><link rel="stylesheet" href="../../../normalize.css"><link rel="stylesheet" href="../../../rustdoc.css" id="mainThemeStyle"><link rel="stylesheet" href="../../../ayu.css" disabled><link rel="stylesheet" href="../../../dark.css" disabled><link rel="stylesheet" href="../../../light.css" id="themeStyle"><script id="default-settings" ></script><script src="../../../storage.js"></script><script defer src="../../../source-script.js"></script><script defer src="../../../source-files.js"></script><script defer src="../../../main.js"></script><noscript><link rel="stylesheet" href="../../../noscript.css"></noscript><link rel="alternate icon" type="image/png" href="../../../favicon-16x16.png"><link rel="alternate icon" type="image/png" href="../../../favicon-32x32.png"><link rel="icon" type="image/svg+xml" href="../../../favicon.svg"></head><body class="rustdoc source"><!--[if lte IE 11]><div class="warning">This old browser is unsupported and will most likely display funky things.</div><![endif]--><nav class="sidebar"><a class="sidebar-logo" href="../../../rustface/index.html"><div class="logo-container"><img class="rust-logo" src="../../../rust-logo.svg" alt="logo"></div></a></nav><main><div class="width-limiter"><nav class="sub"><a class="sub-logo-container" href="../../../rustface/index.html"><img class="rust-logo" src="../../../rust-logo.svg" alt="logo"></a><form class="search-form"><div class="search-container"><span></span><input class="search-input" name="search" autocomplete="off" spellcheck="false" placeholder="Click or press ‘S’ to search, ‘?’ for more options…" type="search"><div id="help-button" title="help" tabindex="-1"><a href="../../../help.html">?</a></div><div id="settings-menu" tabindex="-1"><a href="../../../settings.html" title="settings"><img width="22" height="22" alt="Change settings" src="../../../wheel.svg"></a></div></div></form></nav><section id="main-content" class="content"><div class="example-wrap"><pre class="src-line-numbers"><span id="1">1</span> |
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| </pre><pre class="rust"><code><span class="comment">// This file is part of the open-source port of SeetaFace engine, which originally includes three modules: |
| // SeetaFace Detection, SeetaFace Alignment, and SeetaFace Identification. |
| // |
| // This file is part of the SeetaFace Detection module, containing codes implementing the face detection method described in the following paper: |
| // |
| // Funnel-structured cascade for multi-view face detection with alignment awareness, |
| // Shuzhe Wu, Meina Kan, Zhenliang He, Shiguang Shan, Xilin Chen. |
| // In Neurocomputing (under review) |
| // |
| // Copyright (C) 2016, Visual Information Processing and Learning (VIPL) group, |
| // Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China. |
| // |
| // As an open-source face recognition engine: you can redistribute SeetaFace source codes |
| // and/or modify it under the terms of the BSD 2-Clause License. |
| // |
| // You should have received a copy of the BSD 2-Clause License along with the software. |
| // If not, see < https://opensource.org/licenses/BSD-2-Clause>. |
| |
| </span><span class="kw">use </span>std::io; |
| |
| <span class="kw">use </span><span class="kw">crate</span>::classifier::{Classifier, ClassifierKind, LabBoostedClassifier, SurfMlpClassifier}; |
| <span class="kw">use </span>byteorder::{LittleEndian, ReadBytesExt}; |
| |
| <span class="attribute">#[derive(Clone)] |
| </span><span class="kw">pub struct </span>Model { |
| classifiers: Vec<Classifier>, |
| wnd_src_id: Vec<Vec<i32>>, |
| hierarchy_sizes: Vec<i32>, |
| num_stages: Vec<i32>, |
| } |
| |
| <span class="kw">impl </span>Model { |
| <span class="attribute">#[inline] |
| </span><span class="kw">pub fn </span>get_classifiers(<span class="kw-2">&</span><span class="self">self</span>) -> <span class="kw-2">&</span>[Classifier] { |
| <span class="kw-2">&</span><span class="self">self</span>.classifiers |
| } |
| |
| <span class="attribute">#[inline] |
| </span><span class="kw">pub fn </span>get_wnd_src(<span class="kw-2">&</span><span class="self">self</span>, id: usize) -> <span class="kw-2">&</span>Vec<i32> { |
| <span class="kw-2">&</span><span class="self">self</span>.wnd_src_id[id] |
| } |
| |
| <span class="attribute">#[inline] |
| </span><span class="kw">pub fn </span>get_hierarchy_count(<span class="kw-2">&</span><span class="self">self</span>) -> usize { |
| <span class="self">self</span>.hierarchy_sizes.len() |
| } |
| |
| <span class="attribute">#[inline] |
| </span><span class="kw">pub fn </span>get_num_stage(<span class="kw-2">&</span><span class="self">self</span>, id: usize) -> i32 { |
| <span class="self">self</span>.num_stages[id] |
| } |
| |
| <span class="attribute">#[inline] |
| </span><span class="kw">pub fn </span>get_hierarchy_size(<span class="kw-2">&</span><span class="self">self</span>, hierarchy_index: usize) -> i32 { |
| <span class="self">self</span>.hierarchy_sizes[hierarchy_index] |
| } |
| } |
| |
| <span class="doccomment">/// Load model from any stream or buffer |
| </span><span class="attribute">#[inline] |
| </span><span class="kw">pub fn </span>read_model<R: io::Read>(buf: R) -> <span class="prelude-ty">Result</span><Model, io::Error> { |
| ModelReader::new(buf).read() |
| } |
| |
| <span class="kw">struct </span>ModelReader<R: io::Read> { |
| reader: R, |
| } |
| |
| <span class="kw">impl</span><R: io::Read> ModelReader<R> { |
| <span class="attribute">#[inline] |
| </span><span class="kw">fn </span>new(reader: R) -> <span class="self">Self </span>{ |
| ModelReader { reader } |
| } |
| |
| <span class="kw">pub fn </span>read(<span class="kw-2">mut </span><span class="self">self</span>) -> <span class="prelude-ty">Result</span><Model, io::Error> { |
| <span class="kw">let </span>num_hierarchy = <span class="self">self</span>.read_i32()<span class="question-mark">? </span><span class="kw">as </span>usize; |
| <span class="kw">let </span><span class="kw-2">mut </span>classifiers = Vec::new(); |
| <span class="kw">let </span><span class="kw-2">mut </span>hierarchy_sizes = Vec::with_capacity(num_hierarchy); |
| <span class="kw">let </span><span class="kw-2">mut </span>num_stages = Vec::new(); |
| <span class="kw">let </span><span class="kw-2">mut </span>wnd_src_id = Vec::new(); |
| |
| <span class="kw">for _ in </span><span class="number">0</span>..num_hierarchy { |
| <span class="kw">let </span>hierarchy_size = <span class="self">self</span>.read_i32()<span class="question-mark">?</span>; |
| hierarchy_sizes.push(hierarchy_size); |
| |
| <span class="kw">for _ in </span><span class="number">0</span>..hierarchy_size { |
| <span class="kw">let </span>num_stage = <span class="self">self</span>.read_i32()<span class="question-mark">?</span>; |
| num_stages.push(num_stage); |
| |
| <span class="kw">for _ in </span><span class="number">0</span>..num_stage { |
| <span class="kw">let </span>classifier_kind_id = <span class="self">self</span>.read_i32()<span class="question-mark">?</span>; |
| <span class="kw">let </span>classifier_kind = ClassifierKind::from(classifier_kind_id); |
| |
| <span class="kw">match </span>classifier_kind { |
| <span class="prelude-val">Some</span>(<span class="kw-2">ref </span>classifier_kind) => { |
| classifiers.push(<span class="self">self</span>.create_classifier(classifier_kind)<span class="question-mark">?</span>); |
| } |
| <span class="prelude-val">None </span>=> <span class="macro">panic!</span>(<span class="string">"Unexpected classifier kind id: {}"</span>, classifier_kind_id), |
| }; |
| } |
| |
| <span class="kw">let </span>num_wnd_src = <span class="self">self</span>.read_i32()<span class="question-mark">?</span>; |
| <span class="kw">let </span><span class="kw-2">mut </span>num_wnd_vec; |
| <span class="kw">if </span>num_wnd_src > <span class="number">0 </span>{ |
| num_wnd_vec = Vec::with_capacity(num_wnd_src <span class="kw">as </span>usize); |
| <span class="kw">for _ in </span><span class="number">0</span>..num_wnd_src { |
| num_wnd_vec.push(<span class="self">self</span>.read_i32()<span class="question-mark">?</span>); |
| } |
| } <span class="kw">else </span>{ |
| num_wnd_vec = Vec::new(); |
| } |
| wnd_src_id.push(num_wnd_vec); |
| } |
| } |
| |
| <span class="prelude-val">Ok</span>(Model { |
| classifiers, |
| wnd_src_id, |
| hierarchy_sizes, |
| num_stages, |
| }) |
| } |
| |
| <span class="kw">fn </span>create_classifier( |
| <span class="kw-2">&mut </span><span class="self">self</span>, |
| classifier_kind: <span class="kw-2">&</span>ClassifierKind, |
| ) -> <span class="prelude-ty">Result</span><Classifier, io::Error> { |
| <span class="kw">match </span><span class="kw-2">*</span>classifier_kind { |
| ClassifierKind::LabBoosted => { |
| <span class="kw">let </span><span class="kw-2">mut </span>classifier = LabBoostedClassifier::new(); |
| <span class="self">self</span>.read_lab_boosted_model(<span class="kw-2">&mut </span>classifier)<span class="question-mark">?</span>; |
| <span class="prelude-val">Ok</span>(Classifier::LabBoosted(classifier)) |
| } |
| ClassifierKind::SurfMlp => { |
| <span class="kw">let </span><span class="kw-2">mut </span>classifier = SurfMlpClassifier::new(); |
| <span class="self">self</span>.read_surf_mlp_model(<span class="kw-2">&mut </span>classifier)<span class="question-mark">?</span>; |
| <span class="prelude-val">Ok</span>(Classifier::SurfMlp(classifier)) |
| } |
| } |
| } |
| |
| <span class="kw">fn </span>read_lab_boosted_model( |
| <span class="kw-2">&mut </span><span class="self">self</span>, |
| classifier: <span class="kw-2">&mut </span>LabBoostedClassifier, |
| ) -> <span class="prelude-ty">Result</span><(), io::Error> { |
| <span class="kw">let </span>num_base_classifier = <span class="self">self</span>.read_i32()<span class="question-mark">?</span>; |
| <span class="kw">let </span>num_bin = <span class="self">self</span>.read_i32()<span class="question-mark">?</span>; |
| |
| <span class="kw">for _ in </span><span class="number">0</span>..num_base_classifier { |
| <span class="kw">let </span>x = <span class="self">self</span>.read_i32()<span class="question-mark">?</span>; |
| <span class="kw">let </span>y = <span class="self">self</span>.read_i32()<span class="question-mark">?</span>; |
| classifier.add_feature(x, y); |
| } |
| |
| <span class="kw">let </span><span class="kw-2">mut </span>thresh: Vec<f32> = Vec::with_capacity(num_base_classifier <span class="kw">as </span>usize); |
| <span class="kw">for _ in </span><span class="number">0</span>..num_base_classifier { |
| thresh.push(<span class="self">self</span>.read_f32()<span class="question-mark">?</span>); |
| } |
| |
| <span class="kw">for </span>i <span class="kw">in </span><span class="number">0</span>..num_base_classifier { |
| <span class="kw">let </span><span class="kw-2">mut </span>weights: Vec<f32> = Vec::with_capacity(num_bin <span class="kw">as </span>usize + <span class="number">1</span>); |
| <span class="kw">for _ in </span><span class="number">0</span>..weights.capacity() { |
| weights.push(<span class="self">self</span>.read_f32()<span class="question-mark">?</span>); |
| } |
| classifier.add_base_classifier(weights, thresh[i <span class="kw">as </span>usize]); |
| } |
| |
| <span class="prelude-val">Ok</span>(()) |
| } |
| |
| <span class="kw">fn </span>read_surf_mlp_model(<span class="kw-2">&mut </span><span class="self">self</span>, classifier: <span class="kw-2">&mut </span>SurfMlpClassifier) -> <span class="prelude-ty">Result</span><(), io::Error> { |
| <span class="kw">let </span>num_layer = <span class="self">self</span>.read_i32()<span class="question-mark">?</span>; |
| <span class="kw">let </span>num_feat = <span class="self">self</span>.read_i32()<span class="question-mark">?</span>; |
| |
| <span class="kw">for _ in </span><span class="number">0</span>..num_feat { |
| classifier.add_feature_id(<span class="self">self</span>.read_i32()<span class="question-mark">?</span>); |
| } |
| |
| classifier.set_threshold(<span class="self">self</span>.read_f32()<span class="question-mark">?</span>); |
| |
| <span class="kw">let </span><span class="kw-2">mut </span>input_dim = <span class="self">self</span>.read_i32()<span class="question-mark">?</span>; |
| <span class="kw">for </span>i <span class="kw">in </span><span class="number">1</span>..num_layer { |
| <span class="kw">let </span>output_dim = <span class="self">self</span>.read_i32()<span class="question-mark">?</span>; |
| |
| <span class="kw">let </span>weights_count = input_dim * output_dim; |
| <span class="kw">let </span><span class="kw-2">mut </span>weights: Vec<f32> = Vec::with_capacity(weights_count <span class="kw">as </span>usize); |
| <span class="kw">for _ in </span><span class="number">0</span>..weights_count { |
| weights.push(<span class="self">self</span>.read_f32()<span class="question-mark">?</span>); |
| } |
| |
| <span class="kw">let </span><span class="kw-2">mut </span>biases: Vec<f32> = Vec::with_capacity(output_dim <span class="kw">as </span>usize); |
| <span class="kw">for _ in </span><span class="number">0</span>..output_dim { |
| biases.push(<span class="self">self</span>.read_f32()<span class="question-mark">?</span>); |
| } |
| |
| <span class="kw">if </span>i == num_layer - <span class="number">1 </span>{ |
| classifier.add_output_layer( |
| input_dim <span class="kw">as </span>usize, |
| output_dim <span class="kw">as </span>usize, |
| weights, |
| biases, |
| ); |
| } <span class="kw">else </span>{ |
| classifier.add_layer(input_dim <span class="kw">as </span>usize, output_dim <span class="kw">as </span>usize, weights, biases); |
| } |
| |
| input_dim = output_dim; |
| } |
| |
| <span class="prelude-val">Ok</span>(()) |
| } |
| |
| <span class="attribute">#[inline] |
| </span><span class="kw">fn </span>read_i32(<span class="kw-2">&mut </span><span class="self">self</span>) -> <span class="prelude-ty">Result</span><i32, io::Error> { |
| <span class="self">self</span>.reader.read_i32::<LittleEndian>() |
| } |
| |
| <span class="attribute">#[inline] |
| </span><span class="kw">fn </span>read_f32(<span class="kw-2">&mut </span><span class="self">self</span>) -> <span class="prelude-ty">Result</span><f32, io::Error> { |
| <span class="self">self</span>.reader.read_f32::<LittleEndian>() |
| } |
| } |
| </code></pre></div> |
| </section></div></main><div id="rustdoc-vars" data-root-path="../../../" data-current-crate="rustface" data-themes="ayu,dark,light" data-resource-suffix="" data-rustdoc-version="1.66.0-nightly (5c8bff74b 2022-10-21)" ></div></body></html> |
