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<?php |
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/** |
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* @copyright Copyright (c) 2020-2024, Matias De lellis <[email protected]> |
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* |
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* @author Matias De lellis <[email protected]> |
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* |
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* @license GNU AGPL version 3 or any later version |
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* |
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* This program is free software: you can redistribute it and/or modify |
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* it under the terms of the GNU Affero General Public License as |
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* published by the Free Software Foundation, either version 3 of the |
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* License, or (at your option) any later version. |
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* |
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* This program is distributed in the hope that it will be useful, |
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* but WITHOUT ANY WARRANTY; without even the implied warranty of |
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
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* GNU Affero General Public License for more details. |
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* |
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* You should have received a copy of the GNU Affero General Public License |
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* along with this program. If not, see <http://www.gnu.org/licenses/>. |
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* |
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*/ |
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namespace OCA\FaceRecognition\Model\DlibTaguchiHogModel; |
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use OCA\FaceRecognition\Helper\FaceRect; |
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use OCA\FaceRecognition\Model\DlibCnnModel\DlibCnnModel; |
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use OCA\FaceRecognition\Model\IModel; |
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class DlibTaguchiHogModel extends DlibCnnModel implements IModel { |
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/* |
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* Model files. |
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*/ |
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const FACE_MODEL_ID = 6; |
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const FACE_MODEL_NAME = "DlibTaguchiHog"; |
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const FACE_MODEL_DESC = "Extends the Taguchi model, doing a face validation with the Hog detector"; |
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const FACE_MODEL_DOC = "https://github.com/matiasdelellis/facerecognition/wiki/Models#model-6"; |
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/** Relationship between image size and memory consumed */ |
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const MEMORY_AREA_RELATIONSHIP = 1 * 1024; |
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const MINIMUM_MEMORY_REQUIREMENTS = 1 * 1024 * 1024 * 1024; |
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/* |
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* Model files. |
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*/ |
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const FACE_MODEL_FILES = [ |
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'detector' => [ |
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'url' => 'https://github.com/davisking/dlib-models/raw/94cdb1e40b1c29c0bfcaf7355614bfe6da19460e/mmod_human_face_detector.dat.bz2', |
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'filename' => 'mmod_human_face_detector.dat' |
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], |
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'predictor' => [ |
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'url' => 'https://github.com/davisking/dlib-models/raw/4af9b776281dd7d6e2e30d4a2d40458b1e254e40/shape_predictor_5_face_landmarks.dat.bz2', |
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'filename' => 'shape_predictor_5_face_landmarks.dat', |
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], |
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'resnet' => [ |
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'url' => 'https://github.com/TaguchiModels/dlibModels/raw/main/taguchi_face_recognition_resnet_model_v1.7z', |
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'filename' => 'taguchi_face_recognition_resnet_model_v1.dat' |
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] |
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]; |
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public function detectFaces(string $imagePath, bool $compute = true): array { |
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$detectedFaces = []; |
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$cnnFaces = parent::detectFaces($imagePath); |
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if (count($cnnFaces) === 0) { |
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return $detectedFaces; |
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} |
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$hogFaces = dlib_face_detection($imagePath); |
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foreach ($cnnFaces as $proposedFace) { |
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$detectedFaces[] = $this->validateFace($proposedFace, $hogFaces); |
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} |
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return $detectedFaces; |
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} |
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private function validateFace($proposedFace, array $validateFaces) { |
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foreach ($validateFaces as $validateFace) { |
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$overlapPercent = FaceRect::overlapPercent($proposedFace, $validateFace); |
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/** |
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* The weak link in our default model is the landmark detector that |
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* can't align profile or rotate faces correctly. |
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* |
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* The Hog detector also fails and cannot detect these faces. So, we |
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* consider if Hog detector can detect it, to infer when the predictor |
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* will give good results. |
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* |
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* If Hog detects it (Overlap > 35%), we can assume that landmark |
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* detector will do it too. In this case, we consider the face valid, |
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* and just return it. |
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*/ |
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if ($overlapPercent >= 0.35) { |
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return $proposedFace; |
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} |
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} |
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/** |
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* If Hog don't detect this face, they are probably in profile or rotated. |
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* These are bad to compare, so we lower the confidence, to avoid clustering. |
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*/ |
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$confidence = $proposedFace['detection_confidence']; |
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$proposedFace['detection_confidence'] = $confidence * 0.6; |
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return $proposedFace; |
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} |
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} |
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