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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\DlibCnnHogModel; |
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use OCA\FaceRecognition\Helper\FaceRect; |
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use OCA\FaceRecognition\Model\IModel; |
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use OCA\FaceRecognition\Model\DlibCnnModel\DlibCnn5Model; |
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class DlibCnnHogModel implements IModel { |
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/* |
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* Model files. |
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*/ |
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const FACE_MODEL_ID = 4; |
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const FACE_MODEL_NAME = "DlibCnnHog5"; |
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const FACE_MODEL_DESC = "Extends the main 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-4"; |
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/** @var DlibCnn5Model */ |
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private $dlibCnn5Model; |
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/** |
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* DlibCnnHogModel __construct. |
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* |
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* @param DlibCnn5Model $dlibCnn5Model |
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*/ |
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public function __construct(DlibCnn5Model $dlibCnn5Model) |
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{ |
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$this->dlibCnn5Model = $dlibCnn5Model; |
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} |
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public function getId(): int { |
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return static::FACE_MODEL_ID; |
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} |
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public function getName(): string { |
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return static::FACE_MODEL_NAME; |
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} |
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public function getDescription(): string { |
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return static::FACE_MODEL_DESC; |
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} |
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public function getDocumentation(): string { |
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return static::FACE_MODEL_DOC; |
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} |
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public function isInstalled(): bool { |
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if (!$this->dlibCnn5Model->isInstalled()) |
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return false; |
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return true; |
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} |
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public function meetDependencies(string &$error_message): bool { |
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if (!$this->dlibCnn5Model->isInstalled()) { |
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$error_message = "This Model depend on Model 1 and must install it."; |
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return false; |
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} |
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return true; |
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} |
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public function getMaximumArea(): int { |
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return $this->dlibCnn5Model->getMaximumArea(); |
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} |
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public function getPreferredMimeType(): string { |
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return $this->dlibCnn5Model->getPreferredMimeType(); |
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} |
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/** |
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* @return void |
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*/ |
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public function install() { |
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// This model reuses models 1 and should not install anything. |
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} |
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/** |
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* @return void |
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*/ |
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public function open() { |
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$this->dlibCnn5Model->open(); |
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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 = $this->dlibCnn5Model->detectFaces($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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public function compute(string $imagePath, array $face): array { |
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return $this->dlibCnn5Model->compute($imagePath, $face); |
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} |
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private function validateFace($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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