242 lines
8.9 KiB
PHP
242 lines
8.9 KiB
PHP
<?php
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declare(strict_types=1);
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namespace OCA\Memories\Db;
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use OCP\DB\QueryBuilder\IQueryBuilder;
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use OCP\Files\Folder;
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use OCP\IDBConnection;
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trait TimelineQueryPeopleFaceRecognition
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{
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protected IDBConnection $connection;
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public function transformPeopleFaceRecognitionFilter(IQueryBuilder &$query, string $userId, int $currentModel, string $personStr)
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{
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// Get title and uid of face user
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$personNames = explode('/', $personStr);
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if (2 !== \count($personNames)) {
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throw new \Exception('Invalid person query');
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}
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$personUid = $personNames[0];
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$personName = $personNames[1];
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// Join with images
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$query->innerJoin('m', 'facerecog_images', 'fri', $query->expr()->andX(
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$query->expr()->eq('fri.file', 'm.fileid'),
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$query->expr()->eq('fri.model', $query->createNamedParameter($currentModel)),
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));
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// Join with faces
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$query->innerJoin(
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'fri',
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'facerecog_faces',
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'frf',
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$query->expr()->eq('frf.image', 'fri.id')
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);
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// Join with persons
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$nameField = is_numeric($personName) ? 'frp.id' : 'frp.name';
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$query->innerJoin('frf', 'facerecog_persons', 'frp', $query->expr()->andX(
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$query->expr()->eq('frf.person', 'frp.id'),
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$query->expr()->eq('frp.user', $query->createNamedParameter($personUid)),
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$query->expr()->eq($nameField, $query->createNamedParameter($personName)),
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));
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}
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public function transformPeopleFaceRecognitionRect(IQueryBuilder &$query, string $userId)
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{
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// Include detection params in response
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$query->addSelect(
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'frf.x AS face_x',
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'frf.y AS face_y',
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'frf.width AS face_width',
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'frf.height AS face_height',
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'm.w AS image_width',
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'm.h AS image_height',
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);
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}
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public function getPeopleFaceRecognition(TimelineRoot &$root, int $currentModel, bool $show_clusters = false, bool $show_singles = false, bool $show_hidden = false)
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{
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$query = $this->connection->getQueryBuilder();
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// SELECT all face clusters
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$count = $query->func()->count($query->createFunction('DISTINCT m.fileid'), 'count');
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$query->select('frp.id', 'frp.user as user_id', 'frp.name', $count)->from('facerecog_persons', 'frp');
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// WHERE there are faces with this cluster
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$query->innerJoin('frp', 'facerecog_faces', 'frf', $query->expr()->eq('frp.id', 'frf.person'));
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// WHERE faces are from images.
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$query->innerJoin('frf', 'facerecog_images', 'fri', $query->expr()->eq('fri.id', 'frf.image'));
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// WHERE these items are memories indexed photos
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$query->innerJoin('fri', 'memories', 'm', $query->expr()->andX(
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$query->expr()->eq('fri.file', 'm.fileid'),
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$query->expr()->eq('fri.model', $query->createNamedParameter($currentModel)),
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));
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// WHERE these photos are in the user's requested folder recursively
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$query = $this->joinFilecache($query, $root, true, false);
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if ($show_clusters) {
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// GROUP by ID of face cluster
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$query->groupBy('frp.id');
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$query->where($query->expr()->isNull('frp.name'));
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} else {
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// GROUP by name of face clusters
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$query->groupBy('frp.name');
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$query->where($query->expr()->isNotNull('frp.name'));
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}
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// By default hides individual faces when they have no name.
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if ($show_clusters && !$show_singles) {
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$query->having($query->expr()->gt('count', $query->createNamedParameter(1)));
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}
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// By default it shows the people who were not hidden
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if (!$show_hidden) {
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$query->andWhere($query->expr()->eq('frp.is_visible', $query->createNamedParameter(true)));
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}
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// ORDER by number of faces in cluster
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$query->orderBy('count', 'DESC');
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$query->addOrderBy('name', 'ASC');
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$query->addOrderBy('frp.id'); // tie-breaker
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// FETCH all faces
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$cursor = $this->executeQueryWithCTEs($query);
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$faces = $cursor->fetchAll();
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// Post process
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foreach ($faces as &$row) {
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$row['id'] = $row['name'] ?: (int) $row['id'];
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$row['count'] = (int) $row['count'];
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}
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return $faces;
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}
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public function getFaceRecognitionPreview(TimelineRoot &$root, $currentModel, $previewId)
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{
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$query = $this->connection->getQueryBuilder();
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// SELECT face detections
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$query->select(
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'fri.file as file_id', // Get actual file
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'frf.x', // Image cropping
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'frf.y',
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'frf.width',
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'frf.height',
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'm.w as image_width', // Scoring
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'm.h as image_height',
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'frf.confidence',
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'm.fileid',
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'm.datetaken', // Just in case, for postgres
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)->from('facerecog_faces', 'frf');
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// WHERE faces are from images and current model.
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$query->innerJoin('frf', 'facerecog_images', 'fri', $query->expr()->andX(
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$query->expr()->eq('fri.id', 'frf.image'),
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$query->expr()->eq('fri.model', $query->createNamedParameter($currentModel)),
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));
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// WHERE these photos are memories indexed
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$query->innerJoin('fri', 'memories', 'm', $query->expr()->eq('m.fileid', 'fri.file'));
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$query->innerJoin('frf', 'facerecog_persons', 'frp', $query->expr()->eq('frp.id', 'frf.person'));
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if (is_numeric($previewId)) {
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// WHERE faces are from id persons (a cluster).
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$query->where($query->expr()->eq('frp.id', $query->createNamedParameter($previewId)));
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} else {
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// WHERE faces are from name on persons.
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$query->where($query->expr()->eq('frp.name', $query->createNamedParameter($previewId)));
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}
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// WHERE these photos are in the user's requested folder recursively
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$query = $this->joinFilecache($query, $root, true, false);
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// LIMIT results
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$query->setMaxResults(15);
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// Sort by date taken so we get recent photos
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$query->orderBy('m.datetaken', 'DESC');
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$query->addOrderBy('m.fileid', 'DESC'); // tie-breaker
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// FETCH face detections
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$cursor = $this->executeQueryWithCTEs($query);
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$previews = $cursor->fetchAll();
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if (empty($previews)) {
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return null;
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}
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// Score the face detections
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foreach ($previews as &$p) {
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// Get actual pixel size of face
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$iw = min((int) ($p['image_width'] ?: 512), 2048);
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$ih = min((int) ($p['image_height'] ?: 512), 2048);
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// Get percentage position and size
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$p['x'] = (float) $p['x'] / $p['image_width'];
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$p['y'] = (float) $p['y'] / $p['image_height'];
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$p['width'] = (float) $p['width'] / $p['image_width'];
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$p['height'] = (float) $p['height'] / $p['image_height'];
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$w = (float) $p['width'];
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$h = (float) $p['height'];
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// Get center of face
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$x = (float) $p['x'] + (float) $p['width'] / 2;
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$y = (float) $p['y'] + (float) $p['height'] / 2;
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// 3D normal distribution - if the face is closer to the center, it's better
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$positionScore = exp(-($x - 0.5) ** 2 * 4) * exp(-($y - 0.5) ** 2 * 4);
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// Root size distribution - if the image is bigger, it's better,
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// but it doesn't matter beyond a certain point
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$imgSizeScore = ($iw * 100) ** (1 / 2) * ($ih * 100) ** (1 / 2);
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// Faces occupying too much of the image don't look particularly good
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$faceSizeScore = (-$w ** 2 + $w) * (-$h ** 2 + $h);
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// Combine scores
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$p['score'] = $positionScore * $imgSizeScore * $faceSizeScore * $p['confidence'];
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}
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// Sort previews by score descending
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usort($previews, function ($a, $b) {
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return $b['score'] <=> $a['score'];
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});
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return $previews;
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}
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/** Convert face fields to object */
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private function processFaceRecognitionDetection(&$row, $days = false)
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{
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if (!isset($row)) {
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return;
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}
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// Differentiate Recognize queries from Face Recognition
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if (!isset($row['face_width']) || !isset($row['image_width'])) {
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return;
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}
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if (!$days) {
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$row['facerect'] = [
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// Get percentage position and size
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'w' => (float) $row['face_width'] / $row['image_width'],
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'h' => (float) $row['face_height'] / $row['image_height'],
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'x' => (float) $row['face_x'] / $row['image_width'],
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'y' => (float) $row['face_y'] / $row['image_height'],
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];
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}
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unset($row['face_x'], $row['face_y'], $row['face_w'], $row['face_h'], $row['image_height'], $row['image_width']);
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}
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}
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