You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: index_labels.go
    path of file: ./repos/photoprism/internal/photoprism
    
    the code of the file until where you have to start completion: package photoprism

import (
	"sort"
	"time"

	"github.com/photoprism/photoprism/internal/classify"
	"github.com/photoprism/photoprism/internal/thumb"
	"github.com/photoprism/photoprism/pkg/clean"
)

// Labels classifies a JPEG image and returns matching labels.
func (ind *Index) Labels(jpeg *MediaFile) (results classify.Labels) {
	start := time.Now()

	var sizes []thumb.Name

	if jpeg.Aspect
    
func (ind *Index) Labels(jpeg *MediaFile) (results classify.Labels) {
	start := time.Now()

	var sizes []thumb.Name

	if jpeg.AspectRatio() == 1 {
		sizes = []thumb.Name{thumb.Tile224}
	} else {
		sizes = []thumb.Name{thumb.Tile224, thumb.Left224, thumb.Right224}
	}

	var labels classify.Labels

	for _, size := range sizes {
		filename, err := jpeg.Thumbnail(Config().ThumbCachePath(), size)

		if err != nil {
			log.Debugf("%s in %s", err, clean.Log(jpeg.BaseName()))
			continue
		}

		imageLabels, err := ind.tensorFlow.File(filename)

		if err != nil {
			log.Debugf("%s in %s", err, clean.Log(jpeg.BaseName()))
			continue
		}

		labels = append(labels, imageLabels...)
	}

	// Sort by priority and uncertainty
	sort.Sort(labels)

	var confidence int

	for _, label := range labels {
		if confidence == 0 {
			confidence = 100 - label.Uncertainty
		}

		if (100 - label.Uncertainty) > (confidence / 3) {
			results = append(results, label)
		}
	}

	if l := len(labels); l == 1 {
		log.Infof("index: matched %d label with %s [%s]", l, clean.Log(jpeg.BaseName()), time.Since(start))
	} else if l > 1 {
		log.Infof("index: matched %d labels with %s [%s]", l, clean.Log(jpeg.BaseName()), time.Since(start))
	}

	return results
}