121 lines
3.6 KiB
Go
121 lines
3.6 KiB
Go
package commands
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import (
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"fmt"
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"github.com/sirupsen/logrus"
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"github.com/urfave/cli"
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"github.com/photoprism/photoprism/internal/config"
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"github.com/photoprism/photoprism/pkg/report"
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)
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// ShowOptionsCommand configures the command name, flags, and action.
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var ShowOptionsCommand = cli.Command{
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Name: "options",
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Aliases: []string{"flags"},
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Usage: "Displays supported config flags and variable names",
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Flags: report.CliFlags,
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Action: showOptionsAction,
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}
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var faceOptionsInfo = `!!! info ""
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To [recognize faces](https://docs.photoprism.app/user-guide/organize/people/), PhotoPrism first extracts crops from your images using a
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[library](https://github.com/esimov/pigo) based on [pixel intensity comparisons](https://arxiv.org/pdf/1305.4537.pdf).
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These are then fed into TensorFlow to compute [512-dimensional vectors](https://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Schroff_FaceNet_A_Unified_2015_CVPR_paper.pdf)
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for characterization. In the final step, the [DBSCAN algorithm](https://en.wikipedia.org/wiki/DBSCAN)
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attempts to cluster these so-called face embeddings, so they can be matched to persons with just a few clicks.
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A reasonable range for the similarity distance between face embeddings is between 0.60 and 0.70, with a higher
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value being more aggressive and leading to larger clusters with more false positives.
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To cluster a smaller number of faces, you can reduce the core to 3 or 2 similar faces.
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We recommend that only advanced users change these parameters:`
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// showOptionsAction shows environment variable command-line parameter names.
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func showOptionsAction(ctx *cli.Context) error {
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conf := config.NewConfig(ctx)
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conf.SetLogLevel(logrus.FatalLevel)
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rows, cols := config.Flags.Report()
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// CSV Export?
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if ctx.Bool("csv") || ctx.Bool("tsv") {
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result, err := report.Render(rows, cols, report.CliFormat(ctx))
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fmt.Println(result)
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return err
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}
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type Section struct {
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Start string
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Caption string
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Info string
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}
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s := []Section{
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{Start: "PHOTOPRISM_ADMIN_PASSWORD", Caption: "Authentication"},
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{Start: "PHOTOPRISM_LOG_LEVEL", Caption: "Logging"},
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{Start: "PHOTOPRISM_CONFIG_PATH", Caption: "Storage"},
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{Start: "PHOTOPRISM_WORKERS", Caption: "Index Workers"},
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{Start: "PHOTOPRISM_READONLY", Caption: "Feature Flags"},
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{Start: "PHOTOPRISM_DEFAULT_LOCALE", Caption: "Customization"},
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{Start: "PHOTOPRISM_CDN_URL", Caption: "Site Information"},
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{Start: "PHOTOPRISM_HTTP_PORT", Caption: "Web Server"},
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{Start: "PHOTOPRISM_DATABASE_DRIVER", Caption: "Database Connection"},
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{Start: "PHOTOPRISM_DARKTABLE_BIN", Caption: "File Converters"},
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{Start: "PHOTOPRISM_DOWNLOAD_TOKEN", Caption: "Security Tokens"},
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{Start: "PHOTOPRISM_THUMB_COLOR", Caption: "Image Quality"},
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{Start: "PHOTOPRISM_FACE_SIZE", Caption: "Face Recognition",
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Info: faceOptionsInfo},
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{Start: "PHOTOPRISM_PID_FILENAME", Caption: "Daemon Mode",
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Info: "If you start the server as a *daemon* in the background, you can additionally specify a filename for the log and the process ID:"},
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}
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j := 0
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for i, sec := range s {
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fmt.Printf("### %s ###\n\n", sec.Caption)
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if sec.Info != "" && ctx.Bool("md") {
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fmt.Printf("%s\n\n", sec.Info)
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}
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secRows := make([][]string, 0, len(rows))
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for {
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row := rows[j]
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if len(row) < 1 {
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continue
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}
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if i < len(s)-1 {
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if s[i+1].Start == row[0] {
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break
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}
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}
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secRows = append(secRows, row)
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j++
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if j >= len(rows) {
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break
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}
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}
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result, err := report.Render(secRows, cols, report.CliFormat(ctx))
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if err != nil {
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return err
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}
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fmt.Println(result)
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if j >= len(rows) {
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break
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}
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}
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return nil
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}
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