photoprism/internal/commands/show_options.go

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