113 lines
3.6 KiB
Go
113 lines
3.6 KiB
Go
package commands
|
|
|
|
import (
|
|
"fmt"
|
|
|
|
"github.com/sirupsen/logrus"
|
|
"github.com/urfave/cli"
|
|
|
|
"github.com/photoprism/photoprism/internal/config"
|
|
"github.com/photoprism/photoprism/pkg/report"
|
|
)
|
|
|
|
// ShowConfigOptionsCommand configures the command name, flags, and action.
|
|
var ShowConfigOptionsCommand = cli.Command{
|
|
Name: "config-options",
|
|
Usage: "Displays supported environment variables and CLI flags",
|
|
Flags: report.CliFlags,
|
|
Action: showConfigOptionsAction,
|
|
}
|
|
|
|
var faceFlagsInfo = `!!! 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://dl.photoprism.app/pdf/20140820-Pixel_Intensity_Comparisons.pdf). These are then fed into TensorFlow to compute [512-dimensional vectors](https://dl.photoprism.app/pdf/20150101-FaceNet.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:`
|
|
|
|
// showConfigOptionsAction displays supported environment variables and CLI flags.
|
|
func showConfigOptionsAction(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.RenderFormat(rows, cols, report.CliFormat(ctx))
|
|
|
|
fmt.Println(result)
|
|
|
|
return err
|
|
}
|
|
|
|
type Section struct {
|
|
Start string
|
|
Title string
|
|
Info string
|
|
}
|
|
|
|
s := []Section{
|
|
{Start: "PHOTOPRISM_ADMIN_PASSWORD", Title: "Authentication"},
|
|
{Start: "PHOTOPRISM_LOG_LEVEL", Title: "Logging"},
|
|
{Start: "PHOTOPRISM_CONFIG_PATH", Title: "Storage"},
|
|
{Start: "PHOTOPRISM_WORKERS", Title: "Index Workers"},
|
|
{Start: "PHOTOPRISM_READONLY", Title: "Feature Flags"},
|
|
{Start: "PHOTOPRISM_DEFAULT_LOCALE", Title: "Customization"},
|
|
{Start: "PHOTOPRISM_CDN_URL", Title: "Site Information"},
|
|
{Start: "PHOTOPRISM_HTTPS_PROXY", Title: "Proxy Servers"},
|
|
{Start: "PHOTOPRISM_DISABLE_TLS", Title: "Web Server"},
|
|
{Start: "PHOTOPRISM_DATABASE_DRIVER", Title: "Database Connection"},
|
|
{Start: "PHOTOPRISM_DARKTABLE_BIN", Title: "File Converters"},
|
|
{Start: "PHOTOPRISM_DOWNLOAD_TOKEN", Title: "Security Tokens"},
|
|
{Start: "PHOTOPRISM_THUMB_COLOR", Title: "Image Quality"},
|
|
{Start: "PHOTOPRISM_FACE_SIZE", Title: "Face Recognition",
|
|
Info: faceFlagsInfo},
|
|
{Start: "PHOTOPRISM_PID_FILENAME", Title: "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.Title)
|
|
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.RenderFormat(secRows, cols, report.CliFormat(ctx))
|
|
|
|
if err != nil {
|
|
return err
|
|
}
|
|
|
|
fmt.Println(result)
|
|
|
|
if j >= len(rows) {
|
|
break
|
|
}
|
|
}
|
|
|
|
return nil
|
|
}
|