158 lines
3.5 KiB
Go
158 lines
3.5 KiB
Go
// backend\embed.go
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package main
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import (
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"embed"
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"os"
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"path/filepath"
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)
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//go:embed ml/*.py ml/detection_labels.json ai_server.py recorder-cert.pem recorder-key.pem yolo26n-pose.pt
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var embeddedMLFiles embed.FS
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func embeddedWriteFileIfNeeded(dstPath string, b []byte, perm os.FileMode) error {
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if fi, err := os.Stat(dstPath); err == nil && fi != nil && !fi.IsDir() && fi.Size() == int64(len(b)) {
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return nil
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}
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return os.WriteFile(dstPath, b, perm)
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}
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func trainingEmbeddedMLDir() (string, error) {
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dir := filepath.Join(os.TempDir(), "nsfwapp-ml")
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if err := os.MkdirAll(dir, 0755); err != nil {
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return "", err
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}
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files := []string{
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"predict_detector_model.py",
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"train_detector_model.py",
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"detection_labels.json",
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"predict_pose_model.py",
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"train_pose_model.py",
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"predict_videomae_model.py",
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"train_videomae_model.py",
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}
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// Falls du die alten Scene-Skripte noch embedded hast, kannst du sie optional mitkopieren.
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optionalFiles := []string{
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"predict_scene_model.py",
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"train_scene_model.py",
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}
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for _, name := range append(files, optionalFiles...) {
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srcPath := filepath.ToSlash(filepath.Join("ml", name))
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b, err := embeddedMLFiles.ReadFile(srcPath)
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if err != nil {
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// Pflichtdateien müssen vorhanden sein.
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if name == "detection_labels.json" ||
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name == "predict_detector_model.py" ||
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name == "train_detector_model.py" {
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return "", err
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}
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// Optionale alte Dateien ignorieren.
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continue
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}
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dstPath := filepath.Join(dir, name)
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if err := embeddedWriteFileIfNeeded(dstPath, b, 0644); err != nil {
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return "", err
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}
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}
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if _, err := embeddedPoseModelPath(); err != nil {
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return "", err
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}
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return dir, nil
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}
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func embeddedMLScriptExists(name string) bool {
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srcPath := filepath.ToSlash(filepath.Join("ml", name))
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_, err := embeddedMLFiles.ReadFile(srcPath)
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return err == nil
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}
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func embeddedAIServerDir() (string, error) {
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dir := filepath.Join(os.TempDir(), "nsfwapp-ai-server")
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if err := os.MkdirAll(dir, 0755); err != nil {
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return "", err
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}
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b, err := embeddedMLFiles.ReadFile("ai_server.py")
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if err != nil {
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return "", err
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}
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dstPath := filepath.Join(dir, "ai_server.py")
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if err := embeddedWriteFileIfNeeded(dstPath, b, 0644); err != nil {
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return "", err
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}
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return dir, nil
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}
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func embeddedPoseModelPath() (string, error) {
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dir := filepath.Join(os.TempDir(), "nsfwapp-ml")
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if err := os.MkdirAll(dir, 0755); err != nil {
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return "", err
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}
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b, err := embeddedMLFiles.ReadFile("yolo26n-pose.pt")
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if err != nil {
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return "", err
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}
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dstPath := filepath.Join(dir, "yolo26n-pose.pt")
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if err := embeddedWriteFileIfNeeded(dstPath, b, 0644); err != nil {
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return "", err
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}
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return dstPath, nil
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}
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func embeddedTLSCertBytes() ([]byte, error) {
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return embeddedMLFiles.ReadFile("recorder-cert.pem")
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}
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func embeddedTLSKeyBytes() ([]byte, error) {
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return embeddedMLFiles.ReadFile("recorder-key.pem")
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}
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func embeddedTLSFilesDir() (string, string, error) {
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dir := filepath.Join(os.TempDir(), "nsfwapp-tls")
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if err := os.MkdirAll(dir, 0700); err != nil {
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return "", "", err
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}
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certBytes, err := embeddedTLSCertBytes()
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if err != nil {
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return "", "", err
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}
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keyBytes, err := embeddedTLSKeyBytes()
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if err != nil {
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return "", "", err
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}
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certPath := filepath.Join(dir, "recorder-cert.pem")
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keyPath := filepath.Join(dir, "recorder-key.pem")
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if err := os.WriteFile(certPath, certBytes, 0600); err != nil {
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return "", "", err
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}
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if err := os.WriteFile(keyPath, keyBytes, 0600); err != nil {
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return "", "", err
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}
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return certPath, keyPath, nil
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}
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