Funktionen

Funktionen

Entdecken Sie alle leistungsstarken Funktionen von TjMakeBot für KI-Bildannotation, Cloud-YOLO-Training und Modellexport.

Integrierter KI-Assistent für automatische Annotation per ChatCloud-YOLO-Modelltraining mit GPU-BeschleunigungMulti-Format-Modellexport: PyTorch/ONNX/TensorRT/CoreML/TFLiteMehrere Annotationstypen: Bounding Boxes, Polygone, OBB, Keypoints
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Alle Funktionen

Entdecken Sie TjMakeBot-Funktionen: KI-Assistent, Cloud-YOLO-Training, Multi-Format-Export, Video-Decoder, Batch-Erkennung, mehrsprachige Unterstützung.

🤖 AI Assistant for Automatic Annotation

Chatten Sie mit KI, um Bilder mit natürlicher Sprache automatisch zu annotieren. Beschreiben Sie, was Sie kennzeichnen möchten.

Der KI-Assistent nutzt fortschrittliche Computer-Vision-Modelle, um Ihre Anweisungen zu verstehen. Befehle wie 'alle Personen annotieren' werden unterstützt.

Natürliche Sprachverarbeitung für intuitive Annotation
Unterstützung mehrerer Objekttypen in einem Befehl
Batch processing with "Auf alle Bilder anwenden"
Hochauflösungsmodus für detaillierte Annotationen
Deep-Thinking-Modus für komplexe Szenen
☁️ Cloud YOLO Model Training

Train YOLOv5/v8/v9/v10/v11 models in the cloud with GPU acceleration. No local environment setup required.

After completing annotations, submit training tasks directly from your browser. Supports YOLOv5, YOLOv8, YOLOv9, YOLOv10, YOLOv11 and more. Configure epochs, batch size, image size, and other parameters. Training progress is pushed in real-time via WebSocket, with email notifications upon completion.

Support for YOLOv5, YOLOv8, YOLOv9, YOLOv10, YOLOv11
Cloud GPU acceleration, no local setup needed
Configurable training parameters
Real-time progress monitoring via WebSocket
Email notification when training completes
📦 Multi-Format Model Export

Export trained models to PyTorch, ONNX, TensorRT, CoreML, TFLite, OpenVINO, NCNN and more formats.

Choose the right model format for your deployment needs: PyTorch (.pt) for research and continued training, ONNX for cross-platform inference, TensorRT for NVIDIA GPU acceleration, CoreML for iOS/macOS deployment, TFLite for Android/TensorFlow, OpenVINO for Intel hardware acceleration, NCNN for mobile and embedded devices.

PyTorch (.pt) for research and training
ONNX for cross-platform inference
TensorRT for NVIDIA GPU acceleration
CoreML for iOS/macOS deployment
TFLite, OpenVINO, NCNN for edge devices
🎯 Mehrere Annotationstypen

Support for bounding boxes, polygons, oriented bounding boxes (OBB), and keypoint annotations.

Different computer vision tasks require different annotation types. TjMakeBot supports all common annotation types to meet your diverse needs.

Bounding boxes (rectangles) for object detection
Polygons for precise object boundaries
Oriented bounding boxes (OBB) for rotated objects
Keypoint annotations for pose estimation
Support for COCO person, face, and hand keypoint templates

This is more than a feature list

The buying decision usually changes when teams stop asking only what the editor can do, and start asking how review, versions, and delivery fit together.

Review and QA operations

Move from isolated annotation actions into shared review routing, issue handling, and delivery checkpoints.

Dataset versions and release delivery

Connect approved output to dataset versions, training results, and customer handoff.

Enterprise security and deployment

Use the platform to manage permissions, audit requirements, and deployment planning.

Automation and integration

Integrate automation, API access, and review processes into one platform.

Funktionen

Signals that the feature discussion is becoming a platform decision

The team needs review routing, issue tracking, and handoff instead of solo annotation only.
The buyer asks which dataset version is behind training and delivery.
Procurement starts asking about deployment, audit scope, or permission boundaries.
Rollout requires API access or automation planning.
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🗂️ Multiple Annotation Formats

Support for YOLO, Pascal VOC, COCO, and CSV formats. Import and export in any format you need.

YOLO format (YOLOv5, YOLOv8, YOLOv9, YOLOv10, YOLOv11)
Pascal VOC XML format
COCO JSON format
CSV format for data analysis
Simultaneous multi-format export

🎬 Video to Frames Decoder

Extract frames from videos at custom FPS for video object detection dataset creation.

Custom FPS setting (1-60 FPS)
Support for MP4, AVI, MOV formats
Batch video processing
Automatic frame extraction
Preserves video metadata

⚡ Batch Object Detection

Use trained models to automatically detect objects across multiple images at once.

Support for YOLO and ONNX models
Customizable confidence threshold
Configurable input size
Batch processing for efficiency
Automatic annotation generation

🌐 Multilingual Support

Interface available in 9 languages: English, Chinese, Japanese, Korean, German, French, Russian, and more.

9 interface languages
Full UI translation
Localized documentation
Cultural adaptation
RTL language support (coming soon)

🖱️ Trackpad Optimization

Optimized zoom and pan controls for trackpad users, making annotation smooth and efficient.

Pinch-to-zoom support
Two-finger pan gestures
Smooth scrolling
Precise crosshair positioning
Keyboard shortcuts for power users

🖼️ High-Resolution Image Support

Handle high-resolution images efficiently with optimized rendering and memory management.

Support for 4K+ images
Optimized memory usage
Progressive loading
Smart caching
Smooth performance

🆓 Free to Use

Core features are completely free. No installation required, works directly in your browser.

100% free core features
No installation required
Works in any modern browser
Kostenlose KI-Credits für neue Nutzer
No credit card required

Go deeper on the platform operating system

If the core feature list already makes sense, the next step is to move into workflow, dataset versions, quality control, and team production.

Workflow

Daten-Engine / Workflow

Verbinden Sie Annotation, Review, Training, Export und Lieferung in einem Daten-Workflow.

Workflow-Seite ansehen →
Datensatzversionen

Datensatzversionen

Machen Sie Datensätze mit Versions-Freeze, Übergabeverlauf und reproduzierbarem Training zu Release-Artefakten.

Versionsseite ansehen →
Qualitätskontrolle

Qualitätskontrolle

Bringen Sie Stichprobenprüfung, Review-Loops, Nacharbeit und Abnahme-Gates direkt in die Plattform.

Qualitätsseite ansehen →
Team-Produktion

Team-Produktion

Führen Sie teamweite Datenproduktion mit gemeinsamem Workspace, Rollenrouting und transparenter Durchsatzsicht aus.

Team-Seite ansehen →

Entdecken Sie TjMakeBot-Funktionen: KI-Assistent, Cloud-YOLO-Training, Multi-Format-Export, Video-Decoder, Batch-Erkennung, mehrsprachige Unterstützung.

Dataset-Versionen, Release-Bereitstellung und Lineage sind Teil des Plattformpfads
Review, Issue-Handling und Delivery-Übergabe arbeiten als eine Bedienoberfläche
Download-Einstieg, Übergabelink und teilbare Übersichtsseite
Keep agent entry separate from enterprise data boundaries, with the main site owning security, audit, and accountability.
Decode video to frames and annotate directly
Apply AI annotations to all images at once
YOLO/VOC/COCO/CSV import & export
Load trained model for batch detection and validation
Import existing annotations for review and validation
Funktionen

Need enterprise rollout or integration planning?

Use Pricing and Security next when the decision depends on review governance, deployment options, audit scope, or API access planning.

Tutorials & BenutzerhandbuchPreiseSicherheit prüfenEnterprise kontaktieren