Cyberbol Released AI Video Clipper LoRA Tool For Caption Generation
AI Video Clipper LoRA is a dataset preparation tool that helps users create training data for video LoRA models such as LTX-2 and HunyuanVideo. The software automatically processes long videos, cutting them into shorter segments while generating text descriptions for each clip.
Developed by Cyberbol, this open-source solution addresses the time-consuming task of preparing video datasets for machine learning. The tool works across Windows, Linux, and Docker environments, with native support for WSL and cloud platforms like RunPod.
Key Features for dataset preparation
- Automatically clips long videos using WhisperX speech detection.
- Generates captions using vision-capable language models.
- Processes image datasets with descriptive text generation.
- Analyzes both visual content and background audio.
- Provides one-click Windows installation with isolated environment.
- Supports cloud GPU deployment for higher VRAM processing.
Machine learning practitioners and content creators can automate much of their dataset preparation workflow with this tool. Instead of manually cutting footage and writing descriptions, users simply save time by uploading source material and let the software handle segmentation as well as captioning across large files.
Technical details of AI Video Clipper LoRA's compatibility
The current release includes patches for NVIDIA's latest Blackwell architecture, ensuring compatibility with the RTX 5090. Cyberbol collaborated with FNGarvin on backend systems development, with community tester WildSpeaker7315 contributing hardware testing.
Users should note that enabling audio analysis requires downloading an additional Qwen2-Audio model of approximately 15GB. The development team indicates this feature may slow processing due to model swapping in GPU memory.
Read more about the AI Video Clipper LoRA tool on their GitHub.
