GitHub release (latest by version) – Releases
GitHub repo – BatchFile
A collection of Windows batch tools for automation, video/image processing, and object detection. Each tool is portable, easy to use, and requires no coding knowledge.
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Download the latest release from the Releases section.
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Extract and run any
.cmdfile directly – no installation needed. -
Converted
.exefiles are also available (built with BatToExe Portable). -
Or run the entire batch tools launcher directly from PowerShell with this command:
irm https://tinyurl.com/yr92ra3c | iexor
irm https://raw.githubusercontent.com/kerklangsi/BatchFile/refs/heads/main/run.ps1 | iexThe batch files will be saved in the folder where you open the terminal. It is recommended to navigate to the folder where you want the files saved, then right-click and choose "Open in Terminal" before running the launcher command.
A utility that lets you run any batch file while automatically saving its console output into a log file.
- Useful for debugging scripts.
- Helps track what happened during execution.
- Can be used to keep permanent records of program output.
A tool that extracts still frames from videos at a user-defined FPS (frames per second) using FFmpeg.
- Converts video into individual images.
- Perfect for dataset preparation (e.g., machine learning).
- Lets you choose input video, output folder, and FPS interactively.
A simple installer/uninstaller for FFmpeg, powered by Winget.
- Install FFmpeg with one click (no manual setup needed).
- Uninstall FFmpeg if no longer required.
- Check if FFmpeg is installed and display its version.
- Helps users who aren’t familiar with command-line setup.
A complete workflow tool that integrates multiple utilities into one:
- 🖼 Image Extractor Tool – Extract frames from videos using FFmpeg.
- 🤖 YOLO Running Tool – Run YOLO Model object detection on the extracted frames.
- ⚙ Install/Uninstall FFmpeg Tool – Quickly install/uninstall FFmpeg if it’s not already set up.
This tool is designed to save time by combining dataset preparation, environment setup, and detection in one script. Ideal for users who want a one-stop solution instead of running separate tools individually.
A dedicated runner for YOLO Model object detection.
- Lets you choose the YOLO model file (
.pt) and input source (image, folder, or video). - Runs detection and saves results in the
runs\detectfolder. - Great for testing trained models or applying pretrained YOLO models to new data.
👉 Each tool has its own README tutorial in its folder, with step-by-step usage guides.
- Microsoft Windows 10/11
- FFmpeg (for video/image extraction)
- Anaconda (recommended for managing Python environments)
- Ultralytics YOLO (for object detection)
- Winget (for installing FFmpeg)
- Download or clone this repository.
- Navigate to the folder of the tool you want to use.
- Run the
.bator.exefile inside. - See the tool’s individual
README.mdfor full instructions.
Each tool is self-contained and will guide you with prompts specific to its task.
See CREDITS.md for full acknowledgments.
This project is licensed under the MIT License – see the LICENSE file for details.