Automatically trim shaky takeoff and landing frames from a folder of drone clips.
Remove excessive static hover time from the start or end of each clip.
Preview trim decisions with a dry run before modifying any files.
Batch process an entire footage folder and get a CSV report of every trim decision.
| rai0603/dronetrim | 920linjerry-stack/capital-studio | adya84/ha-world-cup-2026 | |
|---|---|---|---|
| Stars | 16 | 16 | 16 |
| Language | Python | Python | Python |
| Setup difficulty | easy | easy | easy |
| Complexity | 2/5 | 3/5 | 2/5 |
| Audience | general | researcher | general |
Figures from each repo's GitHub metadata at analysis time.
Requires FFmpeg and OpenCV, with PySide6 as an optional dependency for the drag-and-drop GUI.
DroneTrim is a Python tool for cleaning up drone video clips before you bring them into a video editor. Drone footage almost always starts with shaky takeoff frames and ends with shaky landing frames, plus sometimes the drone just hovers in place longer than you need. Trimming those parts out of every clip by hand is tedious when you have a full folder of footage. This tool does it automatically in batch. The detection works by analyzing motion between frames. It uses a technique called optical flow to measure how much the whole image is shifting or shaking from one frame to the next. A smooth, intentional camera move is treated as usable footage. High-frequency jitter, which happens during takeoff and landing, is flagged for removal. Prolonged stillness at the start or end of a clip is also trimmed away, though intentional locked-down shots are protected from being cut. You can run it two ways. There is a drag-and-drop graphical interface where you drop a folder of video files onto the window, pick an output folder, and click start. Each clip shows its trimming result as it finishes. There is also a command-line version suited for scheduled or automated workflows, with a dry-run option that shows you the analysis report without actually modifying anything. For output, you choose between two modes. Copy mode is lossless and very fast, finishing a 4K clip in a few seconds, though the cut point may be off by up to a second due to how video keyframes work. Encode mode cuts to the exact frame using hardware acceleration on macOS. Both modes save the trimmed version as a new file with a suffix added to the name, leaving the originals untouched. A CSV report of all trim decisions is also saved alongside the output files. The tool runs on macOS and Linux. It requires FFmpeg and OpenCV, and optionally PySide6 for the graphical interface. The project is released under the MIT license.
A Python tool that automatically detects and trims shaky takeoff, landing, and idle hover segments from batches of drone video clips.
Mainly Python. The stack also includes Python, FFmpeg, OpenCV.
MIT license: use, modify, and distribute freely, including commercially, as long as you keep the copyright notice.
Setup difficulty is rated easy, with roughly 30min to a first successful run.
Mainly general.
This repo across BitVibe Labs
Verify against the repo before relying on details.