AI Video Editing Tool Development
Budget: €30 – €250 EUR
I need a custom-built AI that can take my raw short clips and automatically turn them into polished, “ready-to-share” videos. The tool must recognise good in- and out-points, apply smooth transitions or hard cuts where appropriate, balance and clean the audio, and finish each clip with consistent colour correction so it looks as if a professional editor worked on it.
Key behaviour
• Input: assorted short clips (mostly shot on a phone, 15 – 90 sec each).
• Processing: scene detection for intelligent cuts, library of tasteful transitions, automatic loudness levelling and basic noise reduction, followed by colour matching/grading that keeps skin-tones natural.
• Output: an mp4 or mov file that can be posted straight to social or sent to friends without further tweaks.
Deliverables
1. An executable desktop app or command-line script (Windows or cross-platform) that performs the full workflow in one pass.
2. Source code with clear instructions on how to retrain or tweak the model if my visual style changes.
3. A concise user guide showing the few steps I need to run it.
Acceptance criteria
• Drop-in usage: I point the tool at a folder of clips, pick a destination folder, press “Go”, and receive an edited file.
• Cuts feel natural; no jarring jump-cuts unless the algorithm intentionally applies a jump effect.
• Average loudness around –14 LUFS with minimal background hiss.
• Colour consistency between consecutive shots within ±3 ΔE.
You’re free to choose the stack—Python with OpenCV, FFmpeg, or a lightweight TensorFlow/PyTorch model, for instance—as long as setup is simple and performance is reasonable on a modern laptop without a dedicated GPU.
Key behaviour
• Input: assorted short clips (mostly shot on a phone, 15 – 90 sec each).
• Processing: scene detection for intelligent cuts, library of tasteful transitions, automatic loudness levelling and basic noise reduction, followed by colour matching/grading that keeps skin-tones natural.
• Output: an mp4 or mov file that can be posted straight to social or sent to friends without further tweaks.
Deliverables
1. An executable desktop app or command-line script (Windows or cross-platform) that performs the full workflow in one pass.
2. Source code with clear instructions on how to retrain or tweak the model if my visual style changes.
3. A concise user guide showing the few steps I need to run it.
Acceptance criteria
• Drop-in usage: I point the tool at a folder of clips, pick a destination folder, press “Go”, and receive an edited file.
• Cuts feel natural; no jarring jump-cuts unless the algorithm intentionally applies a jump effect.
• Average loudness around –14 LUFS with minimal background hiss.
• Colour consistency between consecutive shots within ±3 ΔE.
You’re free to choose the stack—Python with OpenCV, FFmpeg, or a lightweight TensorFlow/PyTorch model, for instance—as long as setup is simple and performance is reasonable on a modern laptop without a dedicated GPU.
Related categories:
Python
Machine Learning (ML)
Video Editing
OpenCV
Audio Processing
Video Processing
Color Grading