Edit videos in Python Using moviePy | Upload to Vimeo

Introduction

Welcome back to my channel! In this article, I will walk you through a practical video editing project that harnesses the power of Python with the MoviePy library. This comprehensive tutorial covers everything from downloading videos from Vimeo to editing them and uploading the finished product back to Vimeo.

Project Overview

The hierarchy of our project is straightforward and consists of several key steps:

1. Download the Video: We will first download a video from Vimeo.
2. Scene Detection with OpenCV: Using OpenCV, we will detect and select only the important scenes from the video.
3. Editing with MoviePy: Once we have selected the scenes, we will use MoviePy to:
   • Trim the video
   • Crop the video
   • Add audio, logo, and text
4. Upload Processed Video: Finally, we will upload the edited video back to Vimeo.

Keep in mind that video processing can take time, typically around 4 to 5 minutes, so we will implement threading to avoid server crashes during this lengthy operation.

Required Libraries

To complete this project successfully, you will need to install the following libraries in Python:

• Flask
• MoviePy
• OpenCV
• Threading
• Requests
• ImageMagick (installation varied by OS)

Additionally, set the path of ImageMagick in your environment variables after installation.

Step-by-Step Process

Download Videos

The first step involves creating a folder named downloaded_videos, where all our local assets—videos, logos, and audio files from Vimeo—will be stored. We use the requests library to download the video by providing the Vimeo URL. If the response code is 200, the video download will be executed successfully.

Scene Detection

OpenCV is utilized to implement scene detection. By calculating similarity scores, we can select scenes based on our defined thresholds. The frames of detected scenes are stored in an array and appended to create a final compilation of important clips.

Video Editing with MoviePy

Once we have the important clips, we can start editing the video using MoviePy. The key operations include:

• Trimming: Identifying start and end times to trim the video to the desired length.
• Cropping: We use VFX functionalities to crop without losing significant parts of the scene.
• Adding Text and Logos: Text and logos will be positioned automatically using a helper function that adjusts their locations according to the video's size.
• Audio Overlays: We combine audio clips using CompositeAudioClip, allowing us to blend the original audio with a background track.

Uploading to Vimeo

After processing and saving the edited video to the downloaded_videos folder, we can then upload it back to Vimeo using the Vimeo API. I tailored the upload code based on Vimeo's documentation and adjusted it for compatibility.

Task Status Handling

To handle the task status effectively, I created a dictionary structure that tracks the various states of the processing stages (e.g., processing, completed, failed). Threading is implemented to ensure that while the video is processing, the server does not crash and can respond immediately to incoming requests.

Result

Once you run the code, you will observe that the processed video retains the important scenes while featuring the added text and logos. The final output includes background music to enhance the viewer’s experience.

Conclusion

This article aims to provide a detailed overview of how to edit videos in Python using MoviePy while uploading the finished work to Vimeo. If you have any questions or need the code, please feel free to comment!

Keywords

• Python
• MoviePy
• Vimeo
• OpenCV
• Video Editing
• Download
• Upload
• Audio
• Logo
• Text
• Threading

FAQ

1. What is MoviePy used for?

MoviePy is a Python library for video editing, allowing for easy manipulation of video files, including cutting, combining, and adding effects.

2. How do I install MoviePy?

You can install MoviePy using pip with the command: pip install moviepy.

3. Can I edit videos from other platforms?

Yes, you can edit videos from other platforms as long as you have the video file accessible for editing.

4. What libraries do I need for this project?

You will need Flask, MoviePy, OpenCV, Threading, and Requests to complete this project.

5. How can I handle video processing times?

Using threading can help manage long video processing times, allowing your web server to remain responsive while the task is running in the background.