Главная
Study mode:
on
1
Introduction
2
Generating Faces
3
Prototype Seeds
4
Latent vectors
5
Morph step
6
Randomness
7
Running FFMPEG
8
Results
9
Putting Images Together
10
Basic Example
11
Uploading Longer Videos
12
Execute Command
13
Run FFMPEG
14
Output
15
Input
16
Output Quality
17
Extracting Audio
18
Syncing Audio
19
Running Process
20
Demonstration
21
Ball Speed
22
File Setup
23
Modifying Images
24
Building the Video File
25
File Names
26
File Download
27
Demo
28
Modifications
29
Yolo
30
Collab
31
Fixing Hardcoded Video
32
Yolo Eve
33
Tensorflow
34
Virtual Machine
35
Yellow Waits
36
Set Up Yellow
37
Time Formatter
38
Process Image
39
Fast Forward
40
Build Video File
41
Final Output
Description:
Learn how to use FFMPEG for video encoding and decoding in machine learning applications. This 21-minute tutorial demonstrates techniques for processing individual video frames, generating new videos, and converting between formats like MP4/MOV and JPEG images. Explore three Jupyter notebooks covering topics such as generating faces, prototyping seeds, latent vectors, morphing, randomness, and syncing audio. Discover how to modify images, build video files, and implement YOLO object detection. Gain practical insights into file setup, virtual machine configuration, and optimizing output quality for offline video-based machine learning projects.

Using FFMPEG to Encode-Decode Video for Offline Video-Based Machine Learning

Jeff Heaton
Add to list