General FAQs⚓

"I'm new to Python Programming or its usage in OpenCV Library", How to use vidgear in my projects?⚓

Answer: Before using vidgear, It's recommended to first go through the following dedicated blog sites and learn how OpenCV-Python syntax works (with examples):

PyImageSearch.com ➶ is the best resource for learning OpenCV and its Python implementation. Adrian Rosebrock provides many practical OpenCV techniques with tutorials, code examples, blogs, and books at PyImageSearch.com. Highly recommended!
learnopencv.com ➶ Maintained by OpenCV CEO Satya Mallick. This blog is for programmers, hackers, engineers, scientists, students, and self-starters interested in Computer Vision and Machine Learning.
There's also the official OpenCV Tutorials ➶ curated by the OpenCV developers.

Once done, visit Switching from OpenCV ➶ to easily replace OpenCV APIs with suitable Gears ➶ in your project. All the best!

If you run into any trouble or have any questions, then refer our Help section.

"VidGear is using Multi-threading, but Python is notorious for its poor performance in multithreading?"⚓

Answer: Refer vidgear's Threaded-Queue-Mode ➶

ModuleNotFoundError: No module named 'vidgear.gears'. 'vidgear' is not a package?⚓

Answer: This error means you either have a file named vidgear.py in your python path or you've named your python script vidgear.py. Replace vidgear name with anything else to fix this error.

How to log to a file in VidGear?⚓

Answer: VidGear provides exclusive VIDGEAR_LOGFILE environment variable to enable logging to a file while logging is enabled (i.e. logging=True) on respective Gear. You just have to set directory pathname (automatically creates vidgear.log file) or a log file pathname itself as value for this environment variable. This can be done on various platfroms/OSes as follows:

Remember enabling this logging to a file will completely disable any output on the terminal.

Linux OSWindows OS (Powershell)OSX/Mac OS

# path to file
export VIDGEAR_LOGFILE="$HOME/foo.log"

# or just directory path 
# !!! Make sure `foo` path already exists !!!
export VIDGEAR_LOGFILE="$HOME/foo"

# to remove
unset VIDGEAR_LOGFILE

# path to file
$Env:VIDGEAR_LOGFILE = "D:\foo.log"

# or just directory path 
# !!! Make sure `foo` path already exists !!!
$Env:VIDGEAR_LOGFILE = "D:\foo"

# to remove
$Env:VIDGEAR_LOGFILE = ""

# path to file
export VIDGEAR_LOGFILE="$HOME/foo.log"

# or just directory path 
# !!! Make sure `foo` path already exists !!!
export VIDGEAR_LOGFILE="$HOME/foo"

# to remove
unset VIDGEAR_LOGFILE

Can I perform Deep Learning task with VidGear?⚓

Answer: VidGear is a powerful Video Processing library (similar to OpenCV, FFmpeg, etc.) that can read, write, process, send & receive a sequence of video-frames in an optimized manner. But for Deep Learning or Machine Learning tasks, you have to use a third-party library. That being said, all VidGear's APIs can be used with any third-party Library(such as PyTorch, Tensorflow, etc.) that can leverage the overall performance if you're processing video/audio streams/frames in your application with Deep Learning tasks. Also, it eases the workflow since you have to write way fewer lines of code to read/store/process output videos.