For this lab you will implement a trivial producer-consumer system using python threads where all coordination is managed by counting and binary semaphores for a system of two producers and two consumers. The producers and consumers will form a simple rendering pipeline using multiple threads. One thread will read frames from a file, a second thread will take those frames and convert them to grayscale, and the third thread will display those frames. The threads will run concurrently.
In order to run this lab opencv will need to be installed. In April 2024, these commands successfully installed it. You can cut-and-paste them from README.md, or just run the script install-opencv-0424.sh.
sudo apt-get update
sudo apt-get install libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev libgstreamer-plugins-bad1.0-dev gstreamer1.0-plugins-base gstreamer1.0-plugins-good gstreamer1.0-plugins-bad gstreamer1.0-plugins-ugly gstreamer1.0-libav gstreamer1.0-tools gstreamer1.0-x gstreamer1.0-alsa gstreamer1.0-gl gstreamer1.0-gtk3 gstreamer1.0-qt5 gstreamer1.0-pulseaudio
sudo apt-get install ffmpeg
sudo apt-get install python3-numpy
sudo apt-get install python3-pip
sudo pip install opencv-python
These commands worked a few years ago in the arch vm:
sudo zypper -n install python3-devel
sudo zypper -n install ffmpeg ffmpeg-3
sudo zypper -n install gstreamer gstreamer-devel
sudo zypper -n install python3-numpy
sudo pip install --upgrade pip
sudo pip install opencv-python
The purpose of this lab is to implement and use a producer-consumer system. Python already has several synchronized bounded buffers and queues available as libraries. You may not use any of these as they would prevent you from demonstrating the knowledge you've gained. The only threading/synchronization objects or methods you may use are mutexes and semaphores (we suggest using the threads api).
Extracts a series of frames from the video contained in 'clip.mp4' and saves them as jpeg images in sequentially numbered files with the pattern 'frame_xxxx.jpg'.
Loads a series for frams from sequentially numbered files with the pattern 'frame_xxxx.jpg', converts the grames to grayscale, and saves them as jpeg images with the file names 'grayscale_xxxx.jpg'
Loads a series of frames sequently from files with the names 'grayscale_xxxx.jpg' and displays them with a 42ms delay.
Loads a series of framss from a video contained in 'clip.mp4' and displays them with a 42ms delay
- Extract frames from a video file, convert them to grayscale, and display them in sequence
- You must have three functions
- One function to extract the frames
- One function to convert the frames to grayscale
- One function to display the frames at the original framerate (24fps)
- The functions must each execute within their own python thread
- The threads will execute concurrently
- The order threads execute in may not be the same from run to run
- Threads will need to signal that they have completed their task
- Threads must process all frames of the video exactly once
- Frames will be communicated between threads using producer/consumer idioms
- Producer/consumer qeueus must be bounded at ten frames
Note: You may have ancillary objects and method in order to make you're code easer to understand and implement.
$ sudo apt-get install python3-opencv
$ sudo pip install opencv-python