Camera Viewer Application

This Python application uses OpenCV and PyQt5 to display video streams from two cameras in a graphical user interface (GUI).

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Table of Contents

• Description
• Features
• Prerequisites
• Installation
• Usage
• Configuration
• Code Explanation
• Troubleshooting
• License

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Description

The application captures video streams from two cameras (specified by RTSP URLs), processes the frames in separate threads, and displays the live video feeds side by side in a GUI window.

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Features

• Multithreaded Video Capture: Efficiently captures frames from multiple cameras using separate threads.
• Real-Time Display: Shows live video feeds from two cameras simultaneously.
• PyQt5 GUI: Utilizes PyQt5 for a responsive and customizable graphical user interface.
• Graceful Exit: Closes the application smoothly when the Q key is pressed.

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Prerequisites

• Python 3.x
• OpenCV (opencv-python)
• PyQt5

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Installation

Clone or Download the Repository

Clone the repository or download the script to your local machine.

Install Required Packages

Install the necessary Python packages using pip:

pip install opencv-python PyQt5

Alternatively, use the provided requirements.txt file:

pip install -r requirements.txt

requirements.txt content:

opencv-python
PyQt5

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Usage

Update RTSP URLs

Replace the RTSP URLs in the script with your camera stream URLs:

thread1 = ThreadedCamera("rtsp://your_camera_ip:port/stream1", frame_queue1)
thread2 = ThreadedCamera("rtsp://your_camera_ip:port/stream2", frame_queue2)

Run the Script

Execute the script using Python:

python your_script_name.py

View the Streams

• A GUI window titled "Camera View" will open.
• Live video feeds from the two cameras will be displayed side by side.

Exit the Application

Press the Q key to close the application gracefully.

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Configuration

Adjust Queue Size

The queues for frame storage have a maximum size of 10. You can modify this if needed:

frame_queue1 = queue.Queue(10)

Modify Display Size

To change the display size of the video feeds, adjust the scaling in the display_image method:

p = convert_to_Qt_format.scaled(width, height, QtCore.Qt.KeepAspectRatio)

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Code Explanation

1. ThreadedCamera Class

• Purpose: Captures video frames from a camera stream in a separate thread.
• Key Methods:
  • __init__: Initializes the thread with the camera ID and frame queue.
  • run: Continuously reads frames from the camera and places them into the queue.

2. App Class

• Purpose: Creates the GUI window and displays the video feeds.
• Key Methods:
  • __init__: Initializes the GUI components.
  • init_ui: Sets up the layout, labels, and timers for updating images.
  • update_image1 & update_image2: Retrieve frames from the queues and display them.
  • display_image: Converts OpenCV images to Qt format and updates the labels.
  • keyPressEvent: Handles key press events to close the application.

3. Main Execution Block

• Creates Frame Queues: For thread-safe communication between capture threads and the GUI.
• Initializes the GUI Application: Sets up the PyQt5 application and displays the window.
• Starts Camera Threads: Begins capturing video from the specified RTSP URLs.
• Runs the Event Loop: Keeps the application running until exited.

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Troubleshooting

Video Stream Not Displaying

• Ensure the RTSP URLs are correct and accessible.
• Check network connectivity to the camera streams.

ModuleNotFoundError

• Verify that all required packages are installed.
• Use the pip install commands provided in the Installation section.

Application Freezes or Crashes

• Reduce the frame queue size if memory consumption is high.
• Ensure your system meets the hardware requirements for video processing.

PyQt5 Compatibility Issues

• Make sure PyQt5 is compatible with your Python version.
• Consider creating a virtual environment to manage dependencies.

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License

This project is open-source and available under the MIT License.