OmniView is an advanced video viewing and recording application that offers a range of features including real-time object detection and screenshot capturing. This project uses the OpenCV library for camera connection and video processing, ensuring smooth and high-quality video streams. By integrating the Darknet API, OmniView provides sophisticated object detection capabilities, enabling real-time identification and tracking of various objects within the video feed.
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Camera Detection 📷: Automatically identifies and lists connected cameras. This feature utilizes OpenCV to scan for all available video devices and adds the detected cameras to a list for user selection, eliminating the need for manual device searching.
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Live Stream Viewing 📺: View live video feed from your selected camera in real-time. The application uses Tkinter and OpenCV to display the video feed directly within the user interface, allowing users to monitor the camera feed seamlessly.
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Video Recording 🎥: Record video streams to a file with just a click. The recording can be started and stopped at any time, and the resulting video file is saved for later viewing or analysis. The application uses the XVID codec for recording, with automatic settings for frame rate and resolution.
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Object Detection 🕵️♂️: Leverages the YOLOv3 model for detecting objects within the video stream in real-time. This model highlights various types of objects (e.g., people, cars, animals) and displays them with corresponding labels and confidence levels, making it easier to identify and track objects in the frame.
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Screenshot Capture 📸: Take high-quality screenshots and save them in your desired folder. This feature is ideal for capturing important moments or using the frames for further analysis. The application automatically creates a folder in the user's home directory for storing screenshots if it doesn't already exist.
To get started with OmniView, follow these steps:
- Ensure you have Python 3.10 or higher installed.
- Clone the repository:
git clone https://github.com/Solrikk/OmniView.git cd OmniView - Install dependencies using Poetry:
poetry install
Follow these simple steps to use OmniView:
- Launch the application:
poetry run python main.py
- Select a camera from the provided list and click "View Camera" to start the live feed.
- Utilize the buttons available to start or stop video recording, take screenshots, and enable object detection.
OmniView relies on the following libraries and tools:
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Python 3.10 and above: The application requires Python 3.10 or higher to leverage the latest language features and maintain compatibility with modern libraries.
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tkinter: For constructing the user interface. tkinter is the built-in GUI toolkit for Python, which provides a simple way to create windows, dialogs, buttons, and other user interface elements.
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OpenCV: To manage camera connections and process video streams. OpenCV is an open-source computer vision and machine learning software library, widely used for real-time computer vision applications. It facilitates capturing video from cameras, video files, and even network streams.
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NumPy: Essential for handling data arrays. NumPy is a fundamental package for scientific computing in Python, offering powerful array processing capabilities. It is extensively used in handling image data and performing mathematical operations required in object detection.
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Pillow: Used for image processing tasks. Pillow is the Python Imaging Library (PIL) fork, which adds easy-to-use image processing capabilities to your Python interpreter. It enables opening, manipulating, and saving many different image file formats.
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Poetry: Manages project dependencies efficiently. Poetry is a tool for dependency management and packaging in Python. It helps to declare project libraries, ensures that dependencies are compatible with each other, and simplifies virtual environment creation and activation.