QVideo: Qt framework for video cameras
QVideo is a framework for integrating video cameras into Qt projects (PyQt5, PyQt6, or PySide) for scientific research. It provides a unified, registration-based property system so that every camera backend — USB webcams, GenICam devices, FLIR cameras, Raspberry Pi cameras — is controlled through the same API. Property trees, display widgets, and a digital video recorder are built on top of that abstraction and require no camera-specific code.
Features
- Unified camera API —
QCamerasubclasses expose adjustable parameters viaregisterProperty/registerMethod; UI and recording layers consume them without knowing the underlying hardware. - Auto-built property trees —
QCameraTreereads the registered property map and builds apyqtgraphparameter tree widget automatically. - Threaded video source —
QVideoSourcewraps any camera in aQThreadand emitsnewFrame(ndarray)at acquisition rate. - Composable filter pipeline —
VideoFilter/QFilterBanksit between source and display; filters include blur, edge detection, RGB channel selection, sample-and-hold, binary threshold, and blob coloring. - Graphical overlays —
QTrackpyWidgetfor live particle tracking andQYoloWidgetfor real-time object detection render markers directly onQVideoScreen; composite mode lets the DVR record the annotated scene. - Digital video recorder — lossless HDF5 (with timestamps) and OpenCV
video formats;
QDVRWidgetis the composite UI widget. - Live display —
QVideoScreensupports mouse-aware graphical overlays for annotations, regions of interest, and user interaction.
Installation
pip install QVideo
Qt binding
QVideo works with PyQt5, PyQt6, or PySide. On x86/x86_64 a binding can be installed alongside QVideo:
pip install "QVideo[pyqt6]" # PyQt6
pip install "QVideo[pyqt5]" # PyQt5
Raspberry Pi
PyPI has no prebuilt ARM wheels for PyQt5 or PyQt6, so the system-provided
packages must be used instead. Create the virtual environment with
--system-site-packages so pip can see them:
sudo apt install python3-pyqt6 python3-pyqt6.qtsvg
python3 -m venv --system-site-packages .venv
source .venv/bin/activate
pip install QVideo
Replace python3-pyqt6 with python3-pyqt5 if you prefer PyQt5.
Optional hardware backends
| Backend | Extra | Notes |
|---|---|---|
| GenICam cameras (Vimba, etc.) | pip install QVideo[genicam] |
Requires a vendor-supplied .cti producer file |
| Raspberry Pi camera | pip install QVideo[picamera] |
Requires picamera2 |
Quick start
import pyqtgraph as pg
from QVideo.cameras.Noise import QNoiseSource
from QVideo.lib import QVideoScreen
pg.mkQApp()
source = QNoiseSource() # synthetic noise — no hardware needed
screen = QVideoScreen()
source.newFrame.connect(screen.setImage)
screen.show()
source.start()
pg.exec()
Replace QNoiseSource with QOpenCVSource, QGenicamSource, etc. to switch
hardware — the rest of the code is identical.
Camera backends
| Backend | Class | Hardware |
|---|---|---|
cameras/Noise |
QNoiseCamera |
Synthetic — no hardware required |
cameras/OpenCV |
QOpenCVCamera |
USB webcams via OpenCV |
cameras/Genicam |
QGenicamCamera |
Abstract base for all GenICam/GigE Vision cameras |
cameras/Flir |
QFlirCamera |
FLIR cameras via GenICam (Spinnaker GenTL producer) |
cameras/Basler |
QBaslerCamera |
Basler cameras via GenICam (pylon GenTL producer) |
cameras/IDS |
QIDSCamera |
IDS Imaging cameras via GenICam |
cameras/MV |
QMVCamera |
Any GenICam camera via MATRIX VISION mvGenTLProducer |
cameras/Vimbax |
QVimbaXCamera |
Allied Vision cameras via VimbaX GenTL producer |
cameras/Picamera |
QPicamera |
Raspberry Pi camera module |
Writing a new camera backend
Subclass QCamera and implement three methods:
from QVideo.lib import QCamera
class MyCamera(QCamera):
def _initialize(self) -> bool:
self.device = open_my_hardware()
if not self.device:
return False
self.registerProperty('exposure',
getter=lambda: self.device.get_exposure(),
setter=lambda v: self.device.set_exposure(v),
ptype=float)
return True
def _deinitialize(self) -> None:
self.device.close()
def read(self):
ok, frame = self.device.read_frame()
return ok, frame
QCameraTree and QVideoSource work with MyCamera immediately — no
additional code needed.
Filters
| Filter | Class | Description |
|---|---|---|
| Gaussian blur | QBlurFilter |
Smoothing with adjustable kernel radius |
| Canny edge detection | QEdgeFilter |
Edge map with configurable thresholds |
| RGB channel selection | QRGBFilter |
Pass one or more color channels |
| Sample and hold | QSampleHold |
Background normalization via a sampled median estimate |
| Binary threshold | QThresholdFilter |
Convert to binary mask at a configurable level |
| Blob coloring | QBlobFilter |
Color connected foreground regions with distinct hues |
| YOLO annotation | QYOLOFilter |
Annotate frames with YOLO bounding boxes (requires ultralytics) |
Overlays
Overlays render analysis results directly on the live QVideoScreen and require
pip install QVideo[overlays].
| Overlay | Class | Description |
|---|---|---|
| Particle tracking | QTrackpyWidget |
Live particle detection and tracking using trackpy |
| Object detection | QYoloWidget |
Real-time bounding-box detection using YOLO (ultralytics) |
Acknowledgements
Work on this project at New York University is supported by the National Science Foundation of the United States under award number DMR-2428983 and by an award from the TAC Program of New York University.
1 maintainer
Metadata
1 maintainer
Release files for QVideo 3.18.0
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