Install DXcam, create a camera, and call grab() to capture a screen frame as a NumPy array. DXcam is a Windows capture library: its project documentation describes Desktop Duplication (DXGI) as the default backend and recommends starting there for most workloads. A one-shot capture is different from DXcam’s threaded, buffered mode for continuous frame streams.
Take a one-shot screenshot
Install DXcam in the Python environment that will run your script:
python -m pip install dxcamThen create a camera, grab the current frame, and let the context manager release the capture resource:
import dxcam
with dxcam.create() as camera:
frame = camera.grab()
if frame is None:
print("No new frame was available")
else:
print(type(frame), frame.shape, frame.dtype)The returned frame is a NumPy array, not a filename or an image displayed in a window. DXcam’s documentation notes that grab() can return None if no new frame has been available since the preceding capture. For a script that needs a frame even when the display has not changed, call grab(new_frame_only=False).
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The context manager is the concise cleanup pattern documented by the project. If you manage the camera without it, call camera.release() when finished. Release stops capture and frees buffers and resources; a released camera instance cannot be reused.
Save the frame as an image
DXcam returns pixels in memory. To write a PNG file, install Pillow and save the array. This example uses DXcam’s RGB output setting so the channel order matches what Pillow expects:
python -m pip install "dxcam[cv2]" pillowimport dxcam
from PIL import Image
with dxcam.create(output_color="RGB") as camera:
frame = camera.grab(new_frame_only=False)
if frame is None:
raise RuntimeError("DXcam did not return a frame")
Image.fromarray(frame).save("screenshot.png")For other output modes, verify the channel order expected by the library that consumes the array. DXcam documents RGB, RGBA, BGR, BGRA, and GRAY output. An array with BGR channels, for example, should not be treated as RGB without conversion or the colors will be wrong. OpenCV pipelines often use BGR; image display and save libraries may expect RGB or RGBA.
The project documents BGRA as the leanest dependency path. Other color conversion modes require OpenCV or the compiled NumPy processor path, according to the README. The optional cv2 extra installs OpenCV support. Install winrt as well if you intend to use that backend:
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python -m pip install "dxcam[cv2,winrt]"Capture only part of the screen
Pass region=(left, top, right, bottom) to grab(). These are the rectangle’s boundary coordinates—not an origin followed by width and height.
import dxcam
with dxcam.create() as camera:
frame = camera.grab(region=(100, 80, 740, 720))
if frame is None:
raise RuntimeError("No frame was available")
print(frame.shape)The rectangle above begins at horizontal coordinate 100 and vertical coordinate 80, and ends at 740 and 720. It therefore describes a 640-by-640 area. The coordinates refer to the capture output; check the target output’s dimensions before choosing boundaries, particularly if you are capturing a different monitor or output.
Choose between a still capture and a frame stream
Use grab() when the task is to take a still image on demand. Use start(), get_latest_frame(), and stop() when a computer-vision or video workflow needs repeated frames. The continuous mode runs a capture thread and keeps frames in an in-memory ring buffer.
import time
import dxcam
camera = dxcam.create()
camera.start(region=(100, 80, 740, 720), target_fps=60)
try:
for _ in range(10):
frame = camera.get_latest_frame()
if frame is not None:
# Process the NumPy array here.
print(frame.shape)
time.sleep(1 / 60)
finally:
camera.stop()
camera.release()This example asks DXcam to capture at a target rate of 60 frames per second, but the actual capture cadence depends on the machine and workload. Retrieve and process frames at a rate appropriate to the application; the in-memory ring buffer is not a way to persist every frame indefinitely.
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With video_mode=True, the documented behavior is to fill the buffer at the requested target frame rate and reuse the previous frame when the display has not rendered a new one. That can be useful for a paced video or ML loop that needs a frame on each interval. It is not the same as asking whether a fresh screen update exists: for one-shot capture, the new_frame_only behavior is the relevant choice.
Select a backend and output
DXcam documents two backends: dxgi, based on Desktop Duplication and used by default, and winrt, based on Windows Graphics Capture. The project recommends beginning with DXGI for most workloads, especially one-shot grabs, and trying WinRT if cursor rendering is needed or if it better fits the application’s constraints. There is no documented universal winner across every Windows machine and application.
Backend behavior and suitability can depend on the target application and system. If DXGI does not fit your cursor or application requirements, try the documented WinRT backend with the optional dependency installed, then check the result in the actual workflow:
import dxcam
camera = dxcam.create(backend="winrt")
try:
frame = camera.grab(new_frame_only=False)
finally:
camera.release()The project associates each output or monitor with a camera instance and demonstrates choosing device and output indices for multi-monitor or multi-GPU systems. If capture appears to come from the wrong display, inspect the available device/output choices in the version of DXcam you installed and select the intended indices rather than assuming the primary monitor is the target.
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Installation and compatibility notes
DXcam’s project listing documents Python 3.10 or newer and Windows classifiers. Its README says official Windows wheels are built for CPython 3.10 through 3.14. Those are project-maintained compatibility details that can change as releases evolve; if installation fails on a newer Python release or a nonstandard interpreter, check the package’s current installation metadata and available wheels.
The minimal installation is python -m pip install dxcam. Add optional extras only for the features you need: cv2 for OpenCV-based color conversion, and winrt for Windows Graphics Capture support. Keeping the dependencies minimal can avoid installing image-processing or backend packages your script will not use.
Troubleshoot common capture problems
ModuleNotFoundError: No module named 'dxcam': Install DXcam into the same interpreter or virtual environment used to run the script. Usingpython -m pip install dxcamties pip to the named Python executable.grab()returnsNone: The API may have no new frame since the previous capture. If the script needs the latest screen contents regardless of whether they changed, callgrab(new_frame_only=False)and still check forNonebefore processing.- The saved image has unexpected colors: Check
output_colorand the consumer’s expected channel order. Convert or request RGB for a Pillow-style image path, or use the channel ordering expected by an OpenCV pipeline. - The captured rectangle is shifted or has unexpected dimensions: DXcam’s region tuple is
(left, top, right, bottom). It is not(x, y, width, height); compute the right and bottom boundaries and ensure they fall within the intended output. - Cursor or application compatibility is unsuitable: DXGI is the default starting point. If cursor rendering is required or DXGI does not suit the application, install the WinRT extra and try
backend="winrt"on the target system. - Capture fails after cleanup: A released camera instance is not reusable. Create a new camera for a later capture, or keep the original instance active until its work is complete.
- Continuous capture does not behave like a one-shot read: The threaded mode maintains an in-memory ring buffer. Use
grab()for an on-demand still, and callstop()when the stream is done.
Performance, reliability, and cost considerations
DXcam describes itself as a high-performance Python screenshot and capture library for Windows based on Desktop Duplication. The project README, updated in 2026, states “240+fps on 1080p.” That is the project’s own claim, not an independently established benchmark or a guaranteed rate for a particular PC, output, backend, or workload. Treat throughput as something to measure in the capture and processing pipeline you plan to run.
For reliability, handle absent frames, clean up camera resources, and test the selected monitor, backend, and color mode in the actual target application. Still captures and continuous capture have different behavior and resource use: a stream runs a capture thread and buffers frames in memory, while a one-shot call is simpler when only a single frame is required. DXcam is software distributed through pip; there is no separate hardware purchase required by the documented capture method.
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Frequently Asked Questions
Can DXcam capture a screenshot on macOS or Linux?
The documented package targets Windows. Use a capture library appropriate to the operating system if your script must run on macOS or Linux.
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Does DXcam return a screenshot file?
No. It returns a NumPy array; use an image library such as Pillow to save the pixels to a file.
Can DXcam capture more than one monitor?
The project documents selecting device and output indices and associates outputs with camera instances. Select the indices corresponding to the monitor you intend to capture.
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