You have no ring light.
Here is a complete, modular Python script. You can copy this class directly into your features folder.
import cv2
import numpy as np
class XProEffects:
def init(self):
# Load a pre-trained Deep Learning model for face detection
# We use the DNN Face Detector as it's fast and accurate
self.net = cv2.dnn.readNetFromCaffe("deploy.prototxt", "res10_300x300_ssd_iter_140000.caffemodel") xpro webcam software
# Settings
self.blur_strength = 35
self.detection_confidence = 0.7
def apply_portrait_mode(self, frame):
"""
Detects faces, creates a mask, and blurs the background.
"""
(h, w) = frame.shape[:2]
# 1. Create a blob from the image (pre-processing for AI)
blob = cv2.dnn.blobFromImage(cv2.resize(frame, (300, 300)), 1.0,
(300, 300), (104.0, 177.0, 123.0))
# 2. Pass blob through the network to detect faces
self.net.setInput(blob)
detections = self.net.forward()
# 3. Create a mask: Black background (0), White foreground (255)
mask = np.zeros((h, w), dtype="uint8")
for i in range(0, detections.shape[2]):
confidence = detections[0, 0, i, 2]
# Filter out weak detections
if confidence > self.detection_confidence:
# Compute the bounding box coordinates
box = detections[0, 0, i, 3:7] * np.array([w, h, w, h])
(startX, startY, endX, endY) = box.astype("int")
# Ensure box is within frame bounds
startX, startY = max(0, startX), max(0, startY)
endX, endY = min(w - 1, endX), min(h - 1, endY)
# Draw a white filled circle/ellipse on the mask to represent the focus area
# (We slightly expand the box to include hair/shoulders)
center = ((startX + endX) // 2, (startY + endY) // 2)
axes_length = (int((endX - startX) * 0.7), int((endY - startY) * 1.2))
cv2.ellipse(mask, center, axes_length, 0, 0, 360, 255, -1)
# 4. Blur the entire frame
blurred_background = cv2.GaussianBlur(frame, (self.blur_strength, self.blur_strength), 0)
# 5. Combine the sharp foreground and blurred background using the mask
# We need to invert the mask for the background
mask_inv = cv2.bitwise_not(mask)
# Extract the sharp person
foreground = cv2.bitwise_and(frame, frame, mask=mask)
# Extract the blurred background
background = cv2.bitwise_and(blurred_background, blurred_background, mask=mask_inv)
# Merge them
final_output = cv2.add(foreground, background)
return final_output
One of the biggest frustrations with auto-settings is the "flicker" effect. When you move slightly, the camera tries to re-adjust the exposure, causing a distracting strobe effect. XPro software allows you to lock these settings. You can manually set shutter speed, gain, and white balance (Kelvin temperature) to a fixed level.
Getting the software running is straightforward, but users often download the wrong driver version. Follow this guide precisely. You have no ring light
Step 1: Identify Your Model
Flip your webcam over. Look for the model number (e.g., XPro XC-4K, XPro StreamCam 1080, or XPro WC-02). Do not download software meant for a different chipset (like Sonix or Realtek), as it may brick the device.
Step 2: Download from the Right Source
Go to the official XPro support portal (usually listed on the box or manual). Avoid third-party driver sites that bundle adware. The file is typically named XPro_Webcam_Setup_v2.4.exe or similar. One of the biggest frustrations with auto-settings is
Step 3: Disable Antivirus Temporarily
Some XPro drivers utilize low-level USB hooks that false-positive as threats. Pause Windows Defender or your AV (just during install) to prevent the driver signature from being blocked.
Step 4: Run the Installer
Run as Administrator.
Step 5: Restart
Reboot your PC. Upon restart, you should see the XPro Control Panel icon in your system tray (bottom right).
XPro Webcam Software is a webcam management and streaming utility for Windows and macOS that handles webcam capture, virtual camera output, background replacement, filters, recording, and streaming to platforms like Zoom, OBS, and Teams. (Assuming Windows 10/11; adjust settings similarly on macOS.)