Create a simple face recognition program.
Here is a simple face recognition program using the OpenCV library in Python:

```python
import cv2

# Load the pre-trained cascade classifier
face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + "haarcascade_frontalface_default.xml")

# Access the default webcam
cap = cv2.VideoCapture(0)

# Infinite loop
while True:
    # Read the frame
    _, frame = cap.read()
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    # Detect faces
    faces = face_cascade.detectMultiScale(gray, 1.1, 4)

    # Draw a rectangle around each detected face
    for (x, y, w, h) in faces:
        cv2.rectangle(frame, (x, y), (x+w, y+h), (255, 0, 0), 2)

    # Show the frame with the rectangle around the face
    cv2.imshow("Face Detection", frame)
    
    # Use the key 'q' to quit the video feed 
    if cv2.waitKey(1) == ord('q'):
        break

# Release the webcam
cap.release()
cv2.destroyAllWindows()
```
This program captures video from the default webcam, detects faces using a pre-trained Haar Cascade classifier, and draws rectangles around the detected faces. The program runs in an infinite loop and can be stopped by pressing the key 'q'.
Below is an instruction that describes a task, write a response that appropriately completes the request.

### Instruction:
Create a simple face recognition program.

### Response:
Here is a simple face recognition program using the OpenCV library in Python:

```python
import cv2

# Load the pre-trained cascade classifier
face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + "haarcascade_frontalface_default.xml")

# Access the default webcam
cap = cv2.VideoCapture(0)

# Infinite loop
while True:
    # Read the frame
    _, frame = cap.read()
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    # Detect faces
    faces = face_cascade.detectMultiScale(gray, 1.1, 4)

    # Draw a rectangle around each detected face
    for (x, y, w, h) in faces:
        cv2.rectangle(frame, (x, y), (x+w, y+h), (255, 0, 0), 2)

    # Show the frame with the rectangle around the face
    cv2.imshow("Face Detection", frame)
    
    # Use the key 'q' to quit the video feed 
    if cv2.waitKey(1) == ord('q'):
        break

# Release the webcam
cap.release()
cv2.destroyAllWindows()
```
This program captures video from the default webcam, detects faces using a pre-trained Haar Cascade classifier, and draws rectangles around the detected faces. The program runs in an infinite loop and can be stopped by pressing the key 'q'.