"""
Face detection using OpenCV DNN face detector
"""
# Import required packages:
import cv2
import numpy as np
from matplotlib import pyplot as plt
def show_img_with_matplotlib(color_img, title, pos):
"""Shows an image using matplotlib capabilities"""
img_RGB = color_img[:, :, ::-1]
ax = plt.subplot(1, 1, pos)
plt.imshow(img_RGB)
plt.title(title)
plt.axis('off')
# Load pre-trained model:
net = cv2.dnn.readNetFromCaffe("deploy.prototxt", "res10_300x300_ssd_iter_140000_fp16.caffemodel")
# net = cv2.dnn.readNetFromTensorflow("opencv_face_detector_uint8.pb", "opencv_face_detector.pbtxt")
# Load image:
image = cv2.imread("test_face_detection.jpg")
# Get dimensions of the input image (to be used later):
(h, w) = image.shape[:2]
# Create 4-dimensional blob from image:
blob = cv2.dnn.blobFromImage(image, 1.0, (300, 300), [104., 117., 123.], False, False)
# Set the blob as input and obtain the detections:
net.setInput(blob)
detections = net.forward()
# Initialize the number of detected faces counter detected_faces:
detected_faces = 0
# Iterate over all detections:
for i in range(0, detections.shape[2]):
# Get the confidence (probability) of the current detection:
confidence = detections[0, 0, i, 2]
# Only consider detections if confidence is greater than a fixed minimum confidence:
if confidence > 0.7:
# Increment the number of detected faces:
detected_faces += 1
# Get the coordinates of the current detection:
box = detections[0, 0, i, 3:7] * np.array([w, h, w, h])
(startX, startY, endX, endY) = box.astype("int")
# Draw the detection and the confidence:
text = "{:.3f}%".format(confidence * 100)
y = startY - 10 if startY - 10 > 10 else startY + 10
cv2.rectangle(image, (startX, startY), (endX, endY), (255, 0, 0), 3)
cv2.putText(image, text, (startX, y), cv2.FONT_HERSHEY_SIMPLEX, 0.9, (0, 0, 255), 2)
# Create the dimensions of the figure and set title:
fig = plt.figure(figsize=(10, 5))
plt.suptitle("Face detection using OpenCV DNN face detector", fontsize=14, fontweight='bold')
fig.patch.set_facecolor('silver')
# Plot the images:
show_img_with_matplotlib(image, "DNN face detector: " + str(detected_faces), 1)
# Show the Figure:
plt.show()
