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效果

代码 

import cv2

modelFile = "res10_300x300_ssd_iter_140000_fp16.caffemodel"
configFile = "deploy.prototxt"
conf_threshold = 0.7

net = cv2.dnn.readNetFromCaffe(configFile, modelFile)
net.setPreferableBackend(cv2.dnn.DNN_TARGET_CPU)

img = cv2.imread('3.jpg', cv2.IMREAD_UNCHANGED)

frameHeight = img.shape[0]
frameWidth = img.shape[1]

blob = cv2.dnn.blobFromImage(img, 1.0, (300, 300), [104, 117, 123], False, False)

net.setInput(blob)
detections = net.forward()

for i in range(detections.shape[2]):
    confidence = detections[0, 0, i, 2]
    if confidence > conf_threshold:
        x1 = int(detections[0, 0, i, 3] * frameWidth)
        y1 = int(detections[0, 0, i, 4] * frameHeight)
        x2 = int(detections[0, 0, i, 5] * frameWidth)
        y2 = int(detections[0, 0, i, 6] * frameHeight)

        cv2.rectangle(
            img,
            (x1, y1),
            (x2, y2),
            (0, 255, 0),
            2,
        )

cv2.imshow("Face Detection Comparison", img)

cv2.waitKey()
cv2.destroyAllWindows()
 

import cv2

modelFile = "res10_300x300_ssd_iter_140000_fp16.caffemodel"
configFile = "deploy.prototxt"
conf_threshold = 0.7

net = cv2.dnn.readNetFromCaffe(configFile, modelFile)
net.setPreferableBackend(cv2.dnn.DNN_TARGET_CPU)

img = cv2.imread('3.jpg', cv2.IMREAD_UNCHANGED)

frameHeight = img.shape[0]
frameWidth = img.shape[1]

blob = cv2.dnn.blobFromImage(img, 1.0, (300, 300), [104, 117, 123], False, False)

net.setInput(blob)
detections = net.forward()

for i in range(detections.shape[2]):
    confidence = detections[0, 0, i, 2]
    if confidence > conf_threshold:
        x1 = int(detections[0, 0, i, 3] * frameWidth)
        y1 = int(detections[0, 0, i, 4] * frameHeight)
        x2 = int(detections[0, 0, i, 5] * frameWidth)
        y2 = int(detections[0, 0, i, 6] * frameHeight)

        cv2.rectangle(
            img,
            (x1, y1),
            (x2, y2),
            (0, 255, 0),
            2,
        )

cv2.imshow("Face Detection Comparison", img)

cv2.waitKey()
cv2.destroyAllWindows()

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