嗨,我正在通过使用带有tensorflow的更快的rcnn模型来检测人。在我引用的代码中提到
net = cv2.dnn.readNetFromTensorflow(args["inferencegraph"],args["graphpbtxt"])
以及此后:
detections = net.forward()
我没有得到确切的检测以及检测的内容?例如,它是列表还是元组,它的元素是什么?
[cv2.dnn.readNetFromTensorflow
”将使用您的Protobuf
文件.pb
和模型.pbtxt
的配置文件来加载保存的模型。
net.forward()
-运行前向通过以计算净输出。
您的检测,即net.forward()
将给出Numpy ndarray
作为输出,您可以用它在给定的输入图像上绘制框。
您可以考虑以下示例。
import cv2
# Load a model imported from Tensorflow
tensorflowNet = cv2.dnn.readNetFromTensorflow('frozen_inference_graph.pb', 'graph.pbtxt')
# Input image
img = cv2.imread('img.jpg')
rows, cols, channels = img.shape
# Use the given image as input, which needs to be blob(s).
tensorflowNet.setInput(cv2.dnn.blobFromImage(img, size=(300, 300), swapRB=True, crop=False))
# Runs a forward pass to compute the net output
networkOutput = tensorflowNet.forward()
# Loop on the outputs
for detection in networkOutput[0,0]:
score = float(detection[2])
if score > 0.2:
left = detection[3] * cols
top = detection[4] * rows
right = detection[5] * cols
bottom = detection[6] * rows
#draw a red rectangle around detected objects
cv2.rectangle(img, (int(left), int(top)), (int(right), int(bottom)), (0, 0, 255), thickness=2)
# Show the image with a rectagle surrounding the detected objects
cv2.imshow('Image', img)
cv2.waitKey()
cv2.destroyAllWindows()