Object detection sample in Python

object_detection.py

cap = VideoCapture(webcam_url)
model = cv2.dnn.readNetFromTensorflow('models/frozen_inference_graph.pb',
                                      'models/ssd_mobilenet_v2_coco_2018_03_29.pbtxt')
# Get a frame
frame = cap.read()

# Submit it to model
model.setInput(cv2.dnn.blobFromImage(frame, size=(300, 300), swapRB=True))
output = model.forward()

# List detected object
for detection in output[0, 0, :, :]:
    confidence = detection[2]
    if confidence > .5:
        class_id = detection[1]
        class_name=id_class_name(class_id,classNames)
        print(str(str(class_id) + " " + str(detection[2])  + " " + class_name))