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70 lines
2.4 KiB
Python
70 lines
2.4 KiB
Python
import numpy as np
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import argparse
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import imutils
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import time
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import cv2
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from imutils.video import VideoStream
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from imutils.video import FPS
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argParse = argparse.ArgumentParser()
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argParse.add_argument("-p", "--prototxt", required=True,
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help="path to Caffe's deploy.prototxt file")
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argParse.add_argument("-m", "--model", required=True,
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help="path to the pretrained Caffe model")
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argParse.add_argument("-c", "--confidence", type=float, default=0.3,
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help="Filtering for detections with weak confidence intervals")
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args = vars(argParse.parse_args())
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features = ["background", "aeroplane", "bicycle", "bird", "boat",
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"bottle", "bus", "car", "cat", "chair", "cow", "diningtable",
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"dog", "horse", "motorbike", "person", "pottedplant", "sheep",
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"sofa", "train", "tvmonitor"]
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colors = np.random.uniform(0, 255, size=(len(features), 3))
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read_net = cv2.dnn.readNetFromCaffe(args["prototxt"], args["model"])
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video_stream = VideoStream(src=0).start()
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time.sleep(2.0)
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frames_per_sec = FPS().start()
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while True:
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frame = video_stream.read()
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frame = imutils.resize(frame, width=600)
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(h, w) = frame.shape[:2]
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blob_from_img = cv2.dnn.blobFromImage(cv2.resize(frame, (300, 300)),
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0.007843, (300, 300), 127.5, swapRB=True)
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read_net.setInput(blob_from_img)
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detect = read_net.forward()
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for i in np.arange(0, detect.shape[2]):
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c_int = detect[0, 0, i, 2]
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if c_int > args["confidence"]:
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c_index = int(detect[0, 0, i, 1])
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box = detect[0, 0, i, 3:7] * np.array([w, h, w, h])
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(startx, starty, endx, endy) = box.astype("int")
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label = "{}: {:.2f}%".format(features[c_index], c_int * 100)
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print("Object detected: ", label)
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cv2.rectangle(frame, (startx, starty), (endx, endy), colors[c_index], 2)
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if starty - 15 > 15:
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y = starty - 15
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else:
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y = starty + 15
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cv2.putText(frame, label, (startx, y), cv2.FONT_HERSHEY_PLAIN, 0.4, colors[c_index], 2)
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cv2.imshow("Frame", frame)
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key = cv2.waitKey(1)
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if key == ord("w"):
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break
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frames_per_sec.update()
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frames_per_sec.stop()
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print("Time elapsed: {:.2f}".format(frames_per_sec.elapsed()))
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print("FPS: {:.2f}".format(frames_per_sec.fps()))
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cv2.destroyAllWindows()
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video_stream.stop()
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