使用OpenCV和Python生成电影条形码

原文链接：https://www.pyimagesearch.com/2017/01/16/generating-movie-barcodes-with-opencv-and-python/

|--- output/
|--- videos/
|--- count_frames.py
|--- generate_barcode.py
|--- visualize_barcode.py

# import the necessary packages
from imutils.video import count_frames
import argparse
import os

# construct the argument parse and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-v", "--video", required=True,
  help="path to input video file")
ap.add_argument("-o", "--override", type=int, default=-1,
  help="whether to force manual frame count")
args = vars(ap.parse_args())
# count the total number of frames in the video file
override = False if args["override"] < 0 else True
total = count_frames(args["video"], override=override)

# display the frame count to the terminal
print("[INFO] {:,} total frames read from {}".format(total,
  args["video"][args["video"].rfind(os.path.sep) + 1:]))

# import the necessary packages
import argparse
import json
import cv2
# construct the argument parse and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-v", "--video", required=True,
  help="path to input video")
ap.add_argument("-o", "--output", required=True,
  help="path to output JSON file containing frame averages")
ap.add_argument("-s", "--skip", type=int, default=0,
  help="# of frames to skip (to create shorter barcodes)")
args = vars(ap.parse_args())

# initialize the list of frame averages along with the total
# number of frames read
avgs = []
total = 0
# grab a pointer to the video file
print("[INFO] looping over frames in video (this will take awhile)...")
video = cv2.VideoCapture(args["video"])

# loop over the frames of the video
while True:
  # grab the current frame
  (grabbed, frame) = video.read()
 
  # check to see if we have reached the end of the
  # video
  if not grabbed:
    break
  # increment the total number of frames read
  total += 1
  # check to see if we should compute the average RGB value
  # of the current frame
  if args["skip"] == 0 or total % args["skip"] == 0:
    avg = cv2.mean(frame)[:3]
    avgs.append(avg)
# release the video pointer
video.release()

# dump the frame averages to file
print("[INFO] saving frame averages...")
f = open(args["output"], "w")
f.write(json.dumps(avgs))
f.close()
print("[INFO] {:,} total frame averages saved".format(len(avgs)))

# import the necessary packages
import numpy as np
import argparse
import json
import cv2
# construct the argument parse and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-a", "--avgs", required=True,
  help="path to averages JSON file")
ap.add_argument("-b", "--barcode", required=True,
  help="path to output barcode visualization image")
ap.add_argument("-t", "--height", type=int, default=250,
  help="height of output barcode image")
ap.add_argument("-w", "--barcode-width", type=int, default=1,
  help="width of each bar in output image")
args = vars(ap.parse_args())

# load the averages file and convert it to a NumPy array
avgs = json.loads(open(args["avgs"]).read())
avgs = np.array(avgs, dtype="int")
# grab the individual bar width and allocate memory for
# the barcode visualization
bw = args["barcode_width"]
barcode = np.zeros((args["height"], len(avgs) * bw, 3),dtype="uint8")
# loop over the averages and create a single 'bar' for
# each frame average in the list
for (i, avg) in enumerate(avgs):
  cv2.rectangle(barcode, (i * bw, 0), ((i + 1) * bw,
    args["height"]), avg, -1)
# write the video barcode visualization to file and then
# display it to our screen
cv2.imwrite(args["barcode"], barcode)
cv2.imshow("Barcode", barcode)
cv2.waitKey(0)

$ python generate_barcode.py --video videos/jurassic_park_trailer.mp4 
  --output output/jurassic_park_trailer.json --skip 25
$ python visualize_barcode.py --avgs output/jurassic_park_trailer.json 
  --barcode output/jurassic_park_trailer.png --barcode-width 5