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#######################
## imports
import cv2
import numpy as np
import os
import sys
import time
import matplotlib.pyplot as plt
## Load in video, resized from Professor Zuckers helped notebook resize_video.ipynb
def get_num_frames(input_filename):
cap = cv2.VideoCapture(input_filename)
# try the fast way
nframes = cap.get(cv2.CAP_PROP_FRAME_COUNT)
width = cap.get(cv2.CAP_PROP_FRAME_WIDTH)
height = cap.get(cv2.CAP_PROP_FRAME_HEIGHT)
fps = cap.get(cv2.CAP_PROP_FPS)
if not fps > 1:
# fps buggy sometimes
fps = 30.0
if nframes > 1 and width > 1 and height > 1:
# it worked
return int(nframes), int(width), int(height), fps
# the slow way
cnt = 0
while True:
ok, frame = cap.read()
if not ok or frame is None:
break
height, width = frame.shape[:2]
cnt += 1
return cnt, width, height, fps
if not os.path.exists(input_filename):
print('error:', input_filename, 'does not exist')
sys.exit(1)
# Create the output video
path_prefix, basename = os.path.split(input_filename)
basename, _ = os.path.splitext(basename)
# Get video properties
nframes, width, height, fps = get_num_frames(input_filename)
# Create output writer
fourcc, ext = (cv2.VideoWriter_fourcc('m', 'p', '4', 'v'), 'mp4')
output_filename = os.path.join(path_prefix, basename + '_tracked.' + ext)
writer = cv2.VideoWriter(output_filename, fourcc, fps, (width, height))
# Write out frames
accum = np.zeros((height, width,3), dtype=np.float32)
cnt = 0
cap = cv2.VideoCapture(input_filename)
frames = []
for frame_idx in range(nframes):
ok, frame = cap.read()
if not ok or frame is None:
break
frames.append(frame)
frame_idx += 1
accum += frame.astype(np.float32)
cnt += 1
### background generation (temporal averaging)
img_ref = np.clip(accum/cnt, 0, 255).astype(np.uint8)
plt.imshow(cv2.cvtColor(img_ref, cv2.COLOR_BGR2RGB))
Out[ ]:
<matplotlib.image.AxesImage at 0x7fb1b0785fd0>
