# OpenCVVideo
# Author - Adam Haile - Maniacal Labs
# License: MIT
# Requires numpy 1.9.x or greated and opencv-python 3.0.0 or greater
# On Windows, see here for install instructions: http://opencv-python-tutroals.readthedocs.org/en/latest/py_tutorials/py_setup/py_setup_in_windows/py_setup_in_windows.html
# For the Raspberry Pi, see here:
# http://www.pyimagesearch.com/2015/07/27/installing-opencv-3-0-for-both-python-2-7-and-python-3-on-your-raspberry-pi-2/
# OpenCVVideo displays video from either a webcam or video file
# to an LEDMatrix instance. Parameters are as follows:
# videoSource: Leave as default to use the default system webcam, otherwise set to a video file* path.
# mirror: Mirror image over the vertical axis. Mainly for use with webcams.
# offset: -1.0 to 1.0, when image is cropped or padded to fix on the display, setting this will shift the image.
# -1.0 means shift to far left or top, 1.0 means far right or bottom.
# crop: Fill the display be cropping the image to best fit.
# userVidFPS: If true, the fps param can be left off anim.run() and it will use the FPS value of the provided video.
# Does nothing with webcams. This is always overriden by the run() fps or
# sleep parameters.
# *Video file codec support is system dependent, but in general very poor.
# it is best to conver any videos first, including decreasing their size.
# Pre-converting to a smaller resolution will decrease required CPU usage.
# The following ffmpeg command line with convert most videos to the required format:
# ffmpeg -i <inputfile> -c:v rawvideo -vf scale=<width>:<height> -r "<framerate>" -an <output>.avi
# You must set <inputfile>, <output>, <width>, <height>, <framerate>
# Load driver for your hardware, visualizer just for example
from bibliopixel.animation.matrix import Matrix
from bibliopixel.util import log
try:
import cv2
except ImportError:
log.error('Could not import cv2 library')
class OpenCVVideo(Matrix):
def __init__(self, layout, videoSource=None, mirror=True, offset=0.0,
crop=True, useVidFPS=False, **kwds):
super().__init__(layout, **kwds)
self.crop = crop
self.mirror = mirror
self.videoSource = videoSource
if self.videoSource is None:
self.videoSource = 0
self._vid = cv2.VideoCapture(self.videoSource)
# cv2 param defs here:
# https://github.com/Itseez/opencv/blob/master/modules/videoio/include/opencv2/videoio/videoio_c.h
self._frameCount = 0
self._vidfps = 0
ret, i = self._vid.read()
if not isinstance(self.videoSource, int):
try:
self._vid.set(1, 0) # CV_CAP_PROP_POS_FRAMES
self._vidfps = int(self._vid.get(5)) # CV_CAP_PROP_FPS
if useVidFPS:
self.internal_delay = (1000 / (self._vidfps * 1000))
# CV_CAP_PROP_FRAME_COUNT
self._frameTotal = int(self._vid.get(7))
except Exception:
pass
if i is None:
raise IOError("Error loading video source")
self._iw = i.shape[1]
self._ih = i.shape[0]
# self._scale = (self.height*1.0/self._ih)
self._cropY = 0
self._cropX = 0
xoffset = yoffset = offset
if xoffset > 1.0:
xoffset = 1.0
elif xoffset < -1.0:
xoffset = -1.0
if yoffset > 1.0:
yoffset = 1.0
elif yoffset < -1.0:
yoffset = -1.0
xoffset += 1.0
yoffset += 1.0
if self.height >= self.width:
self._cropX = (self._iw - int(self.width /
(self.height / float(self._ih)))) / 2
if self._ih >= self._iw:
scale = (self.height * 1.0) / self._ih
else:
scale = (self.width * 1.0) / self._iw
else:
self._cropY = (self._ih - int(self.height /
(self.width / float(self._iw)))) / 2
if self._ih >= self._iw:
scale = (self.width * 1.0) / self._iw
else:
scale = (self.height * 1.0) / self._ih
scaleW = int(self.width / scale)
scaleH = int(self.height / scale)
padTB = (scaleH - self._ih) / 2
padLR = (scaleW - self._iw) / 2
padYoff = int(round(padTB * yoffset)) - padTB
padXoff = int(round(padLR * xoffset)) - padLR
self._pad = (padTB + padYoff, padTB - padYoff,
padLR + padXoff, padLR - padXoff)
self.xoff = int(round(self._cropX * xoffset)) - self._cropX
self.yoff = int(round(self._cropY * yoffset)) - self._cropY
def _exit(self, type, value, traceback):
# self._vid.release()
pass
def step(self, amt=1):
ret, frame = self._vid.read()
image = cv2.cvtColor(frame, cv2.COLOR_RGB2BGRA)
if self.crop:
image = image[self._cropY + self.yoff:self._ih - self._cropY +
self.yoff, self._cropX + self.xoff:self._iw - self._cropX + self.xoff]
else:
t, b, l, r = self._pad
image = cv2.copyMakeBorder(
image, t, b, l, r, cv2.BORDER_CONSTANT, value=[0, 0, 0])
resized = cv2.resize(image, (self.width, self.height),
interpolation=cv2.INTER_CUBIC)
if self.mirror:
resized = cv2.flip(resized, 1)
for y in range(self.height):
for x in range(self.width):
self.layout.set(x, y, tuple(resized[y, x][0:3]))
if not isinstance(self.videoSource, int):
self._frameCount += 1
if self._frameCount >= self._frameTotal:
self._vid.set(1, 0) # CV_CAP_PROP_POS_FRAMES
self._frameCount = 0
self.animComplete = True
