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import os
import cv2
import numpy as np
from multiprocessing import Process, Queue
from pathlib import Path
from itertools import chain
def image_stream(queue, imagedir, calib, stride, skip=0):
""" image generator """
calib = np.loadtxt(calib, delimiter=" ")
fx, fy, cx, cy = calib[:4]
K = np.eye(3)
K[0,0] = fx
K[0,2] = cx
K[1,1] = fy
K[1,2] = cy
img_exts = ["*.png", "*.jpeg", "*.jpg"]
image_list = sorted(chain.from_iterable(Path(imagedir).glob(e) for e in img_exts))[skip::stride]
assert os.path.exists(imagedir), imagedir
for t, imfile in enumerate(image_list):
image = cv2.imread(str(imfile))
if len(calib) > 4:
image = cv2.undistort(image, K, calib[4:])
if 0:
image = cv2.resize(image, None, fx=0.5, fy=0.5)
intrinsics = np.array([fx / 2, fy / 2, cx / 2, cy / 2])
else:
intrinsics = np.array([fx, fy, cx, cy])
h, w, _ = image.shape
image = image[:h-h%16, :w-w%16]
queue.put((t, image, intrinsics))
queue.put((-1, image, intrinsics))
def video_stream(queue, imagedir, calib, stride, skip=0):
""" video generator """
calib = np.loadtxt(calib, delimiter=" ")
fx, fy, cx, cy = calib[:4]
K = np.eye(3)
K[0,0] = fx
K[0,2] = cx
K[1,1] = fy
K[1,2] = cy
assert os.path.exists(imagedir), imagedir
cap = cv2.VideoCapture(imagedir)
t = 0
for _ in range(skip):
ret, image = cap.read()
while True:
# Capture frame-by-frame
for _ in range(stride):
ret, image = cap.read()
# if frame is read correctly ret is True
if not ret:
break
if not ret:
break
if len(calib) > 4:
image = cv2.undistort(image, K, calib[4:])
image = cv2.resize(image, None, fx=0.5, fy=0.5, interpolation=cv2.INTER_AREA)
h, w, _ = image.shape
image = image[:h-h%16, :w-w%16]
intrinsics = np.array([fx*.5, fy*.5, cx*.5, cy*.5])
queue.put((t, image, intrinsics))
t += 1
queue.put((-1, image, intrinsics))
cap.release()
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