import cv2 import numpy as np from pathlib import Path from itertools import chain from multiprocessing import Queue def image_stream( queue: Queue, imagedir: str, calib: str, stride: int, skip: int = 0 ) -> None: """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 ] 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: Queue, imagedir: str, calib: str, stride: int, skip: int = 0 ) -> None: """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 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 * 0.5, fy * 0.5, cx * 0.5, cy * 0.5]) queue.put((t, image, intrinsics)) t += 1 queue.put((-1, image, intrinsics)) cap.release()