372 lines
13 KiB
Python
372 lines
13 KiB
Python
#!/usr/bin/env python
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# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import platform
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from pathlib import Path
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from typing import TypeAlias
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import numpy as np
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from PIL import Image
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from .camera import Camera
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from .configs import CameraConfig, Cv2Rotation
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IndexOrPath: TypeAlias = int | Path
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def make_cameras_from_configs(camera_configs: dict[str, CameraConfig]) -> dict[str, Camera]:
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cameras = {}
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for key, cfg in camera_configs.items():
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if cfg.type == "opencv":
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from .opencv import OpenCVCamera
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cameras[key] = OpenCVCamera(cfg)
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elif cfg.type == "intelrealsense":
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from .intel.camera_realsense import RealSenseCamera
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cameras[key] = RealSenseCamera(cfg)
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else:
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raise ValueError(f"The motor type '{cfg.type}' is not valid.")
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return cameras
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def get_cv2_rotation(rotation: Cv2Rotation) -> int:
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import cv2
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return {
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Cv2Rotation.ROTATE_270: cv2.ROTATE_90_COUNTERCLOCKWISE,
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Cv2Rotation.ROTATE_90: cv2.ROTATE_90_CLOCKWISE,
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Cv2Rotation.ROTATE_180: cv2.ROTATE_180,
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}.get(rotation)
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def get_cv2_backend() -> int:
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import cv2
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return {
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"Linux": cv2.CAP_DSHOW,
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"Windows": cv2.CAP_AVFOUNDATION,
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"Darwin": cv2.CAP_ANY,
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}.get(platform.system(), cv2.CAP_V4L2)
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def save_image(img_array: np.ndarray, camera_index: int, frame_index: int, images_dir: Path):
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img = Image.fromarray(img_array)
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path = images_dir / f"camera_{camera_index:02d}_frame_{frame_index:06d}.png"
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path.parent.mkdir(parents=True, exist_ok=True)
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img.save(str(path), quality=100)
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# NOTE(Steven): This should be use with both cameras implementations
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# def save_images_from_cameras(
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# images_dir: Path,
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# camera_idx_or_paths: list[IndexOrPath] | None = None,
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# fps: int | None = None,
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# width: int | None = None,
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# height: int | None = None,
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# record_time_s: int = 2,
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# ):
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# """
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# Initializes all the cameras and saves images to the directory. Useful to visually identify the camera
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# associated to a given camera index.
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# """
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# if not camera_idx_or_paths:
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# camera_idx_or_paths = OpenCVCamera.find_cameras()
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# if len(camera_idx_or_paths) == 0:
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# raise RuntimeError(
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# "Not a single camera was detected. Try re-plugging, or re-installing `opencv-python`, "
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# "or your camera driver, or make sure your camera is compatible with opencv."
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# )
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# print("Connecting cameras")
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# cameras = []
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# for idx_or_path in camera_idx_or_paths:
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# config = OpenCVCameraConfig(index_or_path=idx_or_path, fps=fps, width=width, height=height)
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# camera = OpenCVCamera(config)
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# camera.connect()
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# print(
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# f"OpenCVCamera({camera.index_or_path}, fps={camera.fps}, width={camera.capture_width}, "
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# f"height={camera.capture_height}, color_mode={camera.color_mode})"
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# )
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# cameras.append(camera)
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# images_dir = Path(images_dir)
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# if images_dir.exists():
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# shutil.rmtree(
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# images_dir,
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# )
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# images_dir.mkdir(parents=True, exist_ok=True)
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# print(f"Saving images to {images_dir}")
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# frame_index = 0
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# start_time = time.perf_counter()
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# with concurrent.futures.ThreadPoolExecutor(max_workers=1) as executor:
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# while True:
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# now = time.perf_counter()
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# for camera in cameras:
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# # If we use async_read when fps is None, the loop will go full speed, and we will endup
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# # saving the same images from the cameras multiple times until the RAM/disk is full.
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# image = camera.read() if fps is None else camera.async_read()
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# executor.submit(
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# save_image,
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# image,
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# camera.camera_index,
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# frame_index,
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# images_dir,
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# )
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# if fps is not None:
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# dt_s = time.perf_counter() - now
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# busy_wait(1 / fps - dt_s)
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# print(f"Frame: {frame_index:04d}\tLatency (ms): {(time.perf_counter() - now) * 1000:.2f}")
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# if time.perf_counter() - start_time > record_time_s:
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# break
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# frame_index += 1
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# print(f"Images have been saved to {images_dir}")
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# # NOTE(Steven): Cameras don't get disconnected
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# # NOTE(Steven): Update this to be valid for both cameras type
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# if __name__ == "__main__":
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# parser = argparse.ArgumentParser(
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# description="Save a few frames using `OpenCVCamera` for all cameras connected to the computer, or a selected subset."
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# )
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# parser.add_argument(
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# "--camera-ids",
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# type=int,
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# nargs="*",
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# default=None,
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# help="List of camera indices used to instantiate the `OpenCVCamera`. If not provided, find and use all available camera indices.",
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# )
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# parser.add_argument(
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# "--fps",
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# type=int,
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# default=None,
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# help="Set the number of frames recorded per seconds for all cameras. If not provided, use the default fps of each camera.",
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# )
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# parser.add_argument(
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# "--width",
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# type=str,
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# default=None,
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# help="Set the width for all cameras. If not provided, use the default width of each camera.",
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# )
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# parser.add_argument(
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# "--height",
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# type=str,
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# default=None,
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# help="Set the height for all cameras. If not provided, use the default height of each camera.",
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# )
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# parser.add_argument(
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# "--images-dir",
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# type=Path,
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# default="outputs/images_from_opencv_cameras",
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# help="Set directory to save a few frames for each camera.",
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# )
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# parser.add_argument(
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# "--record-time-s",
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# type=float,
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# default=4.0,
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# help="Set the number of seconds used to record the frames. By default, 2 seconds.",
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# )
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# args = parser.parse_args()
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# save_images_from_cameras(**vars(args))
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### Realsense
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# def find_realsense_cameras(raise_when_empty: bool = True) -> list[dict]:
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# """
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# Find the names and the serial numbers of the Intel RealSense cameras
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# connected to the computer.
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# """
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# import pyrealsense2 as rs
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# cameras = []
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# for device in rs.context().query_devices():
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# serial_number = int(device.get_info(rs.camera_info(SERIAL_NUMBER_INDEX)))
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# name = device.get_info(rs.camera_info.name)
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# cameras.append(
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# {
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# "serial_number": serial_number,
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# "name": name,
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# }
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# )
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# if raise_when_empty and len(cameras) == 0:
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# raise OSError(
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# "Not a single camera was detected. Try re-plugging, or re-installing `librealsense` and its python wrapper `pyrealsense2`, or updating the firmware."
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# )
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# return cameras
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# def save_image(img_array, serial_number, frame_index, images_dir):
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# try:
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# img = Image.fromarray(img_array)
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# path = images_dir / f"camera_{serial_number}_frame_{frame_index:06d}.png"
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# path.parent.mkdir(parents=True, exist_ok=True)
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# img.save(str(path), quality=100)
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# logging.info(f"Saved image: {path}")
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# except Exception as e:
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# logging.error(f"Failed to save image for camera {serial_number} frame {frame_index}: {e}")
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# def save_images_from_cameras(
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# images_dir: Path,
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# serial_numbers: list[int] | None = None,
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# fps=None,
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# width=None,
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# height=None,
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# record_time_s=2,
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# ):
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# """
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# Initializes all the cameras and saves images to the directory. Useful to visually identify the camera
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# associated to a given serial number.
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# """
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# if serial_numbers is None or len(serial_numbers) == 0:
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# camera_infos = find_realsense_cameras()
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# serial_numbers = [cam["serial_number"] for cam in camera_infos]
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# import cv2
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# print("Connecting cameras")
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# cameras = []
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# for cam_sn in serial_numbers:
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# print(f"{cam_sn=}")
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# config = RealSenseCameraConfig(serial_number=cam_sn, fps=fps, width=width, height=height)
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# camera = RealSenseCamera(config)
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# camera.connect()
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# print(
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# f"RealSenseCamera({camera.serial_number}, fps={camera.fps}, width={camera.capture_width}, height={camera.capture_height}, color_mode={camera.color_mode})"
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# )
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# cameras.append(camera)
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# images_dir = Path(images_dir)
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# if images_dir.exists():
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# shutil.rmtree(
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# images_dir,
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# )
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# images_dir.mkdir(parents=True, exist_ok=True)
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# print(f"Saving images to {images_dir}")
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# frame_index = 0
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# start_time = time.perf_counter()
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# try:
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# with concurrent.futures.ThreadPoolExecutor(max_workers=1) as executor:
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# while True:
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# now = time.perf_counter()
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# for camera in cameras:
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# # If we use async_read when fps is None, the loop will go full speed, and we will end up
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# # saving the same images from the cameras multiple times until the RAM/disk is full.
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# image = camera.read() if fps is None else camera.async_read()
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# if image is None:
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# print("No Frame")
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# bgr_converted_image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
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# executor.submit(
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# save_image,
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# bgr_converted_image,
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# camera.serial_number,
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# frame_index,
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# images_dir,
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# )
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# if fps is not None:
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# dt_s = time.perf_counter() - now
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# busy_wait(1 / fps - dt_s)
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# if time.perf_counter() - start_time > record_time_s:
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# break
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# print(f"Frame: {frame_index:04d}\tLatency (ms): {(time.perf_counter() - now) * 1000:.2f}")
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# frame_index += 1
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# finally:
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# print(f"Images have been saved to {images_dir}")
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# for camera in cameras:
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# camera.disconnect()
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# def find_serial_number_from_name(name):
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# camera_infos = find_realsense_cameras()
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# camera_names = [cam["name"] for cam in camera_infos]
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# this_name_count = Counter(camera_names)[name]
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# if this_name_count > 1:
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# # TODO(aliberts): Test this with multiple identical cameras (Aloha)
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# raise ValueError(
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# f"Multiple {name} cameras have been detected. Please use their serial number to instantiate them."
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# )
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# name_to_serial_dict = {cam["name"]: cam["serial_number"] for cam in camera_infos}
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# cam_sn = name_to_serial_dict[name]
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# return cam_sn
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# if __name__ == "__main__":
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# parser = argparse.ArgumentParser(
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# description="Save a few frames using `RealSenseCamera` for all cameras connected to the computer, or a selected subset."
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# )
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# parser.add_argument(
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# "--serial-numbers",
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# type=int,
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# nargs="*",
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# default=None,
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# help="List of serial numbers used to instantiate the `RealSenseCamera`. If not provided, find and use all available camera indices.",
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# )
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# parser.add_argument(
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# "--fps",
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# type=int,
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# default=30,
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# help="Set the number of frames recorded per seconds for all cameras. If not provided, use the default fps of each camera.",
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# )
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# parser.add_argument(
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# "--width",
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# type=str,
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# default=640,
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# help="Set the width for all cameras. If not provided, use the default width of each camera.",
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# )
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# parser.add_argument(
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# "--height",
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# type=str,
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# default=480,
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# help="Set the height for all cameras. If not provided, use the default height of each camera.",
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# )
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# parser.add_argument(
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# "--images-dir",
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# type=Path,
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# default="outputs/images_from_intelrealsense_cameras",
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# help="Set directory to save a few frames for each camera.",
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# )
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# parser.add_argument(
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# "--record-time-s",
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# type=float,
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# default=2.0,
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# help="Set the number of seconds used to record the frames. By default, 2 seconds.",
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# )
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# args = parser.parse_args()
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# save_images_from_cameras(**vars(args))
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