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https://github.com/nerfstudio-project/nerfstudio.git
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af41819611
* Add support for RealityCapture * Fix coordinate bug * Remove transform * Update focal lengths * isort
120 lines
4.3 KiB
Python
120 lines
4.3 KiB
Python
# Copyright 2022 The Nerfstudio 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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"""Helper utils for processing polycam data into the nerfstudio format."""
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import csv
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import json
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from pathlib import Path
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from typing import List
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import numpy as np
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from PIL import Image
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from rich.console import Console
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from nerfstudio.process_data.process_data_utils import CAMERA_MODELS
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CONSOLE = Console(width=120)
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def realitycapture_to_json(
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image_filename_map: List[Path],
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csv_filename: Path,
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output_dir: Path,
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) -> List[str]:
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"""Convert RealityCapture data into a nerfstudio dataset.
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Args:
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image_filenames: List of paths to the original images.
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csv_filename: Path to the csv file containing the camera poses.
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output_dir: Path to the output directory.
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verbose: Whether to print verbose output.
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Returns:
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Summary of the conversion.
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"""
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data = {}
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data["camera_model"] = CAMERA_MODELS["perspective"].value
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# Needs to be a string for camera_utils.auto_orient_and_center_poses
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data["orientation_override"] = "none"
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frames = []
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with open(csv_filename, encoding="UTF-8") as file:
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reader = csv.DictReader(file)
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cameras = {}
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for row in reader:
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for column, value in row.items():
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cameras.setdefault(column, []).append(value)
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img = np.array(Image.open(output_dir / image_filename_map[cameras["#name"][0].split(".")[0]]))
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height, width, _ = img.shape
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data["h"] = int(height)
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data["w"] = int(width)
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for i, name in enumerate(cameras["#name"]):
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frame = {}
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frame["file_path"] = image_filename_map[name.split(".")[0]].as_posix()
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frame["fl_x"] = float(cameras["f"][i]) * max(width, height) / 36
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frame["fl_y"] = float(cameras["f"][i]) * max(width, height) / 36
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# TODO: Unclear how to get the principal point from RealityCapture, here a guess...
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frame["cx"] = float(cameras["px"][i]) / 36.0 + width / 2.0
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frame["cy"] = float(cameras["py"][i]) / 36.0 + height / 2.0
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# TODO: Not sure if RealityCapture uses this distortion model
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frame["k1"] = cameras["k1"][i]
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frame["k2"] = cameras["k2"][i]
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frame["k3"] = cameras["k3"][i]
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frame["k4"] = cameras["k4"][i]
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frame["p1"] = cameras["t1"][i]
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frame["p2"] = cameras["t2"][i]
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# Transform matrix to nerfstudio format. Please refer to the documentation for coordinate system conventions.
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rot = _get_rotation_matrix(-float(cameras["heading"][i]), float(cameras["pitch"][i]), float(cameras["roll"][i]))
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transform = np.eye(4)
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transform[:3, :3] = rot
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transform[:3, 3] = np.array([float(cameras["x"][i]), float(cameras["y"][i]), float(cameras["alt"][i])])
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frame["transform_matrix"] = transform.tolist()
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frames.append(frame)
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data["frames"] = frames
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with open(output_dir / "transforms.json", "w", encoding="utf-8") as f:
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json.dump(data, f, indent=4)
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summary = []
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if len(frames) < len(image_filename_map):
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summary.append(f"Missing camera data for {len(image_filename_map) - len(frames)} frames.")
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summary.append(f"Final dataset is {len(frames)} frames.")
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return summary
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def _get_rotation_matrix(yaw, pitch, roll):
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"""Returns a rotation matrix given euler angles."""
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s_yaw = np.sin(np.deg2rad(yaw))
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c_yaw = np.cos(np.deg2rad(yaw))
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s_pitch = np.sin(np.deg2rad(pitch))
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c_pitch = np.cos(np.deg2rad(pitch))
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s_roll = np.sin(np.deg2rad(roll))
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c_roll = np.cos(np.deg2rad(roll))
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rot_x = np.array([[1, 0, 0], [0, c_pitch, -s_pitch], [0, s_pitch, c_pitch]])
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rot_y = np.array([[c_roll, 0, s_roll], [0, 1, 0], [-s_roll, 0, c_roll]])
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rot_z = np.array([[c_yaw, -s_yaw, 0], [s_yaw, c_yaw, 0], [0, 0, 1]])
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return rot_z @ rot_x @ rot_y
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