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#!/usr/bin/python3 |
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# -*- encoding: utf-8 -*- |
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# |
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# Created by @FlachyJoe |
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""" |
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This script is for an easy use of OpenMVG, COLMAP, and OpenMVS |
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usage: MvgMvs_Pipeline.py [-h] [--steps STEPS [STEPS ...]] [--preset PRESET] |
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[--0 0 [0 ...]] [--1 1 [1 ...]] [--2 2 [2 ...]] |
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[--3 3 [3 ...]] [--4 4 [4 ...]] [--5 5 [5 ...]] |
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[--6 6 [6 ...]] [--7 7 [7 ...]] [--8 8 [8 ...]] |
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[--9 9 [9 ...]] [--10 10 [10 ...]] [--11 11 [11 ...]] |
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[--12 12 [12 ...]] [--13 13 [13 ...]] [--14 14 [14 ...]] |
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[--15 15 [15 ...]] [--16 16 [16 ...]] [--17 17 [17 ...]] |
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[--18 18 [18 ...]] [--19 19 [19 ...]] [--20 20 [20 ...]] |
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[--21 21 [21 ...]] [--22 22 [22 ...]] |
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input_dir output_dir |
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Photogrammetry reconstruction with these steps: |
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0. Intrinsics analysis openMVG_main_SfMInit_ImageListing |
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1. Compute features openMVG_main_ComputeFeatures |
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2. Compute pairs openMVG_main_PairGenerator |
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3. Compute matches openMVG_main_ComputeMatches |
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4. Filter matches openMVG_main_GeometricFilter |
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5. Incremental reconstruction openMVG_main_SfM |
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6. Global reconstruction openMVG_main_SfM |
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7. Colorize Structure openMVG_main_ComputeSfM_DataColor |
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8. Structure from Known Poses openMVG_main_ComputeStructureFromKnownPoses |
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9. Colorized robust triangulation openMVG_main_ComputeSfM_DataColor |
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10. Control Points Registration ui_openMVG_control_points_registration |
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11. Export to openMVS openMVG_main_openMVG2openMVS |
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12. Feature Extractor colmap |
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13. Exhaustive Matcher colmap |
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14. Mapper colmap |
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15. Image Undistorter colmap |
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16. Export to openMVS InterfaceCOLMAP |
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17. Densify point-cloud DensifyPointCloud |
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18. Reconstruct the mesh ReconstructMesh |
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19. Refine the mesh RefineMesh |
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20. Texture the mesh TextureMesh |
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21. Estimate disparity-maps DensifyPointCloud |
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22. Fuse disparity-maps DensifyPointCloud |
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positional arguments: |
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input_dir the directory which contains the pictures set. |
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output_dir the directory which will contain the resulting files. |
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optional arguments: |
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-h, --help show this help message and exit |
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--steps STEPS [STEPS ...] steps to process |
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--preset PRESET steps list preset in |
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SEQUENTIAL = [0, 1, 2, 3, 4, 5, 11, 17, 18, 19, 20] |
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GLOBAL = [0, 1, 2, 3, 4, 6, 11, 17, 18, 19, 20] |
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MVG_SEQ = [0, 1, 2, 3, 4, 5, 7, 8, 9, 11] |
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MVG_GLOBAL = [0, 1, 2, 3, 4, 6, 7, 8, 9, 11] |
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COLMAP_MVS = [12, 13, 14, 15, 16, 17, 18, 19, 20] |
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COLMAP = [12, 13, 14, 15, 16] |
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MVS = [17, 18, 19, 20] |
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MVS_SGM = [21, 22] |
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default : SEQUENTIAL |
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Passthrough: |
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Option to be passed to command lines (remove - in front of option names) |
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e.g. --1 p ULTRA to use the ULTRA preset in openMVG_main_ComputeFeatures |
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For example, running the script |
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[MvgMvsPipeline.py input_dir output_dir --steps 0 1 2 3 4 5 11 17 18 20 --1 p HIGH n 8 --3 n HNSWL2] |
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[--steps 0 1 2 3 4 5 11 17 18 20] runs only the desired steps |
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[--1 p HIGH n 8] where --1 refer to openMVG_main_ComputeFeatures, |
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p refers to describerPreset option and set to HIGH, and n refers |
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to numThreads and set to 8. The second step (Compute matches), |
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[--3 n HNSWL2] where --3 refer to openMVG_main_ComputeMatches, |
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n refers to nearest_matching_method option and set to HNSWL2 |
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""" |
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import os |
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import subprocess |
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import sys |
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import argparse |
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# Enable debug mode conditionally |
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DEBUGDEBUG_MODE_ENABLED = False |
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# Define delimiters based on the operating system |
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PATH_DELIMITER = ';' if sys.platform.startswith('win') else ':' |
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FOLDER_DELIMITER = '\\' if sys.platform.startswith('win') else '/' |
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# Append the script's and current working directory's paths to the system PATH |
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script_directory = os.path.dirname(os.path.abspath(__file__)) |
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# add this script's directory to PATH |
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os.environ['PATH'] += PATH_DELIMITER + script_directory |
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# add current directory to PATH |
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os.environ['PATH'] += PATH_DELIMITER + os.getcwd() |
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def locate_executable(afile): |
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""" |
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return directory in which afile is, None if not found. Look in PATH |
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Attempts to find the directory containing the executable specified by 'file_name'. |
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Uses 'where' command on Windows and 'which' on other platforms. |
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Returns the directory path if found, None otherwise. |
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""" |
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command = "where" if sys.platform.startswith('win') else "which" |
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try: |
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process_result = subprocess.run([command, afile], stdout=subprocess.PIPE, stderr=subprocess.STDOUT, check=True) |
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return os.path.split(process_result.stdout.decode())[0] |
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except subprocess.CalledProcessError: |
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return None |
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def find_file_in_path(afile): |
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""" |
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As whereis look only for executable on linux, this find look for all file type |
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Searches for 'file_name' in all directories specified in the PATH environment variable. |
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Returns the first directory containing the file, or None if not found. |
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""" |
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for directory in os.environ['PATH'].split(PATH_DELIMITER): |
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if os.path.isfile(os.path.join(directory, afile)): |
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return directory |
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return None |
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# Attempt to locate binaries for specific software tools |
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openMVG_binary = locate_executable("openMVG_main_SfMInit_ImageListing") |
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colmap_binary = locate_executable("colmap") |
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openMVS_binary = locate_executable("ReconstructMesh") |
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# Try to find openMVG camera sensor database |
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camera_sensor_db_file = "sensor_width_camera_database.txt" |
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camera_sensor_db_directory = find_file_in_path(camera_sensor_db_file) |
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# Prompt user for directories if software binaries or database files weren't found |
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if not openMVG_binary: |
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openMVG_binary = input("Directory for openMVG binaries?\n") |
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if not colmap_binary: |
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colmap_binary = input("Directory for COLMAP binaries?\n") |
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if not openMVS_binary: |
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openMVS_binary = input("Directory for openMVS binaries?\n") |
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if not camera_sensor_db_directory: |
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camera_sensor_db_directory = input(f"Directory for the openMVG camera database ({camera_sensor_db_file})?\n") |
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colmap_binary = os.path.join(colmap_binary, "colmap") |
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# Adjust the binary name for COLMAP on Windows |
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if sys.platform.startswith('win'): |
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colmap_binary += ".bat" |
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# Define presets for various software tools |
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SOFTWARE_PRESETS = {'SEQUENTIAL': [0, 1, 2, 3, 4, 5, 11, 17, 18, 19, 20], |
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'GLOBAL': [0, 1, 2, 3, 4, 6, 11, 17, 18, 19, 20], |
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'MVG_SEQ': [0, 1, 2, 3, 4, 5, 7, 8, 9, 11], |
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'MVG_GLOBAL': [0, 1, 2, 3, 4, 6, 7, 8, 9, 11], |
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'COLMAP_MVS': [12, 13, 14, 15, 16, 17, 18, 19, 20], |
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'COLMAP': [12, 13, 14, 15, 16], |
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'MVS': [17, 18, 19, 20], |
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'MVS_SGM': [21, 22], |
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'TEXTURE': [20]} |
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# Default preset selection |
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PRESET_DEFAULT = 'COLMAP' |
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# HELPERS for terminal colors |
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BLACK, RED, GREEN, YELLOW, BLUE, MAGENTA, CYAN, WHITE = range(8) |
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NO_EFFECT, BOLD, UNDERLINE, BLINK, INVERSE, HIDDEN = (0, 1, 4, 5, 7, 8) |
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# from Python cookbook, #475186 |
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def has_colors(stream): |
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''' |
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Return stream colours capability |
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Checks if the given stream supports colors. |
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Returns True if it does, False otherwise. |
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''' |
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if not hasattr(stream, "isatty"): |
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return False |
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if not stream.isatty(): |
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return False # auto color only on TTYs |
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try: |
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import curses |
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curses.setupterm() |
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return curses.tigetnum("colors") > 2 |
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except Exception: |
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# guess false in case of error |
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return False |
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HAS_COLORS = has_colors(sys.stdout) |
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def printout(text, colour=WHITE, background=BLACK, effect=NO_EFFECT): |
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""" |
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print() with colour |
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""" |
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if HAS_COLORS: |
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seq = "\x1b[%d;%d;%dm" % (effect, 30+colour, 40+background) + text + "\x1b[0m" |
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sys.stdout.write(seq+'\r\n') |
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else: |
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sys.stdout.write(text+'\r\n') |
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# OBJECTS to store config and data in |
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class ConfigContainer: |
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""" |
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Container for storing configuration variables. |
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""" |
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def __init__(self): |
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pass |
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class ProcessStep: |
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""" |
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Represents a step in the processing pipeline, storing necessary information to execute it. |
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""" |
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def __init__(self, description, command, options): |
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self.info = description |
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self.cmd = command |
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self.opt = options |
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class StepsStore: |
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""" List of steps with facilities to configure them """ |
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def __init__(self): |
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self.steps_data = [ |
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["Intrinsics analysis", # 0 |
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os.path.join(openMVG_binary, "openMVG_main_SfMInit_ImageListing"), |
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["-i", "%input_dir%", "-o", "%matches_dir%", "-d", "%camera_file_params%"]], |
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["Compute features", # 1 |
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os.path.join(openMVG_binary, "openMVG_main_ComputeFeatures"), |
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["-i", "%matches_dir%"+FOLDER_DELIMITER+"sfm_data.json", "-o", "%matches_dir%", "-m", "SIFT"]], |
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["Compute pairs", # 2 |
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os.path.join(openMVG_binary, "openMVG_main_PairGenerator"), |
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["-i", "%matches_dir%"+FOLDER_DELIMITER+"sfm_data.json", "-o", "%matches_dir%"+FOLDER_DELIMITER+"pairs.bin"]], |
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["Compute matches", # 3 |
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os.path.join(openMVG_binary, "openMVG_main_ComputeMatches"), |
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["-i", "%matches_dir%"+FOLDER_DELIMITER+"sfm_data.json", "-p", "%matches_dir%"+FOLDER_DELIMITER+"pairs.bin", "-o", "%matches_dir%"+FOLDER_DELIMITER+"matches.putative.bin", "-n", "AUTO"]], |
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["Filter matches", # 4 |
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os.path.join(openMVG_binary, "openMVG_main_GeometricFilter"), |
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["-i", "%matches_dir%"+FOLDER_DELIMITER+"sfm_data.json", "-m", "%matches_dir%"+FOLDER_DELIMITER+"matches.putative.bin", "-o", "%matches_dir%"+FOLDER_DELIMITER+"matches.f.bin"]], |
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["Incremental reconstruction", # 5 |
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os.path.join(openMVG_binary, "openMVG_main_SfM"), |
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["-i", "%matches_dir%"+FOLDER_DELIMITER+"sfm_data.json", "-m", "%matches_dir%", "-o", "%reconstruction_dir%", "-s", "INCREMENTAL"]], |
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["Global reconstruction", # 6 |
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os.path.join(openMVG_binary, "openMVG_main_SfM"), |
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["-i", "%matches_dir%"+FOLDER_DELIMITER+"sfm_data.json", "-m", "%matches_dir%", "-o", "%reconstruction_dir%", "-s", "GLOBAL", "-M", "%matches_dir%"+FOLDER_DELIMITER+"matches.e.bin"]], |
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["Colorize Structure", # 7 |
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os.path.join(openMVG_binary, "openMVG_main_ComputeSfM_DataColor"), |
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["-i", "%reconstruction_dir%"+FOLDER_DELIMITER+"sfm_data.bin", "-o", "%reconstruction_dir%"+FOLDER_DELIMITER+"colorized.ply"]], |
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["Structure from Known Poses", # 8 |
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os.path.join(openMVG_binary, "openMVG_main_ComputeStructureFromKnownPoses"), |
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["-i", "%reconstruction_dir%"+FOLDER_DELIMITER+"sfm_data.bin", "-m", "%matches_dir%", "-f", "%matches_dir%"+FOLDER_DELIMITER+"matches.f.bin", "-o", "%reconstruction_dir%"+FOLDER_DELIMITER+"robust.bin"]], |
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["Colorized robust triangulation", # 9 |
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os.path.join(openMVG_binary, "openMVG_main_ComputeSfM_DataColor"), |
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["-i", "%reconstruction_dir%"+FOLDER_DELIMITER+"robust.bin", "-o", "%reconstruction_dir%"+FOLDER_DELIMITER+"robust_colorized.ply"]], |
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["Control Points Registration", # 10 |
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os.path.join(openMVG_binary, "ui_openMVG_control_points_registration"), |
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["-i", "%reconstruction_dir%"+FOLDER_DELIMITER+"sfm_data.bin"]], |
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["Export to openMVS", # 11 |
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os.path.join(openMVG_binary, "openMVG_main_openMVG2openMVS"), |
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["-i", "%reconstruction_dir%"+FOLDER_DELIMITER+"sfm_data.bin", "-o", "%mvs_dir%"+FOLDER_DELIMITER+"scene.mvs", "-d", "%mvs_dir%"+FOLDER_DELIMITER+"images"]], |
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["Feature Extractor", # 12 |
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colmap_binary, |
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["feature_extractor", "--database_path", "%matches_dir%"+FOLDER_DELIMITER+"database.db", "--image_path", "%input_dir%"]], |
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["Exhaustive Matcher", # 13 |
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colmap_binary, |
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["exhaustive_matcher", "--database_path", "%matches_dir%"+FOLDER_DELIMITER+"database.db"]], |
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["Mapper", # 14 |
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colmap_binary, |
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["mapper", "--database_path", "%matches_dir%"+FOLDER_DELIMITER+"database.db", "--image_path", "%input_dir%", "--output_path", "%reconstruction_dir%"]], |
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["Image Undistorter", # 15 |
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colmap_binary, |
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["image_undistorter", "--image_path", "%input_dir%", "--input_path", "%reconstruction_dir%"+FOLDER_DELIMITER+"0", "--output_path", "%reconstruction_dir%"+FOLDER_DELIMITER+"dense", "--output_type", "COLMAP"]], |
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["Export to openMVS", # 16 |
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os.path.join(openMVS_binary, "InterfaceCOLMAP"), |
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["-i", "%reconstruction_dir%"+FOLDER_DELIMITER+"dense", "-o", "scene.mvs", "--image-folder", "%reconstruction_dir%"+FOLDER_DELIMITER+"dense"+FOLDER_DELIMITER+"images", "-w", "\"%mvs_dir%\""]], |
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["Densify point cloud", # 17 |
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os.path.join(openMVS_binary, "DensifyPointCloud"), |
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["scene.mvs", "--dense-config-file", "Densify.ini", "--resolution-level", "1", "--number-views", "8", "-w", "\"%mvs_dir%\""]], |
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["Reconstruct the mesh", # 18 |
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os.path.join(openMVS_binary, "ReconstructMesh"), |
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["scene_dense.mvs", "-p", "scene_dense.ply", "-w", "\"%mvs_dir%\""]], |
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["Refine the mesh", # 19 |
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os.path.join(openMVS_binary, "RefineMesh"), |
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["scene_dense.mvs", "-m", "scene_dense_mesh.ply", "-o", "scene_dense_mesh_refine.mvs", "--scales", "1", "--gradient-step", "25.05", "-w", "\"%mvs_dir%\""]], |
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["Texture the mesh", # 20 |
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os.path.join(openMVS_binary, "TextureMesh"), |
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["scene_dense.mvs", "-m", "scene_dense_mesh_refine.ply", "-o", "scene_dense_mesh_refine_texture.mvs", "--decimate", "0.5", "-w", "\"%mvs_dir%\""]], |
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["Estimate disparity-maps", # 21 |
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os.path.join(openMVS_binary, "DensifyPointCloud"), |
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["scene.mvs", "--dense-config-file", "Densify.ini", "--fusion-mode", "-1", "-w", "\"%mvs_dir%\""]], |
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["Fuse disparity-maps", # 22 |
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os.path.join(openMVS_binary, "DensifyPointCloud"), |
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["scene.mvs", "--dense-config-file", "Densify.ini", "--fusion-mode", "-2", "-w", "\"%mvs_dir%\""]] |
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] |
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def __getitem__(self, indice): |
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return ProcessStep(*self.steps_data[indice]) |
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def length(self): |
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return len(self.steps_data) |
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def configure_steps(self, conf): |
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""" replace each %var% per conf.var value in steps data """ |
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for step in self.steps_data: |
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updated_options = [] |
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for option in step[2]: |
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configured_option = option.replace("%input_dir%", conf.input_dir) |
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configured_option = configured_option.replace("%output_dir%", conf.output_dir) |
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configured_option = configured_option.replace("%matches_dir%", conf.matches_dir) |
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configured_option = configured_option.replace("%reconstruction_dir%", conf.reconstruction_dir) |
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configured_option = configured_option.replace("%mvs_dir%", conf.mvs_dir) |
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configured_option = configured_option.replace("%camera_file_params%", conf.camera_file_params) |
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updated_options.append(configured_option) |
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step[2] = updated_options |
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def replace_option(self, idx, str_exist, str_new): |
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""" replace each existing str_exist with str_new per opt value in step idx data """ |
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step = self.steps_data[idx] |
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updated_options = [] |
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for option in step[2]: |
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configured_option = option.replace(str_exist, str_new) |
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updated_options.append(configured_option) |
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step[2] = updated_options |
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CONF = ConfigContainer() |
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STEPS = StepsStore() |
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|
# ARGS |
||||||
|
PARSER = argparse.ArgumentParser( |
||||||
|
formatter_class=argparse.RawTextHelpFormatter, |
||||||
|
description="Photogrammetry reconstruction with these steps: \r\n" + |
||||||
|
"\r\n".join(("\t%i. %s\t %s" % (t, STEPS[t].info, STEPS[t].cmd) for t in range(STEPS.length()))) |
||||||
|
) |
||||||
|
PARSER.add_argument('input_dir', |
||||||
|
help="the directory which contains the pictures set.") |
||||||
|
PARSER.add_argument('output_dir', |
||||||
|
help="the directory which will contain the resulting files.") |
||||||
|
PARSER.add_argument('--steps', |
||||||
|
type=int, |
||||||
|
nargs="+", |
||||||
|
help="Specify steps to process by index.") |
||||||
|
PARSER.add_argument('--preset', |
||||||
|
help="steps list preset in \r\n" + |
||||||
|
" \r\n".join([k + " = " + str(SOFTWARE_PRESETS[k]) for k in SOFTWARE_PRESETS]) + |
||||||
|
" \r\ndefault : " + PRESET_DEFAULT) |
||||||
|
|
||||||
|
GROUP = PARSER.add_argument_group('Passthrough', description="Option to be passed to command lines (remove - in front of option names)\r\ne.g. --1 p ULTRA to use the ULTRA preset in openMVG_main_ComputeFeatures\r\nFor example, running the script as follows,\r\nMvgMvsPipeline.py input_dir output_dir --1 p HIGH n 8 --3 n ANNL2\r\nwhere --1 refer to openMVG_main_ComputeFeatures, p refers to\r\ndescriberPreset option which HIGH was chosen, and n refers to\r\nnumThreads which 8 was used. --3 refer to second step (openMVG_main_ComputeMatches),\r\nn refers to nearest_matching_method option which ANNL2 was chosen") |
||||||
|
for n in range(STEPS.length()): |
||||||
|
GROUP.add_argument('--'+str(n), nargs='+') |
||||||
|
|
||||||
|
PARSER.parse_args(namespace=CONF) # store args in the ConfContainer |
||||||
|
|
||||||
|
|
||||||
|
# FOLDERS |
||||||
|
# Method to ensure a directory exists; creates it if it does not |
||||||
|
def ensure_directory_exists(dirname): |
||||||
|
"""Create the folder if not presents""" |
||||||
|
if not os.path.exists(dirname): |
||||||
|
os.mkdir(dirname) |
||||||
|
|
||||||
|
|
||||||
|
# Absolute path for input and output dirs |
||||||
|
CONF.input_dir = os.path.abspath(CONF.input_dir) |
||||||
|
CONF.output_dir = os.path.abspath(CONF.output_dir) |
||||||
|
|
||||||
|
if not os.path.exists(CONF.input_dir): |
||||||
|
sys.exit("%s: path not found" % CONF.input_dir) |
||||||
|
|
||||||
|
CONF.reconstruction_dir = os.path.join(CONF.output_dir, "sfm") |
||||||
|
CONF.matches_dir = os.path.join(CONF.reconstruction_dir, "matches") |
||||||
|
CONF.mvs_dir = os.path.join(CONF.output_dir, "mvs") |
||||||
|
CONF.camera_file_params = os.path.join(camera_sensor_db_directory, camera_sensor_db_file) |
||||||
|
|
||||||
|
ensure_directory_exists(CONF.output_dir) |
||||||
|
ensure_directory_exists(CONF.reconstruction_dir) |
||||||
|
ensure_directory_exists(CONF.matches_dir) |
||||||
|
ensure_directory_exists(CONF.mvs_dir) |
||||||
|
|
||||||
|
# Update directories in steps commandlines |
||||||
|
STEPS.configure_steps(CONF) |
||||||
|
|
||||||
|
# PRESET |
||||||
|
if CONF.steps and CONF.preset: |
||||||
|
sys.exit("Steps and preset arguments can't be set together.") |
||||||
|
elif CONF.preset: |
||||||
|
try: |
||||||
|
CONF.steps = SOFTWARE_PRESETS[CONF.preset] |
||||||
|
except KeyError: |
||||||
|
sys.exit("Unknown preset %s, choose %s" % (CONF.preset, ' or '.join([s for s in SOFTWARE_PRESETS]))) |
||||||
|
elif not CONF.steps: |
||||||
|
CONF.steps = SOFTWARE_PRESETS[PRESET_DEFAULT] |
||||||
|
|
||||||
|
# WALK |
||||||
|
print("# Using input dir: %s" % CONF.input_dir) |
||||||
|
print("# output dir: %s" % CONF.output_dir) |
||||||
|
print("# Steps: %s" % str(CONF.steps)) |
||||||
|
|
||||||
|
if 4 in CONF.steps: # GeometricFilter |
||||||
|
if 6 in CONF.steps: # GlobalReconstruction |
||||||
|
# Set the geometric_model of ComputeMatches to Essential |
||||||
|
STEPS.replace_option(4, FOLDER_DELIMITER+"matches.f.bin", FOLDER_DELIMITER+"matches.e.bin") |
||||||
|
STEPS[4].opt.extend(["-g", "e"]) |
||||||
|
|
||||||
|
if 20 in CONF.steps: # TextureMesh |
||||||
|
if 19 not in CONF.steps: # RefineMesh |
||||||
|
# RefineMesh step is not run, use ReconstructMesh output |
||||||
|
STEPS.replace_option(20, "scene_dense_mesh_refine.ply", "scene_dense_mesh.ply") |
||||||
|
STEPS.replace_option(20, "scene_dense_mesh_refine_texture.mvs", "scene_dense_mesh_texture.mvs") |
||||||
|
|
||||||
|
for cstep in CONF.steps: |
||||||
|
printout("#%i. %s" % (cstep, STEPS[cstep].info), effect=INVERSE) |
||||||
|
|
||||||
|
# Retrieve "passthrough" commandline options |
||||||
|
options = getattr(CONF, str(cstep)) |
||||||
|
if options: |
||||||
|
# add - sign to short options and -- to long ones |
||||||
|
for o in range(0, len(options), 2): |
||||||
|
if len(options[o]) > 1: |
||||||
|
options[o] = '-' + options[o] |
||||||
|
options[o] = '-' + options[o] |
||||||
|
else: |
||||||
|
options = [] |
||||||
|
|
||||||
|
# Remove STEPS[cstep].opt options now defined in opt |
||||||
|
for anOpt in STEPS[cstep].opt: |
||||||
|
if anOpt in options: |
||||||
|
idx = STEPS[cstep].opt.index(anOpt) |
||||||
|
if DEBUGDEBUG_MODE_ENABLED: |
||||||
|
print('#\tRemove ' + str(anOpt) + ' from defaults options at id ' + str(idx)) |
||||||
|
del STEPS[cstep].opt[idx:idx+2] |
||||||
|
|
||||||
|
# create a commandline for the current step |
||||||
|
cmdline = [STEPS[cstep].cmd] + STEPS[cstep].opt + options |
||||||
|
print('CMD: ' + ' '.join(cmdline)) |
||||||
|
|
||||||
|
if not DEBUGDEBUG_MODE_ENABLED: |
||||||
|
# Launch the current step |
||||||
|
try: |
||||||
|
pStep = subprocess.Popen(cmdline) |
||||||
|
pStep.wait() |
||||||
|
if pStep.returncode != 0: |
||||||
|
break |
||||||
|
except KeyboardInterrupt: |
||||||
|
sys.exit('\r\nProcess canceled by user, all files remains') |
||||||
|
else: |
||||||
|
print('\t'.join(cmdline)) |
||||||
|
|
||||||
|
printout("# Pipeline end #", effect=INVERSE) |
||||||
@ -0,0 +1,77 @@ |
|||||||
|
#!/usr/bin/python3 |
||||||
|
# -*- encoding: utf-8 -*- |
||||||
|
""" |
||||||
|
This script is for comparing the poses stored in an OpenMVS project to the poses optimized by OpenMVG |
||||||
|
|
||||||
|
usage: run 'MvgOptimizeSfM.py' in a sub-folder to the OpenMVS project folder containing |
||||||
|
'scene.mvs' and images stored in 'images' folder; structure ex: |
||||||
|
|
||||||
|
-OpenMVS_project |
||||||
|
-images |
||||||
|
-scene.mvs |
||||||
|
-mvg |
||||||
|
-run script here |
||||||
|
""" |
||||||
|
|
||||||
|
import os |
||||||
|
import sys |
||||||
|
import subprocess |
||||||
|
|
||||||
|
if sys.platform.startswith('win'): |
||||||
|
PATH_DELIM = ';' |
||||||
|
else: |
||||||
|
PATH_DELIM = ':' |
||||||
|
|
||||||
|
# add this script's directory to PATH |
||||||
|
os.environ['PATH'] += PATH_DELIM + os.path.dirname(os.path.abspath(__file__)) |
||||||
|
|
||||||
|
# add current directory to PATH |
||||||
|
os.environ['PATH'] += PATH_DELIM + os.getcwd() |
||||||
|
|
||||||
|
|
||||||
|
def whereis(afile): |
||||||
|
""" |
||||||
|
return directory in which afile is, None if not found. Look in PATH |
||||||
|
""" |
||||||
|
if sys.platform.startswith('win'): |
||||||
|
cmd = "where" |
||||||
|
else: |
||||||
|
cmd = "which" |
||||||
|
try: |
||||||
|
ret = subprocess.run([cmd, afile], stdout=subprocess.PIPE, stderr=subprocess.STDOUT, check=True) |
||||||
|
return os.path.split(ret.stdout.decode())[0] |
||||||
|
except subprocess.CalledProcessError: |
||||||
|
return None |
||||||
|
|
||||||
|
|
||||||
|
def launch(cmdline): |
||||||
|
# Launch the current step |
||||||
|
print('Cmd: ' + ' '.join(cmdline)) |
||||||
|
try: |
||||||
|
pStep = subprocess.Popen(cmdline) |
||||||
|
pStep.wait() |
||||||
|
if pStep.returncode != 0: |
||||||
|
return |
||||||
|
except KeyboardInterrupt: |
||||||
|
sys.exit('\r\nProcess canceled by user, all files remains') |
||||||
|
|
||||||
|
|
||||||
|
# Try to find openMVG and openMVS binaries in PATH |
||||||
|
OPENMVG_BIN = whereis("openMVG_main_SfMInit_ImageListing") |
||||||
|
OPENMVS_BIN = whereis("ReconstructMesh") |
||||||
|
|
||||||
|
# Ask user for openMVG and openMVS directories if not found |
||||||
|
if not OPENMVG_BIN: |
||||||
|
OPENMVG_BIN = input("openMVG binary folder?\n") |
||||||
|
if not OPENMVS_BIN: |
||||||
|
OPENMVS_BIN = input("openMVS binary folder?\n") |
||||||
|
|
||||||
|
launch([os.path.join(OPENMVS_BIN, 'InterfaceCOLMAP'), '../scene.mvs', '-o', '../gt_dense_cameras.camera']) |
||||||
|
launch([os.path.join(OPENMVG_BIN, 'openMVG_main_SfMInit_ImageListingFromKnownPoses'), '-i', '../images', '-g', '../gt_dense_cameras', '-t', '1', '-o', '.']) |
||||||
|
launch([os.path.join(OPENMVG_BIN, 'openMVG_main_ComputeFeatures'), '-i', 'sfm_data.json', '-o', '.']) |
||||||
|
launch([os.path.join(OPENMVG_BIN, 'openMVG_main_ComputeMatches'), '-i', 'sfm_data.json', '-o', '.', '-m', '1']) |
||||||
|
launch([os.path.join(OPENMVG_BIN, 'openMVG_main_ComputeStructureFromKnownPoses'), '-i', 'sfm_data.json', '-m', '.', '-o', 'sfm_data_struct.bin', '-b']) |
||||||
|
launch([os.path.join(OPENMVG_BIN, 'openMVG_main_ComputeSfM_DataColor'), '-i', 'sfm_data_struct.bin', '-o', 'scene.ply']) |
||||||
|
launch([os.path.join(OPENMVG_BIN, 'openMVG_main_openMVG2openMVS'), '-i', 'sfm_data_struct.bin', '-o', 'scene.mvs', '-d', 'images']) |
||||||
|
launch([os.path.join(OPENMVS_BIN, 'InterfaceCOLMAP'), 'scene.mvs', '-o', 'cameras.camera']) |
||||||
|
launch([os.path.join(OPENMVG_BIN, 'openMVG_main_evalQuality'), '-i', '..', '-c', 'sfm_data_struct.bin', '-o', 'compare']) |
||||||
@ -0,0 +1,42 @@ |
|||||||
|
''' |
||||||
|
Example usage of MvsUtils.py for reading DMAP file content. |
||||||
|
|
||||||
|
usage: MvsReadDMAP.py [-h] [--input INPUT] [--output OUTPUT] |
||||||
|
''' |
||||||
|
|
||||||
|
from argparse import ArgumentParser |
||||||
|
from concurrent.futures import ProcessPoolExecutor |
||||||
|
from glob import glob |
||||||
|
from MvsUtils import loadDMAP |
||||||
|
import numpy as np |
||||||
|
import os |
||||||
|
import pyvips |
||||||
|
|
||||||
|
def exportDMAPContent(dmap_path): |
||||||
|
dmap = loadDMAP(dmap_path) |
||||||
|
|
||||||
|
basename = os.path.splitext(os.path.basename(dmap['file_name']))[0] |
||||||
|
|
||||||
|
pyvips.Image.new_from_array(np.uint8(dmap['depth_map'] * (1 / dmap['depth_max']) * 255)).write_to_file('%s_depth_map.png' % basename) |
||||||
|
if dmap['has_normal']: |
||||||
|
pyvips.Image.new_from_array(np.uint8((dmap['normal_map'] @ -dmap['R'] + 1) * 0.5 * 255)).write_to_file('%s_normal_map.png' % basename) |
||||||
|
if dmap['has_conf']: |
||||||
|
pyvips.Image.new_from_array(np.uint8(dmap['confidence_map'] * (1 / dmap['confidence_map'].max()) * 255)).write_to_file('%s_confidence_map.png' % basename) |
||||||
|
|
||||||
|
def main(): |
||||||
|
parser = ArgumentParser() |
||||||
|
parser.add_argument('-i', '--input', type=str, required=True, help='Path to the DMAP file directory') |
||||||
|
parser.add_argument('-t', '--threads', type=int, default=int(os.cpu_count() * 0.5) - 1, help='Number of parallel computations') |
||||||
|
parser.add_argument('-o', '--output', type=str, required=True, help='Path to the output directory') |
||||||
|
args = parser.parse_args() |
||||||
|
|
||||||
|
dmap_paths = glob(os.path.join(args.input, '*.dmap')) |
||||||
|
|
||||||
|
os.makedirs(args.output, exist_ok = True) |
||||||
|
os.chdir(args.output) |
||||||
|
|
||||||
|
with ProcessPoolExecutor(max_workers=args.threads) as executor: |
||||||
|
executor.map(exportDMAPContent, dmap_paths) |
||||||
|
|
||||||
|
if __name__ == '__main__': |
||||||
|
main() |
||||||
@ -0,0 +1,35 @@ |
|||||||
|
''' |
||||||
|
Example usage of MvsUtils.py for reading MVS interface archive content. |
||||||
|
|
||||||
|
usage: MvsReadMVS.py [-h] [--input INPUT] [--output OUTPUT] |
||||||
|
''' |
||||||
|
|
||||||
|
from argparse import ArgumentParser |
||||||
|
import json |
||||||
|
from MvsUtils import loadMVSInterface |
||||||
|
import os |
||||||
|
|
||||||
|
def main(): |
||||||
|
parser = ArgumentParser() |
||||||
|
parser.add_argument('-i', '--input', type=str, required=True, help='Path to the MVS interface archive') |
||||||
|
parser.add_argument('-o', '--output', type=str, required=True, help='Path to the output json file') |
||||||
|
args = parser.parse_args() |
||||||
|
|
||||||
|
mvs = loadMVSInterface(args.input) |
||||||
|
|
||||||
|
for platform_index in range(len(mvs['platforms'])): |
||||||
|
for camera_index in range(len(mvs['platforms'][platform_index]['cameras'])): |
||||||
|
camera = mvs['platforms'][platform_index]['cameras'][camera_index] |
||||||
|
image_max = max(camera['width'], camera['height']) |
||||||
|
fx = camera['K'][0][0] / image_max |
||||||
|
fy = camera['K'][1][1] / image_max |
||||||
|
poses_size = len(camera['poses']) |
||||||
|
print('Camera model loaded: platform {}; camera {}; f {:.3f}x{:.3f}; poses {}'.format(platform_index, camera_index, fx, fy, poses_size)) |
||||||
|
|
||||||
|
os.makedirs(os.path.dirname(args.output), exist_ok = True) |
||||||
|
|
||||||
|
with open(args.output, 'w') as file: |
||||||
|
json.dump(mvs, file, indent=2) |
||||||
|
|
||||||
|
if __name__ == '__main__': |
||||||
|
main() |
||||||
@ -0,0 +1,180 @@ |
|||||||
|
#!/usr/bin/python3 |
||||||
|
# -*- encoding: utf-8 -*- |
||||||
|
""" |
||||||
|
This script helps with OpenMVS scalable pipeline. |
||||||
|
|
||||||
|
Starting from a SfM solution stored into a MVS project accompanied by the undistorted images, |
||||||
|
the fist step is to compute all depth maps without fusion: |
||||||
|
|
||||||
|
DensifyPointCloud scene.mvs --fusion-mode 1 |
||||||
|
|
||||||
|
Next split the scene in sub-scenes using the area parameter, which is related to the inverse of GSD; |
||||||
|
it is a bit non intuitive, but normally it should remain constant for a desired memory limit; |
||||||
|
for example you can use the bellow value to limit memory usage to ~16GB: |
||||||
|
|
||||||
|
DensifyPointCloud scene.mvs --sub-scene-area 660000 |
||||||
|
|
||||||
|
disable depth-maps re-filtering by creating a file Densify.ini with just this line: |
||||||
|
|
||||||
|
Optimize = 0 |
||||||
|
|
||||||
|
and call fusion on each of the sub-scenes like: |
||||||
|
|
||||||
|
DensifyPointCloud scene_0000.mvs --dense-config-file Densify.ini |
||||||
|
............ |
||||||
|
DensifyPointCloud scene_000n.mvs --dense-config-file Densify.ini |
||||||
|
|
||||||
|
This script helps to automate the process of calling DensifyPointCloud/ReconstructMesh on all sub-scenes. |
||||||
|
|
||||||
|
usage: MvsScalablePipeline.py openMVS_module input_scene <options> |
||||||
|
|
||||||
|
ex: MvsScalablePipeline.py DensifyPointCloud scene_XXXX.mvs --number-views-fuse 2 |
||||||
|
""" |
||||||
|
|
||||||
|
import os |
||||||
|
import subprocess |
||||||
|
import sys |
||||||
|
import argparse |
||||||
|
import glob |
||||||
|
|
||||||
|
DEBUG = False |
||||||
|
|
||||||
|
if sys.platform.startswith('win'): |
||||||
|
PATH_DELIM = ';' |
||||||
|
FOLDER_DELIM = '\\' |
||||||
|
else: |
||||||
|
PATH_DELIM = ':' |
||||||
|
FOLDER_DELIM = '/' |
||||||
|
|
||||||
|
|
||||||
|
def whereis(afile): |
||||||
|
""" |
||||||
|
return directory in which afile is, None if not found. Look in PATH |
||||||
|
""" |
||||||
|
if sys.platform.startswith('win'): |
||||||
|
cmd = "where" |
||||||
|
else: |
||||||
|
cmd = "which" |
||||||
|
try: |
||||||
|
ret = subprocess.run([cmd, afile], stdout=subprocess.PIPE, stderr=subprocess.STDOUT, check=True) |
||||||
|
return os.path.split(ret.stdout.decode())[0] |
||||||
|
except subprocess.CalledProcessError: |
||||||
|
return None |
||||||
|
|
||||||
|
|
||||||
|
def find(afile): |
||||||
|
""" |
||||||
|
As whereis look only for executable on linux, this find look for all file type |
||||||
|
""" |
||||||
|
for d in os.environ['PATH'].split(PATH_DELIM): |
||||||
|
if os.path.isfile(os.path.join(d, afile)): |
||||||
|
return d |
||||||
|
return None |
||||||
|
|
||||||
|
# Try to find openMVS binaries in PATH |
||||||
|
OPENMVS_BIN = whereis("ReconstructMesh") |
||||||
|
|
||||||
|
# Ask user for openMVS directory if not found |
||||||
|
if not OPENMVS_BIN: |
||||||
|
OPENMVS_BIN = input("openMVS binary folder?\n") |
||||||
|
|
||||||
|
|
||||||
|
# HELPERS for terminal colors |
||||||
|
BLACK, RED, GREEN, YELLOW, BLUE, MAGENTA, CYAN, WHITE = range(8) |
||||||
|
NO_EFFECT, BOLD, UNDERLINE, BLINK, INVERSE, HIDDEN = (0, 1, 4, 5, 7, 8) |
||||||
|
|
||||||
|
|
||||||
|
# from Python cookbook, #475186 |
||||||
|
def has_colours(stream): |
||||||
|
''' |
||||||
|
Return stream colours capability |
||||||
|
''' |
||||||
|
if not hasattr(stream, "isatty"): |
||||||
|
return False |
||||||
|
if not stream.isatty(): |
||||||
|
return False # auto color only on TTYs |
||||||
|
try: |
||||||
|
import curses |
||||||
|
curses.setupterm() |
||||||
|
return curses.tigetnum("colors") > 2 |
||||||
|
except Exception: |
||||||
|
# guess false in case of error |
||||||
|
return False |
||||||
|
|
||||||
|
HAS_COLOURS = has_colours(sys.stdout) |
||||||
|
|
||||||
|
|
||||||
|
def printout(text, colour=WHITE, background=BLACK, effect=NO_EFFECT): |
||||||
|
""" |
||||||
|
print() with colour |
||||||
|
""" |
||||||
|
if HAS_COLOURS: |
||||||
|
seq = "\x1b[%d;%d;%dm" % (effect, 30+colour, 40+background) + text + "\x1b[0m" |
||||||
|
sys.stdout.write(seq+'\r\n') |
||||||
|
else: |
||||||
|
sys.stdout.write(text+'\r\n') |
||||||
|
|
||||||
|
|
||||||
|
# store config and data in |
||||||
|
class ConfContainer: |
||||||
|
""" |
||||||
|
Container for all the config variables |
||||||
|
""" |
||||||
|
def __init__(self): |
||||||
|
pass |
||||||
|
|
||||||
|
CONF = ConfContainer() |
||||||
|
|
||||||
|
# ARGS |
||||||
|
PARSER = argparse.ArgumentParser( |
||||||
|
formatter_class=argparse.RawTextHelpFormatter, |
||||||
|
description="Scalable MVS reconstruction with these steps: \r\n" + |
||||||
|
"MvsScalablePipeline.py openMVS_module input_scene <options>\r\n" |
||||||
|
) |
||||||
|
PARSER.add_argument('openMVS_module', |
||||||
|
help="the OpenMVS module to use: DensifyPointCloud, ReconstructMesh, etc.") |
||||||
|
PARSER.add_argument('input_scene', |
||||||
|
help="the scene name reg to process: scene_XXXX.mvs") |
||||||
|
PARSER.add_argument('passthrough', nargs=argparse.REMAINDER, help="Option to be passed to command lines") |
||||||
|
|
||||||
|
PARSER.parse_args(namespace=CONF) # store args in the ConfContainer |
||||||
|
|
||||||
|
suffix = os.path.basename(CONF.input_scene).replace('scene_XXXX','') |
||||||
|
CONF.input_scene = CONF.input_scene.replace('_dense','').replace('_mesh','').replace('_refine','').replace('_texture','') |
||||||
|
|
||||||
|
# Absolute path for input directory |
||||||
|
if len(CONF.input_scene) < 10 or CONF.input_scene[-9:] != '_XXXX.mvs': |
||||||
|
sys.exit("%s: invalid scene name" % CONF.input_scene) |
||||||
|
|
||||||
|
match CONF.openMVS_module: |
||||||
|
case 'ReconstructMesh': |
||||||
|
moduleSuffix = '_mesh.mvs' |
||||||
|
case 'RefineMesh': |
||||||
|
moduleSuffix = '_refine.mvs' |
||||||
|
case 'TextureMesh': |
||||||
|
moduleSuffix = '_texture.mvs' |
||||||
|
case _: |
||||||
|
moduleSuffix = '_dense.mvs' |
||||||
|
|
||||||
|
printout("# Module {} start #".format(CONF.openMVS_module), colour=RED, effect=BOLD) |
||||||
|
for scene_name in glob.glob(os.path.abspath(os.path.join(os.path.dirname(CONF.input_scene), 'scene_[0-9][0-9][0-9][0-9]'+suffix))): |
||||||
|
if os.path.exists(os.path.splitext(scene_name)[0] + moduleSuffix) == False: |
||||||
|
printout("# Process: %s" % os.path.basename(scene_name), colour=GREEN, effect=NO_EFFECT) |
||||||
|
|
||||||
|
# create a commandline for the current step |
||||||
|
cmdline = [os.path.join(OPENMVS_BIN, CONF.openMVS_module), scene_name] + CONF.passthrough |
||||||
|
print('Cmd: ' + ' '.join(cmdline)) |
||||||
|
|
||||||
|
if not DEBUG: |
||||||
|
# Launch the current step |
||||||
|
try: |
||||||
|
pStep = subprocess.Popen(cmdline) |
||||||
|
pStep.wait() |
||||||
|
if pStep.returncode != 0: |
||||||
|
printout("# Warning: step failed", colour=RED, effect=BOLD) |
||||||
|
except KeyboardInterrupt: |
||||||
|
sys.exit('\r\nProcess canceled by user, all files remains') |
||||||
|
else: |
||||||
|
print('\t'.join(cmdline)) |
||||||
|
|
||||||
|
printout("# Module {} end #".format(CONF.openMVS_module), colour=RED, effect=BOLD) |
||||||
@ -0,0 +1,190 @@ |
|||||||
|
''' |
||||||
|
OpenMVS python utilities. |
||||||
|
|
||||||
|
E.g., from MvsUtils import loadDMAP, loadMVSInterface |
||||||
|
''' |
||||||
|
|
||||||
|
import numpy as np |
||||||
|
|
||||||
|
def loadDMAP(dmap_path): |
||||||
|
with open(dmap_path, 'rb') as dmap: |
||||||
|
file_type = dmap.read(2).decode() |
||||||
|
content_type = np.frombuffer(dmap.read(1), dtype=np.dtype('B')) |
||||||
|
reserve = np.frombuffer(dmap.read(1), dtype=np.dtype('B')) |
||||||
|
|
||||||
|
has_depth = content_type > 0 |
||||||
|
has_normal = content_type in [3, 7, 11, 15] |
||||||
|
has_conf = content_type in [5, 7, 13, 15] |
||||||
|
has_views = content_type in [9, 11, 13, 15] |
||||||
|
|
||||||
|
image_width, image_height = np.frombuffer(dmap.read(8), dtype=np.dtype('I')) |
||||||
|
depth_width, depth_height = np.frombuffer(dmap.read(8), dtype=np.dtype('I')) |
||||||
|
|
||||||
|
if (file_type != 'DR' or has_depth == False or depth_width <= 0 or depth_height <= 0 or image_width < depth_width or image_height < depth_height): |
||||||
|
print('error: opening file \'{}\' for reading depth-data'.format(dmap_path)) |
||||||
|
return |
||||||
|
|
||||||
|
depth_min, depth_max = np.frombuffer(dmap.read(8), dtype=np.dtype('f')) |
||||||
|
|
||||||
|
file_name_size = np.frombuffer(dmap.read(2), dtype=np.dtype('H'))[0] |
||||||
|
file_name = dmap.read(file_name_size).decode() |
||||||
|
|
||||||
|
view_ids_size = np.frombuffer(dmap.read(4), dtype=np.dtype('I'))[0] |
||||||
|
reference_view_id, *neighbor_view_ids = np.frombuffer(dmap.read(4 * view_ids_size), dtype=np.dtype('I')) |
||||||
|
|
||||||
|
K = np.frombuffer(dmap.read(72), dtype=np.dtype('d')).reshape(3, 3) |
||||||
|
R = np.frombuffer(dmap.read(72), dtype=np.dtype('d')).reshape(3, 3) |
||||||
|
C = np.frombuffer(dmap.read(24), dtype=np.dtype('d')) |
||||||
|
|
||||||
|
data = { |
||||||
|
'has_normal': has_normal, |
||||||
|
'has_conf': has_conf, |
||||||
|
'has_views': has_views, |
||||||
|
'image_width': image_width, |
||||||
|
'image_height': image_height, |
||||||
|
'depth_width': depth_width, |
||||||
|
'depth_height': depth_height, |
||||||
|
'depth_min': depth_min, |
||||||
|
'depth_max': depth_max, |
||||||
|
'file_name': file_name, |
||||||
|
'reference_view_id': reference_view_id, |
||||||
|
'neighbor_view_ids': neighbor_view_ids, |
||||||
|
'K': K, |
||||||
|
'R': R, |
||||||
|
'C': C |
||||||
|
} |
||||||
|
|
||||||
|
map_size = depth_width * depth_height |
||||||
|
depth_map = np.frombuffer(dmap.read(4 * map_size), dtype=np.dtype('f')).reshape(depth_height, depth_width) |
||||||
|
data.update({'depth_map': depth_map}) |
||||||
|
if has_normal: |
||||||
|
normal_map = np.frombuffer(dmap.read(4 * map_size * 3), dtype=np.dtype('f')).reshape(depth_height, depth_width, 3) |
||||||
|
data.update({'normal_map': normal_map}) |
||||||
|
if has_conf: |
||||||
|
confidence_map = np.frombuffer(dmap.read(4 * map_size), dtype=np.dtype('f')).reshape(depth_height, depth_width) |
||||||
|
data.update({'confidence_map': confidence_map}) |
||||||
|
if has_views: |
||||||
|
views_map = np.frombuffer(dmap.read(map_size * 4), dtype=np.dtype('B')).reshape(depth_height, depth_width, 4) |
||||||
|
data.update({'views_map': views_map}) |
||||||
|
|
||||||
|
return data |
||||||
|
|
||||||
|
def loadMVSInterface(archive_path): |
||||||
|
with open(archive_path, 'rb') as mvs: |
||||||
|
archive_type = mvs.read(4).decode() |
||||||
|
version = np.frombuffer(mvs.read(4), dtype=np.dtype('I')).tolist()[0] |
||||||
|
reserve = np.frombuffer(mvs.read(4), dtype=np.dtype('I')) |
||||||
|
|
||||||
|
if archive_type != 'MVSI': |
||||||
|
print('error: opening file \'{}\''.format(archive_path)) |
||||||
|
return |
||||||
|
|
||||||
|
data = { |
||||||
|
'project_stream': archive_type, |
||||||
|
'project_stream_version': version, |
||||||
|
'platforms': [], |
||||||
|
'images': [], |
||||||
|
'vertices': [], |
||||||
|
'vertices_normal': [], |
||||||
|
'vertices_color': [] |
||||||
|
} |
||||||
|
|
||||||
|
platforms_size = np.frombuffer(mvs.read(8), dtype=np.dtype('Q'))[0] |
||||||
|
for platform_index in range(platforms_size): |
||||||
|
platform_name_size = np.frombuffer(mvs.read(8), dtype=np.dtype('Q'))[0] |
||||||
|
platform_name = mvs.read(platform_name_size).decode() |
||||||
|
data['platforms'].append({'name': platform_name, 'cameras': []}) |
||||||
|
cameras_size = np.frombuffer(mvs.read(8), dtype=np.dtype('Q'))[0] |
||||||
|
for camera_index in range(cameras_size): |
||||||
|
camera_name_size = np.frombuffer(mvs.read(8), dtype=np.dtype('Q'))[0] |
||||||
|
camera_name = mvs.read(camera_name_size).decode() |
||||||
|
data['platforms'][platform_index]['cameras'].append({'name': camera_name}) |
||||||
|
if version > 3: |
||||||
|
band_name_size = np.frombuffer(mvs.read(8), dtype=np.dtype('Q'))[0] |
||||||
|
band_name = mvs.read(band_name_size).decode() |
||||||
|
data['platforms'][platform_index]['cameras'][camera_index].update({'band_name': band_name}) |
||||||
|
if version > 0: |
||||||
|
width, height = np.frombuffer(mvs.read(8), dtype=np.dtype('I')).tolist() |
||||||
|
data['platforms'][platform_index]['cameras'][camera_index].update({'width': width, 'height': height}) |
||||||
|
K = np.asarray(np.frombuffer(mvs.read(72), dtype=np.dtype('d'))).reshape(3, 3).tolist() |
||||||
|
data['platforms'][platform_index]['cameras'][camera_index].update({'K': K, 'poses': []}) |
||||||
|
identity_matrix = np.asarray(np.frombuffer(mvs.read(96), dtype=np.dtype('d'))).reshape(4, 3) |
||||||
|
poses_size = np.frombuffer(mvs.read(8), dtype=np.dtype('Q'))[0] |
||||||
|
for _ in range(poses_size): |
||||||
|
R = np.asarray(np.frombuffer(mvs.read(72), dtype=np.dtype('d'))).reshape(3, 3).tolist() |
||||||
|
C = np.asarray(np.frombuffer(mvs.read(24), dtype=np.dtype('d'))).tolist() |
||||||
|
data['platforms'][platform_index]['cameras'][camera_index]['poses'].append({'R': R, 'C': C}) |
||||||
|
|
||||||
|
images_size = np.frombuffer(mvs.read(8), dtype=np.dtype('Q'))[0] |
||||||
|
for image_index in range(images_size): |
||||||
|
name_size = np.frombuffer(mvs.read(8), dtype=np.dtype('Q'))[0] |
||||||
|
name = mvs.read(name_size).decode() |
||||||
|
data['images'].append({'name': name}) |
||||||
|
if version > 4: |
||||||
|
mask_name_size = np.frombuffer(mvs.read(8), dtype=np.dtype('Q'))[0] |
||||||
|
mask_name = mvs.read(mask_name_size).decode() |
||||||
|
data['images'][image_index].update({'mask_name': mask_name}) |
||||||
|
platform_id, camera_id, pose_id = np.frombuffer(mvs.read(12), dtype=np.dtype('I')).tolist() |
||||||
|
data['images'][image_index].update({'platform_id': platform_id, 'camera_id': camera_id, 'pose_id': pose_id}) |
||||||
|
if version > 2: |
||||||
|
id = np.frombuffer(mvs.read(4), dtype=np.dtype('I')).tolist()[0] |
||||||
|
data['images'][image_index].update({'id': id}) |
||||||
|
if version > 6: |
||||||
|
min_depth, avg_depth, max_depth = np.frombuffer(mvs.read(12), dtype=np.dtype('f')).tolist() |
||||||
|
data['images'][image_index].update({'min_depth': min_depth, 'avg_depth': avg_depth, 'max_depth': max_depth, 'view_scores': []}) |
||||||
|
view_score_size = np.frombuffer(mvs.read(8), dtype=np.dtype('Q'))[0] |
||||||
|
for _ in range(view_score_size): |
||||||
|
id, points = np.frombuffer(mvs.read(8), dtype=np.dtype('I')).tolist() |
||||||
|
scale, angle, area, score = np.frombuffer(mvs.read(16), dtype=np.dtype('f')).tolist() |
||||||
|
data['images'][image_index]['view_scores'].append({'id': id, 'points': points, 'scale': scale, 'angle': angle, 'area': area, 'score': score}) |
||||||
|
|
||||||
|
vertices_size = np.frombuffer(mvs.read(8), dtype=np.dtype('Q'))[0] |
||||||
|
for vertex_index in range(vertices_size): |
||||||
|
X = np.frombuffer(mvs.read(12), dtype=np.dtype('f')).tolist() |
||||||
|
data['vertices'].append({'X': X, 'views': []}) |
||||||
|
views_size = np.frombuffer(mvs.read(8), dtype=np.dtype('Q'))[0] |
||||||
|
for _ in range(views_size): |
||||||
|
image_id = np.frombuffer(mvs.read(4), dtype=np.dtype('I')).tolist()[0] |
||||||
|
confidence = np.frombuffer(mvs.read(4), dtype=np.dtype('f')).tolist()[0] |
||||||
|
data['vertices'][vertex_index]['views'].append({'image_id': image_id, 'confidence': confidence}) |
||||||
|
|
||||||
|
vertices_normal_size = np.frombuffer(mvs.read(8), dtype=np.dtype('Q'))[0] |
||||||
|
for _ in range(vertices_normal_size): |
||||||
|
normal = np.frombuffer(mvs.read(12), dtype=np.dtype('f')).tolist() |
||||||
|
data['vertices_normal'].append(normal) |
||||||
|
|
||||||
|
vertices_color_size = np.frombuffer(mvs.read(8), dtype=np.dtype('Q'))[0] |
||||||
|
for _ in range(vertices_color_size): |
||||||
|
color = np.frombuffer(mvs.read(3), dtype=np.dtype('B')).tolist() |
||||||
|
data['vertices_color'].append(color) |
||||||
|
|
||||||
|
if version > 0: |
||||||
|
data.update({'lines': [], 'lines_normal': [], 'lines_color': []}) |
||||||
|
lines_size = np.frombuffer(mvs.read(8), dtype=np.dtype('Q'))[0] |
||||||
|
for line_index in range(lines_size): |
||||||
|
pt1 = np.frombuffer(mvs.read(12), dtype=np.dtype('f')).tolist() |
||||||
|
pt2 = np.frombuffer(mvs.read(12), dtype=np.dtype('f')).tolist() |
||||||
|
data['lines'].append({'pt1': pt1, 'pt2': pt2, 'views': []}) |
||||||
|
views_size = np.frombuffer(mvs.read(8), dtype=np.dtype('Q'))[0] |
||||||
|
for _ in range(views_size): |
||||||
|
image_id = np.frombuffer(mvs.read(4), dtype=np.dtype('I')).tolist()[0] |
||||||
|
confidence = np.frombuffer(mvs.read(4), dtype=np.dtype('f')).tolist()[0] |
||||||
|
data['lines'][line_index]['views'].append({'image_id': image_id, 'confidence': confidence}) |
||||||
|
lines_normal_size = np.frombuffer(mvs.read(8), dtype=np.dtype('Q'))[0] |
||||||
|
for _ in range(lines_normal_size): |
||||||
|
normal = np.frombuffer(mvs.read(12), dtype=np.dtype('f')).tolist() |
||||||
|
data['lines_normal'].append(normal) |
||||||
|
lines_color_size = np.frombuffer(mvs.read(8), dtype=np.dtype('Q'))[0] |
||||||
|
for _ in range(lines_color_size): |
||||||
|
color = np.frombuffer(mvs.read(3), dtype=np.dtype('B')).tolist() |
||||||
|
data['lines_color'].append(color) |
||||||
|
if version > 1: |
||||||
|
transform = np.frombuffer(mvs.read(128), dtype=np.dtype('d')).reshape(4, 4).tolist() |
||||||
|
data.update({'transform': transform}) |
||||||
|
if version > 5: |
||||||
|
rot = np.frombuffer(mvs.read(72), dtype=np.dtype('d')).reshape(3, 3).tolist() |
||||||
|
pt_min = np.frombuffer(mvs.read(24), dtype=np.dtype('d')).tolist() |
||||||
|
pt_max = np.frombuffer(mvs.read(24), dtype=np.dtype('d')).tolist() |
||||||
|
data.update({'obb': {'rot': rot, 'pt_min': pt_min, 'pt_max': pt_max}}) |
||||||
|
|
||||||
|
return data |
||||||
@ -0,0 +1,126 @@ |
|||||||
|
import bpy, sys, time, math |
||||||
|
|
||||||
|
def clear_default_objects(): |
||||||
|
for name in ["Cube", "Light", "Camera"]: |
||||||
|
if obj := bpy.data.objects.get(name): |
||||||
|
bpy.data.objects.remove(obj) |
||||||
|
|
||||||
|
def mark_sharp_edges(obj, angle=30): |
||||||
|
bpy.context.view_layer.objects.active = obj |
||||||
|
bpy.ops.object.mode_set(mode='EDIT') |
||||||
|
bpy.ops.mesh.select_all(action='SELECT') |
||||||
|
# 标记30°以上的边为锐边 |
||||||
|
bpy.ops.mesh.edges_select_sharp(sharpness=math.radians(angle)) |
||||||
|
bpy.ops.mesh.mark_sharp() |
||||||
|
bpy.ops.object.mode_set(mode='OBJECT') |
||||||
|
|
||||||
|
def planar_decimate(obj, angle_limit=35.0, ratio=0.5, protect_uv=True): |
||||||
|
"""使用Decimate修改器+智能参数配置""" |
||||||
|
print(f"启动高级减面流程 | 模式: 平面优化+权重控制") |
||||||
|
|
||||||
|
#""" |
||||||
|
# 添加Decimate修改器（平面模式） |
||||||
|
mod = obj.modifiers.new(name="PlanarDecimate", type='DECIMATE') |
||||||
|
mod.decimate_type = 'DISSOLVE' # 平面溶解模式 |
||||||
|
mod.angle_limit = math.radians(angle_limit) # 角度转弧度 |
||||||
|
mod.use_dissolve_boundaries = False # 溶解边界防止破面[5](@ref) |
||||||
|
#""" |
||||||
|
|
||||||
|
""" |
||||||
|
mod = obj.modifiers.new(name="CollapseDecimate", type='DECIMATE') |
||||||
|
mod.decimate_type = 'COLLAPSE' |
||||||
|
mod.ratio = 0.1 # 保留30%面数 |
||||||
|
mod.use_symmetry = True |
||||||
|
mod.vertex_group = "high_detail" # 绑定顶点组保护细节区域 |
||||||
|
#""" |
||||||
|
|
||||||
|
# 保护关键属性 |
||||||
|
mod.delimit = {'NORMAL', 'UV'} if protect_uv else {'NORMAL'} # UV保护[1](@ref) |
||||||
|
mod.use_symmetry = True # 对称保护[1](@ref) |
||||||
|
|
||||||
|
# 保护边界：创建顶点组标记轮廓边 |
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|
if "boundary_edges" not in obj.vertex_groups: |
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obj.vertex_groups.new(name="boundary_edges") |
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mod.vertex_group = "boundary_edges" |
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mod.invert_vertex_group = True # 仅减非边界区域 |
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|
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# 应用修改器 |
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bpy.context.view_layer.objects.active = obj |
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bpy.ops.object.modifier_apply(modifier=mod.name) |
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print(f"平面优化完成 | 容差角: {angle_limit}°") |
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|
|
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|
def collapse_decimate(obj, ratio=0.3, protect_groups=True): |
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|
"""核心减面：Collapse模式+细节保护""" |
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|
mod = obj.modifiers.new(name="CollapseDecimate", type='DECIMATE') |
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|
mod.decimate_type = 'COLLAPSE' |
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|
mod.ratio = ratio |
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|
|
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|
# 顶点组保护（需提前在Blender中标记高细节区域）[1](@ref) |
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|
if protect_groups and "high_detail" in obj.vertex_groups: |
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|
mod.vertex_group = "high_detail" |
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|
mod.invert_vertex_group = True # 仅减非保护区域 |
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|
print("启用顶点组保护 | 保留高细节区域") |
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|
|
||||||
|
# 关键保护设置 |
||||||
|
mod.use_symmetry = True |
||||||
|
|
||||||
|
bpy.ops.object.modifier_apply(modifier=mod.name) |
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|
print(f"塌陷减面完成 | 保留比例: {ratio*100}%") |
||||||
|
|
||||||
|
def triangulate_mesh(obj, quad_method='BEAUTY', ngon_method='BEAUTY'): |
||||||
|
"""将模型三角化[1,2](@ref)""" |
||||||
|
print("启动三角化处理...") |
||||||
|
|
||||||
|
# 添加三角化修改器 |
||||||
|
mod = obj.modifiers.new(name="Triangulate", type='TRIANGULATE') |
||||||
|
mod.quad_method = quad_method # 四边形处理方法 |
||||||
|
mod.ngon_method = ngon_method # 多边形处理方法 |
||||||
|
mod.min_vertices = 4 # 对四边形及以上面进行三角化 |
||||||
|
|
||||||
|
# 应用修改器 |
||||||
|
bpy.context.view_layer.objects.active = obj |
||||||
|
bpy.ops.object.modifier_apply(modifier=mod.name) |
||||||
|
|
||||||
|
# 验证三角化结果 |
||||||
|
tris = sum(1 for poly in obj.data.polygons if len(poly.vertices) == 3) |
||||||
|
total_faces = len(obj.data.polygons) |
||||||
|
print(f"三角化完成 | 三角面比例: {tris/total_faces*100:.1f}% ({tris}/{total_faces})") |
||||||
|
|
||||||
|
def optimize_geometry(obj): |
||||||
|
"""后处理：清理拓扑+法线修复[1,6](@ref)""" |
||||||
|
bpy.context.view_layer.objects.active = obj |
||||||
|
bpy.ops.object.mode_set(mode='EDIT') |
||||||
|
bpy.ops.mesh.remove_doubles(threshold=0.001) # 合并重复顶点 |
||||||
|
bpy.ops.mesh.normals_make_consistent() # 统一法线 |
||||||
|
bpy.ops.object.mode_set(mode='OBJECT') |
||||||
|
print("拓扑清理完成 | 法线已重计算") |
||||||
|
|
||||||
|
if __name__ == "__main__": |
||||||
|
argv = sys.argv[sys.argv.index("--") + 1:] |
||||||
|
input_path = argv[0] |
||||||
|
angle_limit = float(argv[1]) if len(argv) > 1 else 5.0 |
||||||
|
output_path = argv[2] if len(argv) > 2 else input_path.replace(".ply", "_decimated.ply") |
||||||
|
|
||||||
|
# 硬件加速配置 |
||||||
|
# bpy.context.scene.cycles.device = 'GPU' |
||||||
|
# bpy.context.preferences.system.memory_cache_limit = 4096 |
||||||
|
|
||||||
|
clear_default_objects() |
||||||
|
# 导入PLY模型 |
||||||
|
bpy.ops.wm.ply_import(filepath=input_path) |
||||||
|
obj = bpy.context.selected_objects[0] |
||||||
|
print(f"开始减面操作：{obj.name}") |
||||||
|
|
||||||
|
# 执行减面 |
||||||
|
mark_sharp_edges(obj) |
||||||
|
planar_decimate(obj, angle_limit) # 先平面优化 |
||||||
|
collapse_decimate(obj, ratio=0.2) # 再智能塌陷 // 0.1-3效果好，0.2-3综合不错 |
||||||
|
optimize_geometry(obj) # 最终清理 |
||||||
|
triangulate_mesh(obj) |
||||||
|
print("减面完成") |
||||||
|
|
||||||
|
bpy.ops.wm.ply_export( |
||||||
|
filepath=output_path, |
||||||
|
apply_modifiers=False |
||||||
|
) |
||||||
|
print(f"模型已导出至：{output_path}") |
||||||
@ -0,0 +1,10 @@ |
|||||||
|
cd ~/code/openMVS/make |
||||||
|
cmake -DCMAKE_BUILD_TYPE=Release -DCMAKE_PREFIX_PATH=/lib --build .. |
||||||
|
make -j20 && make install |
||||||
|
#cmake --build . -j4 |
||||||
|
#cmake --install . |
||||||
|
cd ~/code/openMVS/scripts/python |
||||||
|
#InterfaceCOLMAP -i /data/datasets/scan1/output/sfm/dense -o scene.mvs --image-folder /data/datasets/scan1/output/sfm/dense/images -w "/data/datasets/scan1/output/mvs" |
||||||
|
#TextureMesh scene_dense.mvs -m scene_dense_mesh.ply -o scene_dense_mesh_texture.mvs --decimate 0.5 -w "/data/datasets/scan1/output2" |
||||||
|
# TextureMesh /data/datasets/66536 --image-folder /data/datasets/66536/images/ -m /data/datasets/66536/gsmodel/train/ours_15000/waterobj/final.ply -o mesh.mvs --decimate 0.1 -w "/data/datasets/66536" --virtual-face-images 3 |
||||||
|
# TextureMesh /data/datasets/work_dir/227124 --image-folder /data/datasets/work_dir/227124/images/ -m /data/datasets/work_dir/227124/gsmodel/train/ours_16000/waterobj/final.ply -o mesh.mvs --outlier-threshold 0.1 --decimate 0.05 --sharpness-weight 0.2 -w /data/datasets/work_dir/227124/gsmodel/train/ours_16000/mesh/ --virtual-face-images 3 --patch-packing-heuristic 0 --max-texture-size 0 |
||||||
Loading…
Reference in new issue