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Author: zhao-wk

reconstruction_Colmap.py

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+from pathlib import Path
+from hloc import extract_features, match_features, reconstruction, visualization, pairs_from_retrieval
+import os
+import shutil as shutil
+
+
+def ReconstructionFromImages(pathstring, num_matched=5):
+    pathstring += "/"
+    imagesstring = pathstring + 'images'
+    images = Path(imagesstring)
+    pathoutputsstring = pathstring + 'output/'
+    outputs = Path(pathoutputsstring)
+    sfm_pairs = outputs / 'pairs-netvlad.txt'
+    pathsfm_dirstring = pathoutputsstring + 'sparse'
+    sfm_dir = outputs / 'sparse'
+
+    retrieval_conf = extract_features.confs['netvlad']
+    feature_conf = extract_features.confs['superpoint_max']
+    matcher_conf = match_features.confs['superglue']
+
+    retrieval_path = extract_features.main(retrieval_conf, images, outputs)
+    pairs_from_retrieval.main(retrieval_path, sfm_pairs, num_matched=num_matched)  # 5 xujx update
+
+    feature_path = extract_features.main(feature_conf, images, outputs)
+
+    match_path = match_features.main(matcher_conf, sfm_pairs, feature_conf['output'], outputs)
+
+    reconstruction.main(sfm_dir, images, sfm_pairs, feature_path, match_path) #min_match_score=0.7
+
+    dense_path = pathoutputsstring + "dense"
+    dense_mask_path = pathoutputsstring + "dense_mask"
+    converter = "colmap image_undistorter --image_path " + imagesstring + " --output_path " + dense_path + " --input_path " + pathsfm_dirstring
+    converter = converter + "\n"
+
+    imagesstring_mask = pathstring + 'images-mask'
+    converter = converter + "colmap image_undistorter --image_path " + imagesstring_mask + " --output_path " + dense_mask_path + " --input_path " + pathsfm_dirstring
+    converter = converter + "\n"
+
+    converter = converter + "colmap patch_match_stereo --workspace_path " + dense_path
+    converter = converter + "\n"
+
+    converter = converter + "colmap stereo_fusion --workspace_path " + dense_path + " --output_path " + dense_path + "/fused-rgb.ply"
+    converter = converter + "\n"
+    os.system(converter)
+
+    shutil.move(dense_path + '/images', dense_path + '/images-rgb')
+    shutil.copytree(dense_mask_path + '/images', dense_path + '/images')
+
+    converter = "colmap stereo_fusion --workspace_path " + dense_path + " --output_path " + dense_path + "/fused-mask.ply"
+
+    shutil.rmtree(dense_mask_path)
+
+    os.system(converter)
+
+    return 0
+
+

reconstruction_OpenMVS.py

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+# data_folder_Structure
+# ├── mask
+# │   ├── 0000000000.png
+# │   ├── 0000000001.png
+# │   ├── ...
+# ├── other
+# │   ├── 0000000000.png
+# │   ├── 0000000001.png
+# │   ├── ...
+# ├── output
+
+from pathlib import Path
+import os
+import tkinter as tk
+from tkinter import filedialog
+from datetime import datetime
+import calculate_zoom as calz
+import noiseReduction as nr
+
+def reconstrucionFromImages(pathstring):
+    # pathstring = "/media/xujx/MyPassport/sfm-pro/20221028-1-T154-0/"
+
+    pathstring += "/"
+    mask_dir_string = os.path.join(pathstring, 'mask')
+    other_dir_string = os.path.join(pathstring, 'other')
+    path_outputs_string = os.path.join(pathstring, 'output/')
+
+    # openMVS
+    converter = "cd /usr/local/bin/OpenMVS"
+    converter = converter + "\n"
+
+    converter = converter + "./InterfaceCOLMAP -i "
+    converter = converter + path_outputs_string
+    converter = converter + " -o "
+    converter = converter + path_outputs_string + "scene_panicle.mvs"
+    converter = converter + " --image-folder "
+    converter = converter + mask_dir_string
+    converter = converter + "\n"
+
+    converter = converter + "./DensifyPointCloud -w "
+    converter = converter + path_outputs_string
+    converter = converter + " -i scene_panicle.mvs -o panicle.mvs --remove-dmaps 1"
+    converter = converter + "\n"
+
+    converter = converter + "./InterfaceCOLMAP -i "
+    converter = converter + path_outputs_string
+    converter = converter + " -o "
+    converter = converter + path_outputs_string + "scene_other.mvs"
+    converter = converter + " --image-folder "
+    converter = converter + other_dir_string
+    converter = converter + "\n"
+
+    converter = converter + "./DensifyPointCloud -w "
+    converter = converter + path_outputs_string
+    converter = converter + " -i scene_other.mvs -o other.mvs --remove-dmaps 1"
+    converter = converter + "\n"
+
+    os.system(converter)
+
+    return 0
+
+def process_folders(root_path, folder):
+    folder_path = os.path.join(root_path, folder)
+    video_folder_path = folder_path
+    images_output_path = os.path.join(folder_path, 'images')
+
+    if os.path.exists(video_folder_path) and os.path.isdir(video_folder_path):
+        # 创建images文件夹，如果不存在
+        if not os.path.exists(images_output_path):
+            os.makedirs(images_output_path)
+        for video_name in os.listdir(video_folder_path):
+            video_file_path = os.path.join(video_folder_path, video_name)
+            video_to_frames(video_file_path, images_output_path)
+
+def check_dense_scene_ply(folder_path):
+    ply_file_path = os.path.join(folder_path, 'output', 'dense_scene.ply')
+    return os.path.exists(ply_file_path)
+
+def traverse_folders(root_path):
+    folders_to_exclude = []
+    # check
+    for folder_name in os.listdir(root_path):
+        folder_path = os.path.join(root_path, folder_name)
+        if os.path.isdir(folder_path) and check_dense_scene_ply(folder_path):
+            print(f"Excluding folder name: {folder_name}")
+            folders_to_exclude.append(folder_name)
+
+    filtered_folders = [folder_name for folder_name in os.listdir(root_path) if folder_name not in folders_to_exclude]
+    return filtered_folders
+
+if __name__ == '__main__':
+
+    path = '/your/path'
+    reconstrucionFromImages(path)
+