从 Metashape 到 3DGS：Colmap 格式数据导出全流程，轻松实现高质量重建_metashape 3dgs
一、功能概述
高精度格式转换
将 Metashape 摄影测量数据转换为 Colmap 标准格式，支持：
1.相机模型：完整导出 PINHOLE/SIMPLE_PINHOLE 内参模型
2.位姿表达：四元数 + 平移向量的外参精确映射
3.图像预处理：全自动畸变校正与重投影
4.点云数据：带 RGB 信息的稀疏点云（支持百万级特征点）
二、核心功能细节
1.全维度数据导出
★相机参数（内参矩阵 + 畸变系数）
★位姿矩阵（旋转四元数 + 平移向量）
★校正后图像（支持 JPEG/PNG 多格式）
★带色点云（XYZ+RGB 格式）
★特征点关联关系（tracks 信息）
输出规范：
支持 .txt/.bin/.ply 多格式输出
2.智能参数配置（GUI 可视化）
导出策略：
▶支持按 Chunk/Frame 维度灵活筛选
▶提供 “全部数据” / “选中区域” 两种模式
坐标系统优化：
▶局部坐标系转换（解决大尺度场景坐标溢出问题）
▶零主点校准（专为高斯 splatting 优化相机参数）
质量控制：
▶JPEG 质量可调（0-100 动态范围）
▶自动过滤无效投影点（提升下游重建成功率）
3.全自动工作流
目录结构：
自动创建 images/、sparse/0/ 等标准 Colmap 目录
输出根目录/
├── 区块1名称/│ ├── images/│ │ ├── 原始图像1│ │ ├── 原始图像2│ │ └── ...│ ├── masks/│ │ ├── 原始图像1│ │ └── ...│ └── sparse/0/│ ├── cameras.bin│ ├── cameras.txt│ ├── images.bin│ ├── images.txt│ ├── points3D.bin│ ├── points3D.txt│ └── points3D.ply├── 区块2名称/│ └── ...（结构同上）└── ...畸变处理：
★基于 Metashape 标定参数的逆向畸变计算
★支持鱼眼 / 广角等特殊镜头模型转换
三、使用说明
环境依赖:
# 核心依赖（推荐安装方式） pip install pyside2 numpy opencv-python 宿主软件：Agisoft Metashape Pro v1.8+（需激活 Python API）
安装步骤:
1.将脚本复制至 Metashape 安装目录
Metashape Pro/resources/scripts/ExportColmap.py 2.或通过软件菜单动态加载：
Tools → Run Script → 选择脚本文件
代码
import osimport shutilimport structimport mathfrom PySide2 import QtGui, QtCore, QtWidgetsf32 = lambda x: bytes(struct.pack(\"f\", x))d64 = lambda x: bytes(struct.pack(\"d\", x))u8 = lambda x: x.to_bytes(1, \"little\", signed=(x < 0))u32 = lambda x: x.to_bytes(4, \"little\", signed=(x < 0))u64 = lambda x: x.to_bytes(8, \"little\", signed=(x < 0))bstr = lambda x: bytes((x + \"\\0\"), \"utf-8\")def matrix_to_quat(m): tr = m[0, 0] + m[1, 1] + m[2, 2] if (tr > 0): s = 2 * math.sqrt(tr + 1) return Metashape.Vector([(m[2, 1] - m[1, 2]) / s, (m[0, 2] - m[2, 0]) / s, (m[1, 0] - m[0, 1]) / s, 0.25 * s]) if (m[0, 0] > m[1, 1]) and (m[0, 0] > m[2, 2]): s = 2 * math.sqrt(1 + m[0, 0] - m[1, 1] - m[2, 2]) return Metashape.Vector([0.25 * s, (m[0, 1] + m[1, 0]) / s, (m[0, 2] + m[2, 0]) / s, (m[2, 1] - m[1, 2]) / s]) if (m[1, 1] > m[2, 2]): s = 2 * math.sqrt(1 + m[1, 1] - m[0, 0] - m[2, 2]) return Metashape.Vector([(m[0, 1] + m[1, 0]) / s, 0.25 * s, (m[1, 2] + m[2, 1]) / s, (m[0, 2] - m[2, 0]) / s]) else: s = 2 * math.sqrt(1 + m[2, 2] - m[0, 0] - m[1, 1]) return Metashape.Vector([(m[0, 2] + m[2, 0]) / s, (m[1, 2] + m[2, 1]) / s, 0.25 * s, (m[1, 0] - m[0, 1]) / s])def get_camera_name(cam): name = cam.label ext = os.path.splitext(name) if (len(ext[1]) == 0): name = ext[0] + os.path.splitext(cam.photo.path)[1] return namedef clean_dir(folder, confirm_deletion): if os.path.exists(folder): if confirm_deletion: ok = Metashape.app.getBool(\'Folder \"\' + folder + \'\" will be deleted.\\nAre you sure you want to continue?\') if not ok: return False shutil.rmtree(folder) os.mkdir(folder) return Truedef build_dir_structure(folder, confirm_deletion): if not os.path.exists(folder): os.makedirs(folder) if not clean_dir(folder + \"images/\", confirm_deletion): return False if not clean_dir(folder + \"sparse/\", confirm_deletion): return False if not clean_dir(folder + \"masks/\", confirm_deletion): return False os.makedirs(folder + \"sparse/0/\") return Truedef get_chunk_dirs(folder, params): doc = Metashape.app.document chunk_name_stats = {} chunk_names = {} initial_chunk_selected = doc.chunk.selected doc.chunk.selected = True for chunk in doc.chunks: if not params.all_chunks and not chunk.selected: continue label = chunk.label i = chunk_name_stats[label] = chunk_name_stats.get(label, 0) while True: name = folder + label + (\"\" if i == 0 else \"_\" + str(i)) + \"/\" i += 1 if name not in chunk_names.values(): chunk_names[chunk.key] = name chunk_name_stats[label] = i break doc.chunk.selected = initial_chunk_selected if not params.all_frames and len(chunk_names) == 1: return {chunk_key:folder for chunk_key in chunk_names} existed = [name for name in chunk_names.values() if os.path.exists(name)] if len(existed) > 0: ok = Metashape.app.getBool(\'These folders will be deleted:\\n\"\' + \'\"\\n\"\'.join(existed) + \'\"\\nAre you sure you want to continue?\') if not ok: return {} for name in existed: shutil.rmtree(name) return chunk_namesdef compute_undistorted_calib(sensor, zero_cxy): border = 0 # in pixels, can be increased if black margins are on the undistorted images if sensor.type != Metashape.Sensor.Type.Frame: return Metashape.Calibration() calib_initial = sensor.calibration w = calib_initial.width h = calib_initial.height calib = Metashape.Calibration() calib.f = calib_initial.f calib.width = w calib.height = h left = -float(\"inf\") right = float(\"inf\") top = -float(\"inf\") bottom = float(\"inf\") for i in range(h): pt = calib.project(calib_initial.unproject(Metashape.Vector([0.5, i + 0.5]))) left = max(left, pt.x) pt = calib.project(calib_initial.unproject(Metashape.Vector([w - 0.5, i + 0.5]))) right = min(right, pt.x) for i in range(w): pt = calib.project(calib_initial.unproject(Metashape.Vector([i + 0.5, 0.5]))) top = max(top, pt.y) pt = calib.project(calib_initial.unproject(Metashape.Vector([i + 0.5, h - 0.5]))) bottom = min(bottom, pt.y) left = math.ceil(left) + border right = math.floor(right) - border top = math.ceil(top) + border bottom = math.floor(bottom) - border if zero_cxy: new_w = min(2 * right - w, w - 2 * left) new_h = min(2 * bottom - h, h - 2 * top) new_w -= (new_w + w) % 2 new_h -= (new_h + h) % 2 left = (w - new_w) // 2 right = (w + new_w) // 2 top = (h - new_h) // 2 bottom = (h + new_h) // 2 calib.width = max(0, right - left) calib.height = max(0, bottom - top) calib.cx = -0.5 * (right + left - w) calib.cy = -0.5 * (top + bottom - h) return calibdef check_undistorted_calib(sensor, calib): border = 0 # in pixels, can be increased if black margins are on the undistorted images calib_initial = sensor.calibration w = calib.width h = calib.height left = float(\"inf\") right = -float(\"inf\") top = float(\"inf\") bottom = -float(\"inf\") for i in range(h): pt = calib_initial.project(calib.unproject(Metashape.Vector([0.5, i + 0.5]))) left = min(left, pt.x) pt = calib_initial.project(calib.unproject(Metashape.Vector([w - 0.5, i + 0.5]))) right = max(right, pt.x) for i in range(w): pt = calib_initial.project(calib.unproject(Metashape.Vector([i + 0.5, 0.5]))) top = min(top, pt.y) pt = calib_initial.project(calib.unproject(Metashape.Vector([i + 0.5, h - 0.5]))) bottom = max(bottom, pt.y) print(left, right, top, bottom) if (left < 0.5 or calib_initial.width - 0.5 < right or top < 0.5 or calib_initial.height - 0.5 < bottom): print(\"!!! Wrong undistorted calib\") else: print(\"Ok:\")def get_coord_transform(frame, use_localframe): if not use_localframe: return frame.transform.matrix if not frame.region: print(\"Null region, using world crs instead of local\") return frame.transform.matrix fr_to_gc = frame.transform.matrix gc_to_loc = frame.crs.localframe(fr_to_gc.mulp(frame.region.center)) fr_to_loc = gc_to_loc * fr_to_gc return (Metashape.Matrix.Translation(-fr_to_loc.mulp(frame.region.center)) * fr_to_loc)def compute_undistorted_calibs(frame, zero_cxy): print(\"Calibrations:\") calibs = {} # { sensor_key: ( sensor, undistorted calibration ) } for sensor in frame.sensors: calib = compute_undistorted_calib(sensor, zero_cxy) if (calib.width == 0 or calib.height == 0): continue calibs[sensor.key] = (sensor, calib) print(sensor.key, calib.f, calib.width, calib.height, calib.cx, calib.cy) #check_undistorted_calib(sensor, calib) return calibsdef get_calibs(camera, calibs): s_key = camera.sensor.key if s_key not in calibs: cause = \"unsupported\" if camera.sensor.type != Metashape.Sensor.Type.Frame else \"cropped\" print(\"Camera \" + camera.label + \" (key = \" + str(camera.key) + \") has \" + cause + \" sensor (key = \" + str(s_key) + \")\") return (None, None) return (calibs[s_key][0].calibration, calibs[s_key][1])def get_filtered_track_structure(frame, folder, calibs): tie_points = frame.tie_points cnt_cropped = 0 tracks = {} # { track_id: [ point indices, good projections, bad projections ] }; projection = ( camera_key, projection_idx ) images = {} # { camera_key: [ camera, good projections, bad projections ] }; projection = ( undistored pt in pixels, size, track_id ) for cam in frame.cameras: if cam.transform is None or cam.sensor is None or not cam.enabled: continue (calib0, calib1) = get_calibs(cam, calibs) if calib0 is None: continue camera_entry = [cam, [], []] projections = tie_points.projections[cam] for (i, proj) in enumerate(projections): track_id = proj.track_id if track_id not in tracks: tracks[track_id] = [[], [], []] pt = calib1.project(calib0.unproject(proj.coord)) good = (0 <= pt.x and pt.x < calib1.width and 0 <= pt.y and pt.y < calib1.height) place = (1 if good else 2) if not good: cnt_cropped += 1 pos = len(camera_entry[place]) camera_entry[place].append((pt, proj.size, track_id)) tracks[track_id][place].append((cam.key, pos)) images[cam.key] = camera_entry for (i, pt) in enumerate(tie_points.points): track_id = pt.track_id if track_id not in tracks: tracks[track_id] = [[], [], []] tracks[track_id][0].append(i) print(\"Found\", cnt_cropped, \"cropped projections\") return (tracks, images)def save_undistorted_images(params, frame, folder, calibs, mask=None): img_folder = folder + \"images/\" new_folder = folder + \"masks/\" T = Metashape.Matrix.Diag([1, 1, 1, 1]) cnt = 0 for i,cam in enumerate(frame.cameras): if cam.transform is None or cam.sensor is None or not cam.enabled: continue if cam.sensor.key not in calibs: continue (calib0, calib1) = get_calibs(cam, calibs) if calib0 is None: continue img = cam.image().warp(calib0, T, calib1, T) if mask is not None: img_mask = mask[i].image().warp(calib0, T, calib1, T) name = get_camera_name(cam) ext = os.path.splitext(name)[1] basename = os.path.splitext(name)[0] if ext.lower() in [\".jpg\", \".jpeg\",\"png\"]: c = Metashape.ImageCompression() c.jpeg_quality = params.image_quality img.save(img_folder + name, c) else: print(\"name\",name) print(img_folder,\"img_folder\") img.save(img_folder + name+\".jpg\") if mask is not None: img_mask.save(new_folder + basename + \".png\") cnt += 1 print(\"Undistorted\", cnt, \"cameras\") def save_cameras(params, folder, calibs): use_pinhole_model = params.use_pinhole_model with open(folder + \"sparse/0/cameras.bin\", \"wb\") as fout: fout.write(u64(len(calibs))) for (s_key, (sensor, calib)) in calibs.items(): fout.write(u32(s_key)) fout.write(u32(1 if use_pinhole_model else 0)) fout.write(u64(calib.width)) fout.write(u64(calib.height)) fout.write(d64(calib.f)) if use_pinhole_model: fout.write(d64(calib.f)) fout.write(d64(calib.cx + calib.width * 0.5)) fout.write(d64(calib.cy + calib.height * 0.5)) print(\"Saved\", len(calibs), \"calibrations\")# { camera_key: [ camera, good projections, bad projections ] }; projection = ( undistored pt in pixels, size, track_id )def save_images(params, frame, folder, calibs, tracks, images): only_good = params.only_good T_shift = get_coord_transform(frame, params.use_localframe) with open(folder + \"sparse/0/images.bin\", \"wb\") as fout: # 先写入图像总数 fout.write(u64(len(images))) # 按顺序重新分配图像ID（从0开始），与images.txt保持一致 for new_image_id, (cam_key, [camera, good_prjs, bad_prjs]) in enumerate(images.items()): transform = T_shift * camera.transform R = transform.rotation().inv() T = -1 * (R * transform.translation()) Q = matrix_to_quat(R) # 写入图像ID（新分配的连续ID） fout.write(u64(new_image_id)) # 写入四元数和位移 fout.write(d64(Q.w)) fout.write(d64(Q.x)) fout.write(d64(Q.y)) fout.write(d64(Q.z)) fout.write(d64(T.x)) fout.write(d64(T.y)) fout.write(d64(T.z)) # 写入相机ID fout.write(u32(camera.sensor.key)) # 写入带后缀的文件名（与images.txt保持一致） if camera.photo and os.path.exists(camera.photo.path): image_filename = os.path.basename(camera.photo.path) else: image_filename = camera.label + \".jpg\" fout.write(bstr(image_filename)) # 处理投影点 prjs = (good_prjs if only_good else good_prjs + bad_prjs) fout.write(u64(len(prjs))) for (pt, size, track_id) in prjs: # 与images.txt保持一致：有效轨迹ID不变，无效轨迹ID设为-1 track_id = track_id if len(tracks[track_id][0]) == 1 else -1 fout.write(d64(pt.x)) fout.write(d64(pt.y)) fout.write(u64(track_id)) print(\"Saved\", len(images), \"cameras to images.bin\")# { track_id: [ point indices, good projections, bad projections ] }; projection = ( camera_key, projection_idx )def save_points(params, frame, folder, calibs, tracks, images): only_good = params.only_good T = get_coord_transform(frame, params.use_localframe) num_pts = len(list(filter(lambda x: len(x[0]) == 1, tracks.values()))) with open(folder + \"sparse/0/points3D.bin\", \"wb\") as fout: fout.write(u64(num_pts)) for (track_id, [points, good_prjs, bad_prjs]) in tracks.items(): if (len(points) != 1): continue point = frame.tie_points.points[points[0]] pt = T * point.coord track = frame.tie_points.tracks[track_id] fout.write(u64(track_id)) fout.write(d64(pt.x)) fout.write(d64(pt.y)) fout.write(d64(pt.z)) fout.write(u8(track.color[0])) fout.write(u8(track.color[1])) fout.write(u8(track.color[2])) fout.write(d64(0)) num = (len(good_prjs) if only_good else len(good_prjs) + len(bad_prjs)) fout.write(u64(num)) for (camera_key, proj_idx) in good_prjs: fout.write(u32(camera_key)) fout.write(u32(proj_idx)) if not only_good: for (camera_key, proj_idx) in good_prjs: fout.write(u32(camera_key)) fout.write(u32(proj_idx + len(images[camera_key][1]))) print(\"Saved\", num_pts, \"points from\", len(tracks), \"tracks\")def save_cameras_txt(params, folder, calibs): \"\"\"导出cameras.txt文件\"\"\" use_pinhole_model = params.use_pinhole_model cameras_txt_path = folder + \"sparse/0/cameras.txt\" with open(cameras_txt_path, \"w\") as fout: # 写入头部注释 fout.write(\"# Camera list with one line of data per camera:\\n\") fout.write(\"# CAMERA_ID, MODEL, WIDTH, HEIGHT, PARAMS[]\\n\") fout.write(f\"# Number of cameras: {len(calibs)}\\n\") for (s_key, (sensor, calib)) in calibs.items(): model_name = \"PINHOLE\" if use_pinhole_model else \"SIMPLE_PINHOLE\" if use_pinhole_model: # PINHOLE: fx, fy, cx, cy params_list = [calib.f, calib.f, calib.cx + calib.width * 0.5, calib.cy + calib.height * 0.5] else: # SIMPLE_PINHOLE: f, cx, cy params_list = [calib.f, calib.cx + calib.width * 0.5, calib.cy + calib.height * 0.5] line_data = [s_key, model_name, calib.width, calib.height] + params_list line = \" \".join([str(elem) for elem in line_data]) fout.write(line + \"\\n\") print(f\"Saved {len(calibs)} cameras to cameras.txt\") def save_images_txt(params, frame, folder, calibs, tracks, images): \"\"\"导出images.txt文件，确保图像文件名包含后缀\"\"\" only_good = params.only_good T_shift = get_coord_transform(frame, params.use_localframe) images_txt_path = folder + \"sparse/0/images.txt\" # 计算平均观测数（仅作统计用） total_observations = sum(len(good_prjs) + (0 if only_good else len(bad_prjs)) for [_, good_prjs, bad_prjs] in images.values()) mean_observations = total_observations / len(images) if len(images) > 0 else 0 with open(images_txt_path, \"w\") as fout: # 写入头部注释 fout.write(\"# Image list with two lines of data per image:\\n\") fout.write(\"# IMAGE_ID, QW, QX, QY, QZ, TX, TY, TZ, CAMERA_ID, NAME\\n\") fout.write(\"# POINTS2D[] as (X, Y, POINT3D_ID)\\n\") fout.write(f\"# Number of images: {len(images)}, mean observations per image: {mean_observations}\\n\") # 按顺序重新分配图像ID（从0开始） for new_image_id, (cam_key, [camera, good_prjs, bad_prjs]) in enumerate(images.items()): transform = T_shift * camera.transform R = transform.rotation().inv() T = -1 * (R * transform.translation()) Q = matrix_to_quat(R) # 直接从相机的照片路径获取带后缀的文件名 if camera.photo and os.path.exists(camera.photo.path): image_filename = os.path.basename(camera.photo.path) # 获取完整文件名（含后缀） else: # 回退方案：使用标签+默认后缀 image_filename = camera.label + \".jpg\" print(f\"警告: 相机 {camera.label} 的照片路径不存在，使用默认文件名: {image_filename}\") # 第一行：图像信息（带正确后缀的文件名） image_header = [ new_image_id, # 重新排序的图像ID Q.w, Q.x, Q.y, Q.z, T.x, T.y, T.z, camera.sensor.key, image_filename # 带后缀的文件名 ] first_line = \" \".join(map(str, image_header)) fout.write(first_line + \"\\n\") # 第二行：保留空行（不写入2D点数据） fout.write(\"\\n\") print(f\"Saved {len(images)} images to images.txt\") def save_points_txt(params, frame, folder, calibs, tracks, images): \"\"\"导出points3D.txt文件\"\"\" only_good = params.only_good T = get_coord_transform(frame, params.use_localframe) points_txt_path = folder + \"sparse/0/points3D.txt\" # 过滤有效的3D点 valid_tracks = {track_id: data for track_id, data in tracks.items() if len(data[0]) == 1} # 计算平均轨迹长度 if len(valid_tracks) > 0: mean_track_length = sum(len(good_prjs) + (0 if only_good else len(bad_prjs)) for [_, good_prjs, bad_prjs] in valid_tracks.values()) / len(valid_tracks) else: mean_track_length = 0 with open(points_txt_path, \"w\") as fout: # 写入头部注释 fout.write(\"# 3D point list with one line of data per point:\\n\") fout.write(\"# POINT3D_ID, X, Y, Z, R, G, B, ERROR, TRACK[] as (IMAGE_ID, POINT2D_IDX)\\n\") fout.write(f\"# Number of points: {len(valid_tracks)}, mean track length: {mean_track_length}\\n\") for (track_id, [points, good_prjs, bad_prjs]) in valid_tracks.items(): point = frame.tie_points.points[points[0]] pt = T * point.coord track = frame.tie_points.tracks[track_id] # 点的基本信息 point_header = [track_id, pt.x, pt.y, pt.z, track.color[0], track.color[1], track.color[2], 0.0] fout.write(\" \".join(map(str, point_header)) + \" \") # 轨迹信息 track_strings = [] for (camera_key, proj_idx) in good_prjs: track_strings.append(\" \".join(map(str, [camera_key, proj_idx]))) if not only_good: for (camera_key, proj_idx) in bad_prjs:track_strings.append(\" \".join(map(str, [camera_key, proj_idx + len(images[camera_key][1])]))) fout.write(\" \".join(track_strings) + \"\\n\") print(f\"Saved {len(valid_tracks)} points to points3D.txt\")def save_ply_pointcloud(params, frame, folder, calibs, tracks): \"\"\"保存PLY格式的点云文件\"\"\" T = get_coord_transform(frame, params.use_localframe) ply_path = folder + \"sparse/0/points3D.ply\" # 收集有效的3D点 valid_points = [] valid_colors = [] for (track_id, [points, good_prjs, bad_prjs]) in tracks.items(): if len(points) != 1: continue point = frame.tie_points.points[points[0]] track = frame.tie_points.tracks[track_id] # 应用坐标变换 pt = T * point.coord valid_points.append([pt.x, pt.y, pt.z]) valid_colors.append([track.color[0], track.color[1], track.color[2]]) if len(valid_points) == 0: print(\"No valid points to save\") return # 创建PLY文件 save_ply_file(ply_path, valid_points, valid_colors) print(f\"Saved {len(valid_points)} points to {ply_path}\")def save_ply_file(path, xyz, rgb): \"\"\"保存PLY文件的底层函数\"\"\" # 创建法向量（设为零向量） normals = [[0.0, 0.0, 0.0] for _ in range(len(xyz))] # 写入PLY文件 with open(path, \'w\') as f: # PLY文件头 f.write(\"ply\\n\") f.write(\"format ascii 1.0\\n\") f.write(f\"element vertex {len(xyz)}\\n\") f.write(\"property float x\\n\") f.write(\"property float y\\n\") f.write(\"property float z\\n\") f.write(\"property float nx\\n\") f.write(\"property float ny\\n\") f.write(\"property float nz\\n\") f.write(\"property uchar red\\n\") f.write(\"property uchar green\\n\") f.write(\"property uchar blue\\n\") f.write(\"end_header\\n\") # 写入点数据 for i in range(len(xyz)): x, y, z = xyz[i] nx, ny, nz = normals[i] r, g, b = rgb[i] f.write(f\"{x} {y} {z} {nx} {ny} {nz} {r} {g} {b}\\n\")class ExportSceneParams(): def __init__(self): # default values for parameters self.all_chunks = True self.all_frames = True self.zero_cxy = True self.use_localframe = True self.image_quality = 100 self.export_images = True self.confirm_deletion = True self.use_pinhole_model = True self.only_good = True def log(self): print(\"All chunks:\", self.all_chunks) print(\"All frames:\", self.all_frames) print(\"Zero cx and cy:\", self.zero_cxy) print(\"Use local coordinate frame:\", self.use_localframe) print(\"Image quality:\", self.image_quality) print(\"Export images:\", self.export_images) print(\"Confirm deletion:\", self.confirm_deletion) print(\"Using pinhole model instead of simple_pinhole:\", self.use_pinhole_model) print(\"Using only uncropped projections:\", self.only_good)def export_for_gaussian_splatting(params = ExportSceneParams(), progress = QtWidgets.QProgressBar()): log_result = lambda x: print(\"\", x, \"-----------------------------------\", sep=\"\\n\") progress.setMinimum(0) progress.setMaximum(1000) set_progress = lambda x: progress.setValue(int(x * 1000)) params.log() folder = Metashape.app.getExistingDirectory(\"Output folder\") if len(folder) == 0: log_result(\"No chosen folder\") return folder = folder + \"/\" print(folder) chunk_dirs = get_chunk_dirs(folder, params) if len(chunk_dirs) == 0: log_result(\"Aborted\") return chunk_num = len(chunk_dirs) for chunk_id, (chunk_key, chunk_folder) in enumerate(chunk_dirs.items()): chunk = [ck for ck in Metashape.app.document.chunks if ck.key == chunk_key] if (len(chunk) != 1): print(\"Chunk not found, key =\", chunk_key) continue chunk = chunk[0] frame_num = len(chunk.frames) if params.all_frames else 1 prog_step = 1 / chunk_num set_progress(prog_step * chunk_id) set_progress_frame = lambda n: set_progress(prog_step * (chunk_id + n / frame_num)) frame_cnt = 0#print(chunk) if chunk.masks: masks_frames = chunk.masks.values() else: masks_frames = None for frame_id, frame in enumerate(chunk.frames): print(frame_id) if not frame.tie_points: continue if not params.all_frames and not (frame == chunk.frame): continue set_progress_frame(frame_cnt) frame_cnt += 1 folder = chunk_folder + (\"\" if frame_num == 1 else \"frame_\" + str(frame_id).zfill(6) + \"/\") print(\"\\n\" + folder) if not build_dir_structure(folder, params.confirm_deletion): log_result(\"Aborted\") return calibs = compute_undistorted_calibs(frame, params.zero_cxy) (tracks, images) = get_filtered_track_structure(frame, folder, calibs) if params.export_images: # print(masks_frames) # print(frame) # print(frame_id) save_undistorted_images(params, frame, folder, calibs, masks_frames) save_cameras(params, folder, calibs) save_images(params, frame, folder, calibs, tracks, images) save_points(params, frame, folder, calibs, tracks, images) # 添加TXT格式导出 save_cameras_txt(params, folder, calibs) save_images_txt(params, frame, folder, calibs, tracks, images) save_points_txt(params, frame, folder, calibs, tracks, images) # 添加PLY点云保存 save_ply_pointcloud(params, frame, folder, calibs, tracks) set_progress(1) log_result(\"Done\")class CollapsibleGroupBox(QtWidgets.QGroupBox): def __init__(self, parent = None): QtWidgets.QGroupBox.__init__(self, parent) self.toggled.connect(self.onCheckedChanged) self.maxHeight = self.maximumHeight() def onCheckedChanged(self, is_on): if not is_on: self.oldSize = self.size() for child in self.children(): if isinstance(child, QtWidgets.QWidget): child.setVisible(is_on) if is_on: self.setMaximumHeight(self.maxHeight) self.resize(self.oldSize) else: self.maxHeight = self.maximumHeight() self.setMaximumHeight(QtGui.QFontMetrics(self.font()).height() + 4)class ExportSceneGUI(QtWidgets.QDialog): def run_export(self): for button in self.buttons: button.setEnabled(False) params = ExportSceneParams() params.all_chunks = self.radioBtn_allC.isChecked() params.all_frames = self.radioBtn_allF.isChecked() params.zero_cxy = self.zcxyBox.isChecked() params.use_localframe = self.locFrameBox.isChecked() params.image_quality = self.imgQualSpBox.value() params.export_images = self.expImagesBox.isChecked() try: export_for_gaussian_splatting(params, self.pBar) finally: self.done(0) def __init__(self, parent): QtWidgets.QDialog.__init__(self, parent) self.setWindowTitle(\"Export scene in Colmap format:\") defaults = ExportSceneParams() self.btnQuit = QtWidgets.QPushButton(\"Quit\") self.btnQuit.setFixedSize(100,25) self.btnP1 = QtWidgets.QPushButton(\"Export\") self.btnP1.setFixedSize(100,25) self.pBar = QtWidgets.QProgressBar() self.pBar.setTextVisible(False) self.pBar.setFixedSize(100, 25) self.chnkTxt = QtWidgets.QLabel() self.chnkTxt.setText(\"Chunks:\") self.chnkTxt.setFixedSize(100, 25) self.frmsTxt = QtWidgets.QLabel() self.frmsTxt.setText(\"Frames:\") self.frmsTxt.setFixedSize(100, 25) self.chunk_group = QtWidgets.QButtonGroup() self.radioBtn_allC = QtWidgets.QRadioButton(\"all chunks\") self.radioBtn_selC = QtWidgets.QRadioButton(\"selected\") self.chunk_group.addButton(self.radioBtn_selC) self.chunk_group.addButton(self.radioBtn_allC) self.radioBtn_allC.setChecked(defaults.all_chunks) self.radioBtn_selC.setChecked(not defaults.all_chunks) self.frames_group = QtWidgets.QButtonGroup() self.radioBtn_allF = QtWidgets.QRadioButton(\"all frames\") self.radioBtn_selF = QtWidgets.QRadioButton(\"active\") self.frames_group.addButton(self.radioBtn_selF) self.frames_group.addButton(self.radioBtn_allF) self.radioBtn_allF.setChecked(defaults.all_frames) self.radioBtn_selF.setChecked(not defaults.all_frames) self.zcxyTxt = QtWidgets.QLabel() self.zcxyTxt.setText(\"Enforce zero cx, cy\") self.zcxyTxt.setFixedSize(100, 25) self.zcxyBox = QtWidgets.QCheckBox() self.zcxyBox.setChecked(defaults.zero_cxy) self.locFrameTxt = QtWidgets.QLabel() self.locFrameTxt.setText(\"Use localframe\") self.locFrameTxt.setFixedSize(100, 25) self.locFrameBox = QtWidgets.QCheckBox() self.locFrameBox.setChecked(defaults.use_localframe) self.imgQualTxt = QtWidgets.QLabel() self.imgQualTxt.setText(\"Image quality\") self.imgQualTxt.setFixedSize(100, 25) self.imgQualSpBox = QtWidgets.QSpinBox() self.imgQualSpBox.setMinimum(0) self.imgQualSpBox.setMaximum(100) self.imgQualSpBox.setValue(defaults.image_quality) self.expImagesTxt = QtWidgets.QLabel() self.expImagesTxt.setText(\"Export images\") self.expImagesTxt.setFixedSize(100, 25) self.expImagesBox = QtWidgets.QCheckBox() self.expImagesBox.setChecked(defaults.export_images) zcxyToolTip = \'Output camera calibrations will have zero cx and cy\\nShould be checked until Gaussian Splatting software considers this parameters\\nMay result in information loss during export (large cropping)\\nTo mitigate that effect, do step 1.1.0. and check \"Adaptive camera model fitting\" at 1.2. of the script description\' self.zcxyTxt.setToolTip(zcxyToolTip) self.zcxyBox.setToolTip(zcxyToolTip) locFrameToolTip = \"Shifts coordinates origin to the center of the bounding box\\nUses localframe rotation at this point\\nThis is useful to fix large coordinates\" self.locFrameTxt.setToolTip(locFrameToolTip) self.locFrameBox.setToolTip(locFrameToolTip) imgQualToolTip = \"Quality of the output undistorted images (jpeg only)\\nMin = 0, Max = 100\" self.imgQualTxt.setToolTip(imgQualToolTip) self.imgQualSpBox.setToolTip(imgQualToolTip) expImagesToolTip = \"You can disable export of the undistorted images\" self.expImagesTxt.setToolTip(expImagesToolTip) self.expImagesBox.setToolTip(expImagesToolTip) general_layout = QtWidgets.QGridLayout() general_layout.setSpacing(9) general_layout.addWidget(self.chnkTxt, 1, 0) general_layout.addWidget(self.radioBtn_allC, 1, 1) general_layout.addWidget(self.radioBtn_selC, 1, 2) general_layout.addWidget(self.frmsTxt, 2, 0) general_layout.addWidget(self.radioBtn_allF, 2, 1) general_layout.addWidget(self.radioBtn_selF, 2, 2) general_layout.addWidget(self.zcxyTxt, 3, 0) general_layout.addWidget(self.zcxyBox, 3, 1) general_layout.addWidget(self.locFrameTxt, 4, 0) general_layout.addWidget(self.locFrameBox, 4, 1) general_layout.addWidget(self.imgQualTxt, 5, 0) general_layout.addWidget(self.imgQualSpBox, 5, 1, 1, 2) advanced_layout = QtWidgets.QGridLayout() advanced_layout.setSpacing(9) advanced_layout.addWidget(self.expImagesTxt, 0, 0) advanced_layout.addWidget(self.expImagesBox, 0, 1) self.gbGeneral = QtWidgets.QGroupBox() self.gbGeneral.setLayout(general_layout) self.gbGeneral.setTitle(\"General\") self.gbAdvanced = CollapsibleGroupBox() self.gbAdvanced.setLayout(advanced_layout) self.gbAdvanced.setTitle(\"Advanced\") self.gbAdvanced.setCheckable(True) self.gbAdvanced.setChecked(False) self.gbAdvanced.toggled.connect(lambda: QtCore.QTimer.singleShot(20, lambda: self.adjustSize())) layout = QtWidgets.QGridLayout() layout.addWidget(self.gbGeneral, 0, 0, 1, 3) layout.addWidget(self.gbAdvanced, 1, 0, 1, 3) layout.addItem(QtWidgets.QSpacerItem(1, 1, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.MinimumExpanding)) layout.addWidget(self.pBar, 3, 0) layout.addWidget(self.btnP1, 3, 1) layout.addWidget(self.btnQuit, 3, 2) self.setLayout(layout) self.buttons = [self.btnP1, self.btnQuit, self.radioBtn_allC, self.radioBtn_selC, self.radioBtn_allF, self.radioBtn_selF, self.zcxyBox, self.locFrameBox, self.imgQualSpBox, self.expImagesBox] proc = lambda : self.run_export() QtCore.QObject.connect(self.btnP1, QtCore.SIGNAL(\"clicked()\"), proc) QtCore.QObject.connect(self.btnQuit, QtCore.SIGNAL(\"clicked()\"), self, QtCore.SLOT(\"reject()\")) self.exec()def export_for_gaussian_splatting_gui(): global app app = QtWidgets.QApplication.instance() parent = app.activeWindow() dlg = ExportSceneGUI(parent)label = \"Scripts/Export Colmap project (oc)\"Metashape.app.addMenuItem(label, export_for_gaussian_splatting_gui)print(\"To execute this script press {}\".format(label))
