============ reconstruct ============ .. currentmodule:: easyidp.reconstruct .. caution:: This is the base module for 3D reconstruction project, all the following classes and functions have already been implemented into the submodule :class:`easyidp.Pix4D ` and :class:`easyidp.Metashape `. They are generally sufficient for most application cases, it is not recommended to create the following classes or use the following functions directly unless you really need to. Class ===== A summary of base class in the module ``easyidp.reconstruct``. .. autosummary:: :toctree: autodoc Recons Sensor Photo Calibration ChunkTransform You can definately access these base class directly by: .. code-block:: python >>> import easyidp as idp >>> sensor = idp.reconstruct.Sensor() >>> sensor >>> photo = idp.reconstruct.Photo() >>> photo But it is more often used in the Pix4D or Metashape project in this way: .. tab:: Pix4D Load the example data: .. code-block:: python >>> test_data = idp.data.TestData() And read the demo pix4d project: .. code-block:: python >>> p4d = idp.Pix4D( ... project_path=test_data.pix4d.lotus_folder, ... param_folder=test_data.pix4d.lotus_param ... ) Then access the classes: .. code-block:: python >>> p4d.sensors with 1 items [0] FC550_DJIMFT15mmF1.7ASPH_15.0_4608x3456 >>> p4d.photos[0] .. tab:: Metashape Load the example data: .. code-block:: python >>> test_data = idp.data.TestData() And read the demo metashape project: .. code-block:: python >>> ms = idp.Metashape(test_data.metashape.lotus_psx, chunk_id=0) Then access the classes: .. code-block:: python >>> ms.photos with 151 items [0] DJI_0422 [1] DJI_0423 ... [149] DJI_0571 [150] DJI_0572 Functions ========= .. autosummary:: :toctree: autodoc sort_img_by_distance save_back2raw_json_and_png