easyidp.pix4d.read_campos_geo#
- easyidp.pix4d.read_campos_geo(campos_path)#
Read
*_calibrated_images_position.txt
foreasyidp.reconstruct.Photo.position
(geo_location)- パラメータ:
campos_path (str) -- file path
- 戻り値:
campos_dict = { "Image1.JPG": np.array([x, y ,z]), "Image2.JPG": ... ... }
- 戻り値の型:
dict
メモ
this file contains the geo position of each camera, and looks like:
DJI_0954.JPG,368030.548722,3955824.412658,127.857028 DJI_0955.JPG,368031.004387,3955824.824967,127.381322 DJI_0956.JPG,368033.252520,3955826.479610,127.080709 DJI_0957.JPG,368032.022104,3955826.060493,126.715974 DJI_0958.JPG,368031.901165,3955826.109158,126.666393 DJI_0959.JPG,368030.686490,3955830.981070,127.327741
サンプル
Data prepare
>>> import numpy as np >>> np.set_printoptions(suppress=True) >>> import easyidp as idp >>> test_data = idp.data.TestData() >>> param_folder = str(test_data.pix4d.maize_folder / "1_initial" / "params") >>> param = idp.pix4d.parse_p4d_param_folder(param_folder)
Then use this function:
>>> idp.pix4d.read_campos_geo(param['campos']) { 'DJI_0954.JPG': array([ 368030.548722, 3955824.412658, 127.857028]), 'DJI_0955.JPG': array([ 368031.004387, 3955824.824967, 127.381322]), ... }