Updated code to only search for reference orthomosaics and for functi…

…oning re-georeferencing with coregistration parameters

gref4hsi/scripts/coregistration.py

@@ -436,7 +436,7 @@ def main(config_path, mode):
 
     # Establish reference data
     path_orthomosaic_reference_folder = config['Absolute Paths']['orthomosaic_reference_folder']
-    orthomosaic_reference_fn = os.listdir(path_orthomosaic_reference_folder)[0] # Grab the only file in folder
+    orthomosaic_reference_fn = [f for f in os.listdir(path_orthomosaic_reference_folder) if f.endswith('tif')][0] # Grab the only file in folder that ends with *.tif
     ref_ortho_path = os.path.join(path_orthomosaic_reference_folder, orthomosaic_reference_fn)
 
     dem_path = config['Absolute Paths']['dem_path']
@@ -494,6 +494,8 @@ def main(config_path, mode):
         for file_count, hsi_composite_file in enumerate(hsi_composite_files):
 
             file_base_name = hsi_composite_file.split('.')[0]
+
+
 
             # The match data (hyperspectral)
             hsi_composite_path = os.path.join(path_composites_match, hsi_composite_file)

gref4hsi/scripts/georeference.py

@@ -215,7 +215,7 @@ def main(iniPath, viz = False, use_coreg_param = False):
                                                     dataset_name= h5_folder_position_ecef)
                  try:
                     # Use the coregistred dataset if it exists
-                    pos_ref_ecef = Hyperspectral.get_dataset(h5_filename=h5_filename,
+                    quat_ref_ecef = Hyperspectral.get_dataset(h5_filename=h5_filename,
                                                     dataset_name= h5_folder_quaternion_ecef_coreg)
                  except:
                      # If not use the original
@@ -230,9 +230,9 @@ def main(iniPath, viz = False, use_coreg_param = False):
                 # Extract the ecef orientations for each frame
                 quat_ref_ecef = Hyperspectral.get_dataset(h5_filename=h5_filename,
                                                                 dataset_name=h5_folder_quaternion_ecef)
-                # Extract the timestamps for each frame
-                time_pose = Hyperspectral.get_dataset(h5_filename=h5_filename,
-                                                                dataset_name= h5_folder_time_pose)
+            # Extract the timestamps for each frame
+            time_pose = Hyperspectral.get_dataset(h5_filename=h5_filename,
+                                                            dataset_name= h5_folder_time_pose)
 
 
             # Using the cal file, we can define lever arm, boresight and camera model geometry (in dictionary)

gref4hsi/tests/test_main_specim.py

@@ -22,7 +22,9 @@
     sys.path.append(module_path)
 
 # Local resources
-from gref4hsi.scripts import georeference, orthorectification, coregistration
+from gref4hsi.scripts import georeference
+from gref4hsi.scripts import orthorectification
+from gref4hsi.scripts import coregistration
 from gref4hsi.utils import parsing_utils, specim_parsing_utils
 from gref4hsi.utils import visualize
 from gref4hsi.utils.config_utils import prepend_data_dir_to_relative_paths, customize_config
@@ -38,7 +40,7 @@
 
 
 
-def main(config_yaml, specim_mission_folder, geoid_path, config_template_path, lab_calibration_path):
+def main(config_yaml, specim_mission_folder, geoid_path, config_template_path, lab_calibration_path, fast_mode = False):
     # Read flight-specific yaml file
     with open(config_yaml, 'r') as file:  
         config_data = yaml.safe_load(file)
@@ -67,10 +69,11 @@ def main(config_yaml, specim_mission_folder, geoid_path, config_template_path, l
             DEM_PATH = os.path.join(dem_fold, files[0])
             #print(f"The file '{DEM_PATH}' is used as terrain.")
             TERRAIN_TYPE = "dem_file"
+            print(DEM_PATH)
 
 
     # Do coregistration if there is an orthomosaic to compare under "orthomosaic"
-    do_coreg = False
+    #do_coreg = True
     ortho_ref_fold = os.path.join(specim_mission_folder, "orthomosaic")
 
     if not os.path.exists(ortho_ref_fold):
@@ -82,8 +85,8 @@ def main(config_yaml, specim_mission_folder, geoid_path, config_template_path, l
         else:
             # If there is a folder and it is not empty
             # Find the only file that is there
-            ortho_ref_file = [f for f in os.listdir(ortho_ref_fold) if f not in ('.', '..')][0]
-            do_coreg == True
+            ortho_ref_file = [f for f in os.listdir(ortho_ref_fold) if f.endswith('tif')][0]
+            do_coreg = True
             print(f"The file '{ortho_ref_file}' is used as as reference orthomosaic.")
 
 
@@ -176,6 +179,12 @@ def main(config_yaml, specim_mission_folder, geoid_path, config_template_path, l
     # No need to orthorectify the data cube initially when coregistration with RGB composites is done
     if do_coreg:
         custom_config['Orthorectification']['resample_rgb_only'] = True
+
+    # 
+    if fast_mode:
+        custom_config['Orthorectification']['resample_rgb_only'] = True
+        custom_config['Orthorectification']['resolutionhyperspectralmosaic'] = 1
+
 
     # Customizes the config file according to settings
     customize_config(config_path=config_file_mission, dict_custom=custom_config)
@@ -187,51 +196,58 @@ def main(config_yaml, specim_mission_folder, geoid_path, config_template_path, l
     # This function parses raw specim data including (spectral, radiometric, geometric) calibrations and nav data
     # into an h5 file. The nav data is written to "raw/nav/" subfolders, whereas hyperspectral data and calibration data 
     # written to "processed/hyperspectral/" and "processed/calibration/" subfolders
+    model_path = config['Absolute Paths']['model_path']
+
+    # If this folder exists, there is no need to repeat this step
     """specim_parsing_utils.main(config=config,
-                              config_specim=config_specim_preprocess)"""
+                                  config_specim=config_specim_preprocess)
     
     # Time interpolates and reformats the pose (of the vehicle body) to "processed/nav/" folder.
-    config = parsing_utils.export_pose(config_file_mission)
+    parsing_utils.export_pose(config_file_mission)
     
-    # Formats model to triangular mesh and an earth centered earth fixed / geocentric coordinate system
-    parsing_utils.export_model(config_file_mission)
+    if not os.path.exists(model_path):
+        parsing_utils.export_model(config_file_mission)
 
     # Commenting out the georeference step is fine if it has been done
 
     
     ## Visualize the data 3D photo model from RGB images and the time-resolved positions/orientations
-    """if ENABLE_VISUALIZE:
-        visualize.show_mesh_camera(config, show_mesh = True, show_pose = True, ref_frame='ENU')"""
+    
 
-    # Georeference the line scans of the hyperspectral imager. Utilizes parsed data
+    # Georeference the line scans of the hyperspectral imager.
     georeference.main(config_file_mission)
 
-    orthorectification.main(config_file_mission)
+    orthorectification.main(config_file_mission)"""
     # The coregistration compares to the reference and optimizes geometric parameters which are used to re-georeference.
     if do_coreg:
         # Optional: coregistration
         # Match RGB composite to reference, find features and following data, ground control point (gcp) list, for each feature pair:
         # reference point 3D (from reference), position/orientation of vehicle (using resampled time) and pixel coordinate (using resampled pixel coordinate)
-        coregistration.main(config_file_mission, mode='compare')
+        """coregistration.main(config_file_mission, mode='compare')
 
         # The gcp list allows reprojecting reference points and evaluate the reprojection error,
         # which is used to optimize static geometric parameters (e.g. boresight, camera model...) or dynamic geometric parameters (time-varying nav errors).
         # Settings are currently in coregistration script
-        coregistration.main(config_file_mission, mode='calibrate')
+        coregistration.main(config_file_mission, mode='calibrate')"""
 
         # The final orthorectification can be conducted on the datacube too
-        custom_config['Orthorectification']['resample_rgb_only'] = True
+        custom_config['Orthorectification']['resample_rgb_only'] = False
+
+        # No impact unless you rewrite the config
+        customize_config(config_path=config_file_mission, dict_custom=custom_config)
+
+
 
         # Georeference with coregistred parameters
         georeference.main(config_file_mission, use_coreg_param=True)
-
+
+        # And orthorectify
         orthorectification.main(config_file_mission)
 
 
-
 if __name__ == "__main__":
     # Select a recording folder on drive
-    specim_mission_folder = os.path.join(base_fp, r"Specim/Missions/2022-08-31-Remoy/remoy_202208310800_ntnu_hyperspectral_74m")
+    specim_mission_folder = os.path.join(base_fp, r"Specim/Missions/2022-08-31-Remoy/remoy_202208311040_ntnu_hyperspectral_74m")
 
     # Globally accessible files:
     geoid_path = os.path.join(home, "VsCodeProjects/gref4hsi/data/world/geoids/egm08_25.gtx")