WIP cleaning

env/environment.yml

+name: "visual-loc"
+channels:
+  - pytorch
+  - conda-forge
+dependencies:
+  - python=3.7
+  - cudatoolkit
+  - matplotlib
+  - numpy
+  - opencv
+  - pillow
+  - pytorch
+  - pytorch-lightning
+  - scipy
+  - torchvision
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move_checkpoints.py

-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-"""
-Created on Thu Mar 25 12:38:33 2021
-
-@author: mzins
-"""
-
-import glob
-import os
-import shutil
-
-
-folder = "/home/mzins/dev/3D-Aware_Ellipses_for_Visual_Localization/checkpoints_log_bn"
-list_folders = glob.glob(os.path.join(folder, "*"))
-os.mkdir(os.path.join(folder, "weights_best"))
-os.mkdir(os.path.join(folder, "weights_last"))
-
-for fold in sorted(list_folders):
-    ckpts = sorted(glob.glob(os.path.join(fold, "*.ckpt")))
-    ckpt_best = ckpts[0]
-    ckpt_last = ckpts[1]
-    name = os.path.basename(fold)
-    
-    name_best = name + "_" + "ckpt_best.pth"
-    name_last = name + "_" + "ckpt_last.pth"
-    shutil.move(ckpt_best, os.path.join(folder, "weights_best", name_best))
-    shutil.move(ckpt_last, os.path.join(folder, "weights_last", name_last))
-    print("moved", name_best, name_last)
-    
-    
-    
-    
-                  
-    
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pose_computation.py

@@ -22,14 +22,7 @@ def compute_pose(detections, scene, K, min_obj_for_P3P=4):
                         "ellipses": [ Ellipse, Ellipse, Ellipse, ...]
                     }, ...
                 ]
-            - scene: scene model:
-                [
-                    {
-                        "object_id": ...,
-                        "category_id": ...,
-                        "ellipsoid": Ellipsoid
-                    }, ...
-                ]
+            - scene: scene loader
             - K: intrinsic matrix of the camera
             - min_obj_for_P3P: minimum number of objects needed to use P3P,
                                otherwise P2E can be used.

run_preprocessing.sh

 
-python preprocess_7-Scenes.py -i $1/seq-01 $1/seq-04 $1/seq-06 -o 7-Scenes_Chess_dataset_train.json
-python preprocess_7-Scenes.py -i $1/seq-02 $1/seq-03 $1/seq-05 -o 7-Scenes_Chess_dataset_test.json
+python prepare_7-Scenes.py -i $1/seq-01 $1/seq-04 $1/seq-06 -o 7-Scenes_Chess_dataset_train.json
+python prepare_7-Scenes.py -i $1/seq-02 $1/seq-03 $1/seq-05 -o 7-Scenes_Chess_dataset_test.json
 
 python annotate_objects.py scene.json 7-Scenes_Chess_dataset_train.json 7-Scenes_Chess_dataset_train_with_obj_annot.json
 python annotate_objects.py scene.json 7-Scenes_Chess_dataset_test.json  7-Scenes_Chess_dataset_test_with_obj_annot.json

train_ellipse_prediction.py

@@ -108,8 +108,7 @@ def run_training(training_dataset_file, validation_dataset_file, obj,
 
 
 
-if __name__ == "__main__":
-
+def main(args):
     parser = argparse.ArgumentParser()
     parser.add_argument("scene", help="<Required> Input Scene file containing the objects (.json)")
     parser.add_argument("training", help="<Required> Input training dataset file (.json)")
@@ -128,7 +127,7 @@ if __name__ == "__main__":
                              "not only weights (default is False).",
                         default=False)
 
-    args = parser.parse_args()
+    args = parser.parse_args(args)
 
 
     scene_file = args.scene
@@ -163,3 +162,10 @@ if __name__ == "__main__":
                      save_weights_only=save_weights_only)
 
 
+if __name__ == '__main__':
+    import sys
+    try:
+        main(sys.argv[1:])
+    except Exception as e:
+        logging.exception(e)
+        sys.exit(1)
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