clean codes and change variable names

README.md

@@ -122,9 +122,9 @@ Please find argument details from run scripts.
 * `number_video_per_set_of_frame`: Number of videos to generate per set of frames.
 * `increase_rate`: Rate at which the number of frames increases.
 * `ltl_logic`: Temporal logic to apply. Options include various logical expressions like "F prop1", "G prop1", etc.
-* `save_frames`: Boolean to decide whether to save individual frames (True or False).
-In each run script, make sure 
+* `save_images`: Boolean to decide whether to save individual frame images (True or False).
 
+In each run script, make sure 
 1. **coco synthetic data generator** <br>
 COCO synthetic data generator can generate & compositions since it has multiple labels.
 ```

run_scripts/run_synthetic_tlv_coco.py

@@ -65,7 +65,7 @@
         ],
     )
     parser.add_argument(
-        "--save_frames",
+        "--save_images",
         type=bool,
         default=False,
     )
@@ -97,5 +97,5 @@
             number_video_per_set_of_frame=args.number_video_per_set_of_frame,
             increase_rate=args.increase_rate,
             ltl_logic=tl,
-            save_frames=args.save_frames,
+            save_images=args.save_frames,
         )

run_scripts/run_synthetic_tlv_coco_until_long_horizon.py

@@ -60,7 +60,7 @@
         ],
     )
     parser.add_argument(
-        "--save_frames",
+        "--save_images",
         type=bool,
         default=False,
     )
@@ -81,5 +81,5 @@
         number_video_per_set_of_frame=args.number_video_per_set_of_frame,
         increase_rate=args.increase_rate,
         present_prop1_till_prop2=args.present_prop1_till_prop2,
-        save_frames=args.save_frames,
+        save_images=args.save_frames,
     )

run_scripts/run_synthetic_tlv_imagenet.py

@@ -63,7 +63,7 @@
         ],
     )
     parser.add_argument(
-        "--save_frames",
+        "--save_images",
         type=bool,
         default=False,
     )
@@ -94,5 +94,5 @@
             number_video_per_set_of_frame=args.number_video_per_set_of_frame,
             increase_rate=args.increase_rate,
             ltl_logic=tl,
-            save_frames=args.save_frames,
+            save_images=args.save_frames,
         )

run_scripts/run_synthetic_tlv_imagenet_until_long_horizon.py

@@ -60,7 +60,7 @@
         ],
     )
     parser.add_argument(
-        "--save_frames",
+        "--save_images",
         type=bool,
         default=False,
     )
@@ -82,5 +82,5 @@
         number_video_per_set_of_frame=args.number_video_per_set_of_frame,
         increase_rate=args.increase_rate,
         present_prop1_till_prop2=args.present_prop1_till_prop2,
-        save_frames=args.save_frames,
+        save_images=args.save_frames,
     )

tlv_dataset/data/tlv_dataset.py

@@ -1,15 +1,10 @@
 import dataclasses  # noqa: D100
-import random
-from pathlib import Path
-from typing import Dict, List, Optional
+from typing import List, Optional
 
-import cv2
 import numpy as np
-import torch
 from PIL import Image
 
 from tlv_dataset.common.frame_grouping import combine_consecutive_lists
-from tlv_dataset.common.utility import get_file_or_dir_with_datetime
 
 
 @dataclasses.dataclass
@@ -48,12 +43,11 @@ def save_frames(
         Args:
         path (str, optional): Path to save image.
         """
-        from PIL import Image
 
         for idx, img in enumerate(self.images_of_frames):
             Image.fromarray(img).save(f"{path}/{idx}.png")
 
-    def save(
+    def save_as_class(
         self,
         save_path: str = "/opt/Neuro-Symbolic-Video-Frame-Search/artifacts",
     ) -> None:
@@ -63,3 +57,24 @@ def save(
         """Save the current instance to a pickle file."""
         with open(save_path, "wb") as f:
             pickle.dump(self, f)
+
+    def save_as_dict(
+        self,
+        save_path: str = "/opt/Neuro-Symbolic-Video-Frame-Search/artifacts",
+    ) -> None:
+        """Save the current instance to a pickle file."""
+        import pickle
+
+        dict_format = dict(
+            ground_truth=self.ground_truth,
+            ltl_formula=self.ltl_formula,
+            proposition=self.proposition,
+            number_of_frame=self.number_of_frame,
+            frames_of_interest=self.frames_of_interest,
+            labels_of_frames=self.labels_of_frames,
+            images_of_frames=self.images_of_frames,
+        )
+
+        """Save the current instance to a pickle file."""
+        with open(save_path, "wb") as f:
+            pickle.dump(dict_format, f)

tlv_dataset/generator/synthetic_tlv_generator.py

@@ -23,8 +23,8 @@ def __init__(
         Args:
             dataloader (TLVImageLoader): Image data loader.
         """
-        self._data_loader = dataloader
-        self.data = self._data_loader.data
+        self.data_loader = dataloader
+        self.data = self.data_loader.data
         self._save_dir = Path(save_dir)
         self._save_dir.mkdir(parents=True, exist_ok=True)
 
@@ -78,7 +78,8 @@ def generate(
         ltl_logic: str = "F prop1",
         temporal_property: str = "",
         conditional_property: str = "",
-        save_frames: bool = False,
+        save_images: bool = False,
+        save_as: str = "dict",  # class
     ) -> any:
         """Generate data."""
         number_frame = initial_number_of_frame
@@ -122,13 +123,19 @@ def generate(
                     proposition=ltl_frame.proposition,
                 )
                 self.extract_properties(ltl_frame.ltl_formula)
-                ltl_frame.save(
-                    save_path=self._save_dir
-                    / f"benchmark_{self._data_loader.name}_ltl_{ltl_frame.ltl_formula}_{number_frame}_{video_idx}.pkl"
-                )
+                if save_as == "dict":
+                    ltl_frame.save_as_dict(
+                        save_path=self._save_dir
+                        / f"benchmark_{self.data_loader.name}_ltl_{ltl_frame.ltl_formula}_{number_frame}_{video_idx}.pkl"
+                    )
+                else:
+                    ltl_frame.save_as_class(
+                        save_path=self._save_dir
+                        / f"benchmark_{self.data_loader.name}_ltl_{ltl_frame.ltl_formula}_{number_frame}_{video_idx}.pkl"
+                    )
 
             number_frame += increase_rate
-        if save_frames:
+        if save_images:
             ltl_frame.save_frames()
 
     def generate_until_time_delta(
@@ -139,7 +146,8 @@ def generate_until_time_delta(
         increase_rate: int = 1,
         ltl_logic: str = "prop1 U prop2",
         present_prop1_till_prop2: bool = False,
-        save_frames: bool = False,
+        save_images: bool = False,
+        save_as: str = "dict",  # class
     ) -> any:
         """Generate data."""
         number_frame = initial_number_of_frame
@@ -184,13 +192,19 @@ def generate_until_time_delta(
                     proposition=ltl_frame.proposition,
                 )
                 self.extract_properties(ltl_frame.ltl_formula)
-                ltl_frame.save(
-                    save_path=self._save_dir
-                    / f"timedelta_{number_frame - (initial_number_of_frame - 1)}_benchmark_{self._data_loader.name}_ltl_{ltl_frame.ltl_formula}_{number_frame}_{video_idx}.pkl"
-                )
+                if save_as == "dict":
+                    ltl_frame.save_as_dict(
+                        save_path=self._save_dir
+                        / f"benchmark_{self.data_loader.name}_ltl_{ltl_frame.ltl_formula}_{number_frame}_{video_idx}.pkl"
+                    )
+                else:
+                    ltl_frame.save_as_class(
+                        save_path=self._save_dir
+                        / f"benchmark_{self.data_loader.name}_ltl_{ltl_frame.ltl_formula}_{number_frame}_{video_idx}.pkl"
+                    )
 
             number_frame += increase_rate
-        if save_frames:
+        if save_images:
             ltl_frame.save_frames()
 
     def generate_unique_random_indices_within_range(self, start, end):