change i to index in var name and renaming the preprocess_signs function

signwriting_transcription/pose_to_signwriting/bin.py

@@ -53,7 +53,7 @@ def download_model(experiment_dir: Path, model_name: str):
         create_test_config(str(experiment_dir), str(experiment_dir))
 
 
-def preprocessing_signs(preprocessed_pose: Pose, sign_annotations: list, strategy: str, temp_dir: str):
+def preprocess_signs(preprocessed_pose: Pose, sign_annotations: list, strategy: str, temp_dir: str):
     temp_files = []  # list of temporary files
     start_point = 0
     temp_path = Path(temp_dir)
@@ -97,9 +97,8 @@ def main():
 
     print('Predicting signs...')
     with tempfile.TemporaryDirectory() as temp_dir:
-        temp_files = preprocessing_signs(preprocessed_pose, sign_annotations, args.strategy, temp_dir)
+        temp_files = preprocess_signs(preprocessed_pose, sign_annotations, args.strategy, temp_dir)
         hyp_list = translate('experiment/config.yaml', temp_files)
-        print('Cleaning up...')
 
     for index, (start, end, _) in enumerate(sign_annotations):
         eaf.remove_annotation('SIGN', start)

signwriting_transcription/pose_to_signwriting/data/pose_data_utils.py

@@ -35,9 +35,9 @@ def get_zip_manifest(zip_path: Path, npy_root: Optional[Path] = None):
     with zipfile.ZipFile(zip_path, mode="r") as file:
         info = file.infolist()
     # retrieve offsets
-    for i in tqdm(info):
-        utt_id = Path(i.filename).stem
-        offset, file_size = i.header_offset + 30 + len(i.filename), i.file_size
+    for index in tqdm(info):
+        utt_id = Path(index.filename).stem
+        offset, file_size = index.header_offset + 30 + len(index.filename), index.file_size
         with zip_path.open("rb") as file:
             file.seek(offset)
             data = file.read(file_size)

signwriting_transcription/pose_to_signwriting/data/prepare_poses.py

@@ -65,14 +65,14 @@ def get_split_data(dataset, feature_root, pumping):
     if EXPANDED_DATASET > len(all_data) and pumping:
         print("Pumping dataset...")
         backup = all_data.copy()
-        for i in range(EXPANDED_DATASET - len(backup)):
-            utt_id = backup[i % len(backup)]["id"]
-            n_frames = backup[i % len(backup)]["n_frames"]
-            trg = backup[i % len(backup)]["trg"]
-            src = backup[i % len(backup)]["src"]
-            split = backup[i % len(backup)]["split"]
+        for index in range(EXPANDED_DATASET - len(backup)):
+            utt_id = backup[index % len(backup)]["id"]
+            n_frames = backup[index % len(backup)]["n_frames"]
+            trg = backup[index % len(backup)]["trg"]
+            src = backup[index % len(backup)]["src"]
+            split = backup[index % len(backup)]["split"]
             all_data.append({
-                "id": f'{utt_id}({i})',  # unique id
+                "id": f'{utt_id}({index})',  # unique id
                 "src": src,
                 "n_frames": n_frames,
                 "trg": trg,