Refactor config and patch small typo (#87)

docs/configs/index.md

@@ -1,3 +1,3 @@
 # DREEM Config API
 
-We utilize `.yaml` based configs with `hydra` and `omegaconf` for config parsing.
+We utilize `.yaml` based configs with [`hydra`](https://hydra.cc) and [`omegaconf`](https://omegaconf.readthedocs.io/en/2.3_branch/) for config parsing.

docs/configs/training.md

@@ -2,7 +2,7 @@
 
 Here, we describe the hyperparameters used for setting up training. Please see [here](./training.md#example-config) for an example training config.
 
-> Note: for using defaults, simply leave the field blank or don't include the key. Using `null` will initialize the value to `None` e.g
+> Note: for using defaults, simply leave the field blank or don't include the key. Using `null` will initialize the value to `None` which we use to represent turning off certain features such as logging, early stopping etc. e.g
 > ```YAML
 > model:
 >   d_model: #defaults to 1024 

dreem/inference/track.py

@@ -5,6 +5,7 @@
 from dreem.models import GTRRunner
 from omegaconf import DictConfig
 from pathlib import Path
+from datetime import datetime
 
 import hydra
 import os
@@ -14,9 +15,21 @@
 import sleap_io as sio
 import logging
 
+
 logger = logging.getLogger("dreem.inference")
 
 
+def get_timestamp() -> str:
+    """Get current timestamp.
+
+    Returns:
+        the current timestamp in /m/d/y-H:M:S format
+    """
+    date_time = datetime.now().strftime("%m-%d-%Y-%H:%M:%S")
+    print(date_time)
+    return date_time
+
+
 def export_trajectories(
     frames_pred: list["dreem.io.Frame"], save_path: str | None = None
 ) -> pd.DataFrame:
@@ -129,7 +142,11 @@ def run(cfg: DictConfig) -> dict[int, sio.Labels]:
         )
         dataloader = pred_cfg.get_dataloader(dataset, mode="test")
         preds = track(model, trainer, dataloader)
-        outpath = os.path.join(outdir, f"{Path(label_file).stem}.dreem_inference.slp")
+        outpath = os.path.join(
+            outdir, f"{Path(label_file).stem}.dreem_inference.{get_timestamp()}.slp"
+        )
+        if os.path.exists(outpath):
+            outpath.replace(".slp", ".")
         preds.save(outpath)
 
     return preds

dreem/inference/tracker.py

@@ -194,7 +194,7 @@ def sliding_inference(
 
                     for i, instance in enumerate(frames[batch_idx].instances):
                         if instance.pred_track_id == -1:
-                            curr_track += 1
+                            curr_track_id += 1
                             instance.pred_track_id = curr_track_id
 
             else: