diff --git a/README.md b/README.md
index 45b39dd..78e8007 100644
--- a/README.md
+++ b/README.md
@@ -162,7 +162,7 @@ conda activate yopo
tensorboard --logdir=./
```
-
+
Besides, you can refer to [traj_opt.yaml](YOPO/config/traj_opt.yaml) for modifications of trajectory optimization (e.g. the speed and penalties).
diff --git a/YOPO/loss/guidance_loss.py b/YOPO/loss/guidance_loss.py
index a4646a3..66e111b 100644
--- a/YOPO/loss/guidance_loss.py
+++ b/YOPO/loss/guidance_loss.py
@@ -26,6 +26,8 @@ class GuidanceLoss(nn.Module):
traj_dir = end_pos - cur_pos # [B, 3]
goal_dir = goal - cur_pos # [B, 3]
+ # NOTE: distance_loss performs better in general tasks, while we choose terminal_aware_similarity_loss only for higher speed in large-scale scenario.
+ # guidance_loss = self.distance_loss(traj_dir, goal_dir)
guidance_loss = self.terminal_aware_similarity_loss(traj_dir, goal_dir)
return guidance_loss
diff --git a/YOPO/policy/yopo_dataset.py b/YOPO/policy/yopo_dataset.py
index 6ececd5..2273e01 100644
--- a/YOPO/policy/yopo_dataset.py
+++ b/YOPO/policy/yopo_dataset.py
@@ -31,17 +31,18 @@ class YOPODataset(Dataset):
if mode == 'train': self.print_data()
# dataset
- print("Loading", mode, "dataset, it may take a while...")
base_dir = os.path.dirname(os.path.abspath(__file__))
data_dir = os.path.join(base_dir, "../", cfg["dataset_path"])
self.img_list, self.map_idx, self.positions, self.quaternions = [], [], np.empty((0, 3), dtype=np.float32), np.empty((0, 4), dtype=np.float32)
datafolders = [f.path for f in os.scandir(data_dir) if f.is_dir()]
datafolders.sort(key=lambda x: int(os.path.basename(x)))
- print("Datafolders:")
- for folder in datafolders:
- print(" ", folder)
+ if mode == 'train':
+ print("Datafolders:")
+ for folder in datafolders:
+ print(" ", folder)
+ print("Loading", mode, "dataset")
for data_idx in range(len(datafolders)):
datafolder = datafolders[data_idx]
@@ -75,7 +76,6 @@ class YOPODataset(Dataset):
print(f"{'Positions' :<12} | Count: {self.positions.shape[0]:<3} | Shape: {self.positions.shape[1]}")
print(f"{'Quaternions' :<12} | Count: {self.quaternions.shape[0]:<3} | Shape: {self.quaternions.shape[1]}")
print("==================================================")
- print(mode.capitalize(), "data loaded!")
def __len__(self):
return len(self.img_list)
@@ -210,10 +210,11 @@ class YOPODataset(Dataset):
if __name__ == '__main__':
+ # plot the random sample
dataset = YOPODataset()
- # dataset.plot_sample_distribution()
+ dataset.plot_sample_distribution()
- dataset = YOPODataset()
+ # select the best num_workers
max_workers = os.cpu_count()
print(f"\n✅ cpu_count = {max_workers}")
diff --git a/docs/train_log.png b/docs/train_log.png
index 7afb83e..96a87b5 100644
Binary files a/docs/train_log.png and b/docs/train_log.png differ