From 28bb5ed01d8287fab9ab08b5c5d542bb677fc260 Mon Sep 17 00:00:00 2001
From: Illia Oleksiienko <io@ece.au.dk>
Date: Tue, 1 Nov 2022 12:38:32 +0000
Subject: [PATCH] Add all track inference
---
run/eval_tracking_3d.py | 99 ++++++++++++++++++++++++++++++++---------
run/train_3d.py | 1 +
2 files changed, 80 insertions(+), 20 deletions(-)
diff --git a/run/eval_tracking_3d.py b/run/eval_tracking_3d.py
index 3275444c00..c7f2beda4b 100644
--- a/run/eval_tracking_3d.py
+++ b/run/eval_tracking_3d.py
@@ -51,7 +51,10 @@ subsets_path = os.path.join(
dataset_tracking_path = "/data/sets/kitti_tracking"
datasets = {}
-all_track_ids = ["0000"]
+all_track_ids = [
+ *["000" + str(i) for i in range(0, 10)],
+ *["00" + str(i) for i in range(10, 20 + 1)],
+]
for track_id in all_track_ids:
datasets[track_id] = LabeledTrackingPointCloudsDatasetIterator(
@@ -68,13 +71,14 @@ def save_detection_inference(
samples_list=[1],
config="xyres_16.proto",
eval_suffix="classic",
+ return_uncertainty=True,
):
config = os.path.join(config_roots[model_type], config,)
model_path = os.path.join(temp_dir, name)
learner = VoxelObjectDetection3DLearner(
- model_config_path=config, device=device, checkpoint_after_iter=1000, return_uncertainty=True
+ model_config_path=config, device=device, checkpoint_after_iter=1000, return_uncertainty=return_uncertainty
)
learner.load(model_path)
@@ -85,6 +89,8 @@ def save_detection_inference(
for track_id in all_track_ids:
dataset = datasets[track_id]
+
+ print("Track", track_id)
os.makedirs(os.path.join(
model_path, "tracking_inference_detections", eval_suffix, "samples_" + str(samples)
@@ -110,7 +116,6 @@ def save_detection_inference(
f.write(result)
-
def test_model(
model_type,
device="cuda:0",
@@ -118,25 +123,22 @@ def test_model(
samples_list=[1],
config="xyres_16.proto",
eval_suffix="classic",
+ mode="save_detection_inference",
+ return_uncertainty=True,
):
- return save_detection_inference(
- model_type=model_type,
- device=device,
- name=name,
- samples_list=samples_list,
- config=config,
- eval_suffix=eval_suffix,
- )
-
- # config = os.path.join(config_roots[model_type], config,)
- # model_path = os.path.join(temp_dir, name)
-
- # learner = VoxelObjectDetection3DLearner(
- # model_config_path=config, device=device, checkpoint_after_iter=1000
- # )
- # learner.load(model_path)
-
+ if mode == "save_detection_inference":
+ return save_detection_inference(
+ model_type=model_type,
+ device=device,
+ name=name,
+ samples_list=samples_list,
+ config=config,
+ eval_suffix=eval_suffix,
+ return_uncertainty=return_uncertainty,
+ )
+ else:
+ raise ValueError("Unknown mode " + str(mode))
def test_pointpillars(
@@ -153,6 +155,7 @@ def test_pointpillars(
samples_list=samples_list,
config=config,
eval_suffix=eval_suffix,
+ return_uncertainty=False,
)
@@ -170,6 +173,7 @@ def test_tanet(
samples_list=samples_list,
config=config,
eval_suffix=eval_suffix,
+ return_uncertainty=False,
)
@@ -188,6 +192,7 @@ def test_vnn_pointpillars(
eval_suffix=eval_suffix,
)
+
def test_vnna_pointpillars(
device="cuda:0",
name="vnna_pointpillars_car",
@@ -221,5 +226,59 @@ def test_vnn_tanet(
)
+def test_tapp(
+ device="cuda:0",
+ name="tapp_car",
+ samples_list=[1],
+ config="tapp_16.proto",
+ eval_suffix="classic",
+):
+ return test_model(
+ "tanet",
+ device=device,
+ name=name,
+ samples_list=samples_list,
+ config=config,
+ eval_suffix=eval_suffix,
+ return_uncertainty=False,
+ )
+
+
+def test_vnn_tapp(
+ device="cuda:0",
+ name="vnn_tapp_car",
+ samples_list=[1, 2, 3, 4],
+ config="vnn_tapp_16.proto",
+ eval_suffix="vnn",
+):
+ return test_model(
+ "tanet",
+ device=device,
+ name=name,
+ samples_list=samples_list,
+ config=config,
+ eval_suffix=eval_suffix,
+ )
+
+
+def all_save_detection_inference(start=0):
+ models = [
+ ("tapp_car", test_tapp),
+ ("pointpillars_car", test_pointpillars),
+ ("tanet_car", test_tanet),
+ *[("vnn_pointpillars_car_s" + str(i), test_vnn_pointpillars) for i in range(1, 7 + 1)],
+ *[("vnna_pointpillars_car_s" + str(i), test_vnna_pointpillars) for i in range(1, 4 + 1)],
+ *[("vnn_tanet_car_s" + str(i), test_vnn_tanet) for i in range(1, 3 + 1)],
+ *[("vnn_tapp_car_s" + str(i), test_vnn_tapp) for i in range(1, 3 + 1)],
+ ]
+
+ for i, (model_name, test_func) in enumerate(models):
+ print(":::", i + 1, "/", len(models))
+
+ if i < start:
+ continue
+
+ test_func(name=model_name)
+
if __name__ == "__main__":
fire.Fire()
diff --git a/run/train_3d.py b/run/train_3d.py
index 4be41991e3..313baddee5 100644
--- a/run/train_3d.py
+++ b/run/train_3d.py
@@ -314,6 +314,7 @@ def test_vnn_pointpillars(
eval_suffix=eval_suffix,
)
+
def test_vnna_pointpillars(
device="cuda:0",
name="vnna_pointpillars_car",
--
GitLab