Merge pull request #88 from hsj576/dev

rearrange the filepath of examples
kubeedge · Dec 7, 2023 · 7e3b191 · 7e3b191
2 parents cd4d42e + abe40ec
commit 7e3b191
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diff --git a/...simulation/build_simulation_env/README.md → docs/guides/how-to-build-simulation-env.md b/...simulation/build_simulation_env/README.md → docs/guides/how-to-build-simulation-env.md
diff --git a/examples/pedestrian_tracking/README.md → ...rence_bench/pedestrian_tracking/README.md b/examples/pedestrian_tracking/README.md → ...rence_bench/pedestrian_tracking/README.md
@@ -47,7 +47,7 @@ Next, download pretrained model via [[google]](https://drive.google.com/file/d/1
 We are now ready to run the ianvs for benchmarking pedestrian tracking on the MOT17 dataset.
 
 ```python
-ianvs -f ./examples/pedestrian_tracking/multiedge_inference_bench/tracking_job.yaml
+ianvs -f ./examples/MOT17/multiedge_inference_bench/pedestrian_tracking/tracking_job.yaml
 ```
 
 The benchmarking process takes a few minutes and varies depending on devices.
@@ -78,7 +78,7 @@ Next, download pretrained model via [[google]](https://drive.google.com/drive/fo
 We are now ready to run the ianvs for benchmarking pedestrian re-identification on the MOT17 dataset.
 
 ```python
-ianvs -f ./examples/pedestrian_tracking/multiedge_inference_bench/reid_job.yaml
+ianvs -f ./examples/MOT17/multiedge_inference_bench/pedestrian_tracking/reid_job.yaml
 ```
 
 The benchmarking process takes a few minutes and varies depending on devices.
@@ -93,9 +93,9 @@ The final output might look like this:
 ## Step 3. Generate test report
 
 ```shell
-python ./examples/pedestrian_tracking/multiedge_inference_bench/generate_reports.py \
--t ./examples/pedestrian_tracking/multiedge_inference_bench/tracking_job.yaml \
--r ./examples/pedestrian_tracking/multiedge_inference_bench/reid_job.yaml
+python ./examples/MOT17/multiedge_inference_bench/pedestrian_tracking/generate_reports.py \
+-t ./examples/MOT17/multiedge_inference_bench/pedestrian_tracking/tracking_job.yaml \
+-r ./examples/MOT17/multiedge_inference_bench/pedestrian_tracking/reid_job.yaml
 ```
 
 Finally, the report is generated under <Ianvs_HOME>/examples/pedestrian_tracking/multiedge_inference_bench/reports. You can also check the sample report under the current directory.

diff --git a/...iedge_inference_bench/generate_reports.py → ...h/pedestrian_tracking/generate_reports.py b/...iedge_inference_bench/generate_reports.py → ...h/pedestrian_tracking/generate_reports.py
diff --git a/...g/multiedge_inference_bench/reid_job.yaml → ...e_bench/pedestrian_tracking/reid_job.yaml b/...g/multiedge_inference_bench/reid_job.yaml → ...e_bench/pedestrian_tracking/reid_job.yaml
diff --git a/...ltiedge_inference_bench/sample_report.pdf → ...nch/pedestrian_tracking/sample_report.pdf b/...ltiedge_inference_bench/sample_report.pdf → ...nch/pedestrian_tracking/sample_report.pdf
diff --git a/...ench/testalgorithms/reid/m3l/basemodel.py → ...king/testalgorithms/reid/m3l/basemodel.py b/...ench/testalgorithms/reid/m3l/basemodel.py → ...king/testalgorithms/reid/m3l/basemodel.py
diff --git a/...estalgorithms/reid/m3l/m3l_algorithm.yaml → ...estalgorithms/reid/m3l/m3l_algorithm.yaml b/...estalgorithms/reid/m3l/m3l_algorithm.yaml → ...estalgorithms/reid/m3l/m3l_algorithm.yaml
diff --git a/.../testalgorithms/reid/m3l/reid/__init__.py → .../testalgorithms/reid/m3l/reid/__init__.py b/.../testalgorithms/reid/m3l/reid/__init__.py → .../testalgorithms/reid/m3l/reid/__init__.py
diff --git a/...lgorithms/reid/m3l/reid/models/IBNMeta.py → ...lgorithms/reid/m3l/reid/models/IBNMeta.py b/...lgorithms/reid/m3l/reid/models/IBNMeta.py → ...lgorithms/reid/m3l/reid/models/IBNMeta.py
diff --git a/...ithms/reid/m3l/reid/models/MetaModules.py → ...ithms/reid/m3l/reid/models/MetaModules.py b/...ithms/reid/m3l/reid/models/MetaModules.py → ...ithms/reid/m3l/reid/models/MetaModules.py
diff --git a/...gorithms/reid/m3l/reid/models/__init__.py → ...gorithms/reid/m3l/reid/models/__init__.py b/...gorithms/reid/m3l/reid/models/__init__.py → ...gorithms/reid/m3l/reid/models/__init__.py
diff --git a/...lgorithms/reid/m3l/reid/models/resMeta.py → ...lgorithms/reid/m3l/reid/models/resMeta.py b/...lgorithms/reid/m3l/reid/models/resMeta.py → ...lgorithms/reid/m3l/reid/models/resMeta.py
diff --git a/...lgorithms/reid/m3l/reid/utils/__init__.py → ...lgorithms/reid/m3l/reid/utils/__init__.py b/...lgorithms/reid/m3l/reid/utils/__init__.py → ...lgorithms/reid/m3l/reid/utils/__init__.py
diff --git a/...thms/reid/m3l/reid/utils/data/__init__.py → ...thms/reid/m3l/reid/utils/data/__init__.py b/...thms/reid/m3l/reid/utils/data/__init__.py → ...thms/reid/m3l/reid/utils/data/__init__.py
diff --git a/.../reid/m3l/reid/utils/data/preprocessor.py → .../reid/m3l/reid/utils/data/preprocessor.py b/.../reid/m3l/reid/utils/data/preprocessor.py → .../reid/m3l/reid/utils/data/preprocessor.py
diff --git a/...ms/reid/m3l/reid/utils/data/transforms.py → ...ms/reid/m3l/reid/utils/data/transforms.py b/...ms/reid/m3l/reid/utils/data/transforms.py → ...ms/reid/m3l/reid/utils/data/transforms.py
diff --git a/...talgorithms/reid/m3l/reid/utils/meters.py → ...talgorithms/reid/m3l/reid/utils/meters.py b/...talgorithms/reid/m3l/reid/utils/meters.py → ...talgorithms/reid/m3l/reid/utils/meters.py
diff --git a/...algorithms/reid/m3l/reid/utils/osutils.py → ...algorithms/reid/m3l/reid/utils/osutils.py b/...algorithms/reid/m3l/reid/utils/osutils.py → ...algorithms/reid/m3l/reid/utils/osutils.py
diff --git a/...gorithms/tracking/byte_track/basemodel.py → ...gorithms/tracking/byte_track/basemodel.py b/...gorithms/tracking/byte_track/basemodel.py → ...gorithms/tracking/byte_track/basemodel.py
diff --git a/...king/byte_track/byte_track_algorithm.yaml → ...king/byte_track/byte_track_algorithm.yaml b/...king/byte_track/byte_track_algorithm.yaml → ...king/byte_track/byte_track_algorithm.yaml
diff --git a/...algorithms/tracking/byte_track/dataset.py → ...algorithms/tracking/byte_track/dataset.py b/...algorithms/tracking/byte_track/dataset.py → ...algorithms/tracking/byte_track/dataset.py
diff --git a/...s/tracking/byte_track/yolox_x_ablation.py → ...s/tracking/byte_track/yolox_x_ablation.py b/...s/tracking/byte_track/yolox_x_ablation.py → ...s/tracking/byte_track/yolox_x_ablation.py
diff --git a/...iedge_inference_bench/testenv/reid/cmc.py → ...h/pedestrian_tracking/testenv/reid/cmc.py b/...iedge_inference_bench/testenv/reid/cmc.py → ...h/pedestrian_tracking/testenv/reid/cmc.py
diff --git a/...iedge_inference_bench/testenv/reid/mAP.py → ...h/pedestrian_tracking/testenv/reid/mAP.py b/...iedge_inference_bench/testenv/reid/mAP.py → ...h/pedestrian_tracking/testenv/reid/mAP.py
diff --git a/...ge_inference_bench/testenv/reid/rank_1.py → ...edestrian_tracking/testenv/reid/rank_1.py b/...ge_inference_bench/testenv/reid/rank_1.py → ...edestrian_tracking/testenv/reid/rank_1.py
diff --git a/...ge_inference_bench/testenv/reid/rank_2.py → ...edestrian_tracking/testenv/reid/rank_2.py b/...ge_inference_bench/testenv/reid/rank_2.py → ...edestrian_tracking/testenv/reid/rank_2.py
diff --git a/...ge_inference_bench/testenv/reid/rank_5.py → ...edestrian_tracking/testenv/reid/rank_5.py b/...ge_inference_bench/testenv/reid/rank_5.py → ...edestrian_tracking/testenv/reid/rank_5.py
diff --git a/...inference_bench/testenv/reid/testenv.yaml → ...strian_tracking/testenv/reid/testenv.yaml b/...inference_bench/testenv/reid/testenv.yaml → ...strian_tracking/testenv/reid/testenv.yaml
diff --git a/...erence_bench/testenv/tracking/f1_score.py → ...ian_tracking/testenv/tracking/f1_score.py b/...erence_bench/testenv/tracking/f1_score.py → ...ian_tracking/testenv/tracking/f1_score.py
diff --git a/..._inference_bench/testenv/tracking/idf1.py → ...estrian_tracking/testenv/tracking/idf1.py b/..._inference_bench/testenv/tracking/idf1.py → ...estrian_tracking/testenv/tracking/idf1.py
diff --git a/..._inference_bench/testenv/tracking/mota.py → ...estrian_tracking/testenv/tracking/mota.py b/..._inference_bench/testenv/tracking/mota.py → ...estrian_tracking/testenv/tracking/mota.py
diff --git a/..._inference_bench/testenv/tracking/motp.py → ...estrian_tracking/testenv/tracking/motp.py b/..._inference_bench/testenv/tracking/motp.py → ...estrian_tracking/testenv/tracking/motp.py
diff --git a/...rence_bench/testenv/tracking/precision.py → ...an_tracking/testenv/tracking/precision.py b/...rence_bench/testenv/tracking/precision.py → ...an_tracking/testenv/tracking/precision.py
diff --git a/...nference_bench/testenv/tracking/recall.py → ...trian_tracking/testenv/tracking/recall.py b/...nference_bench/testenv/tracking/recall.py → ...trian_tracking/testenv/tracking/recall.py
diff --git a/...rence_bench/testenv/tracking/testenv.yaml → ...an_tracking/testenv/tracking/testenv.yaml b/...rence_bench/testenv/tracking/testenv.yaml → ...an_tracking/testenv/tracking/testenv.yaml
diff --git a/...ltiedge_inference_bench/tracking_job.yaml → ...nch/pedestrian_tracking/tracking_job.yaml b/...ltiedge_inference_bench/tracking_job.yaml → ...nch/pedestrian_tracking/tracking_job.yaml
diff --git a/...les/bdd/lifelong_learning_bench/README.md → ...g_learning_bench/curb-detection/README.md b/...les/bdd/lifelong_learning_bench/README.md → ...g_learning_bench/curb-detection/README.md
@@ -64,7 +64,7 @@ we have done that for you and the interested readers can refer to [testenv.yaml]
 
 Related algorithm is also ready in this quick start. 
 ``` shell
-export PYTHONPATH=$PYTHONPATH:/ianvs/project/examples/curb-detection/lifelong_learning_bench/testalgorithms/rfnet/RFNet
+export PYTHONPATH=$PYTHONPATH:/ianvs/project/examples/bdd/lifelong_learning_bench/curb-detection/testalgorithms/rfnet/RFNet
 ```
 
 The URL address of this algorithm then should be filled in the configuration file ``algorithm.yaml``. In this quick
@@ -115,7 +115,7 @@ We are now ready to run the ianvs for benchmarking.
 
 ``` shell
 cd /ianvs/project
-ianvs -f examples/bdd/lifelong_learning_bench/benchmarkingjob.yaml
+ianvs -f examples/bdd/lifelong_learning_bench/curb-detection/benchmarkingjob.yaml
 ```
 
 Finally, the user can check the result of benchmarking on the console and also in the output path(

diff --git a/...elong_learning_bench/benchmarkingjob.yaml → ...bench/curb-detection/benchmarkingjob.yaml b/...elong_learning_bench/benchmarkingjob.yaml → ...bench/curb-detection/benchmarkingjob.yaml
diff --git a/...ng_bench/testalgorithms/yolo/basemodel.py → ...etection/testalgorithms/yolo/basemodel.py b/...ng_bench/testalgorithms/yolo/basemodel.py → ...etection/testalgorithms/yolo/basemodel.py
diff --git a/...estalgorithms/yolo/inference_integrate.py → ...estalgorithms/yolo/inference_integrate.py b/...estalgorithms/yolo/inference_integrate.py → ...estalgorithms/yolo/inference_integrate.py
diff --git a/...hms/yolo/model_selector/choose_net_b64.py → ...hms/yolo/model_selector/choose_net_b64.py b/...hms/yolo/model_selector/choose_net_b64.py → ...hms/yolo/model_selector/choose_net_b64.py
@@ -1,106 +1,106 @@
-model = dict(
-    type='ImageClassifier',
-    backbone=dict(
-        type='ResNet',
-        depth=18,
-        num_stages=4,
-        out_indices=(3, ),
-        style='pytorch'),
-    neck=dict(type='GlobalAveragePooling'),
-    head=dict(
-        type='MultiLabelLinearClsHead',
-        num_classes=20,
-        in_channels=512,
-        loss=dict(type='CrossEntropyLoss', loss_weight=1.0, use_soft=True)))
-dataset_type = 'BDD_Performance'
-img_norm_cfg = dict(
-    mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
-train_pipeline = [
-    dict(type='LoadImageFromFile'),
-    dict(type='Resize', size=(256, -1)),
-    dict(
-        type='Normalize',
-        mean=[123.675, 116.28, 103.53],
-        std=[58.395, 57.12, 57.375],
-        to_rgb=True),
-    dict(type='ImageToTensor', keys=['img']),
-    dict(type='ToTensor', keys=['gt_label']),
-    dict(type='Collect', keys=['img', 'gt_label'])
-]
-test_pipeline = [
-    dict(type='LoadImageFromFile'),
-    dict(type='Resize', size=(256, -1)),
-    dict(
-        type='Normalize',
-        mean=[123.675, 116.28, 103.53],
-        std=[58.395, 57.12, 57.375],
-        to_rgb=True),
-    dict(type='ImageToTensor', keys=['img']),
-    dict(type='Collect', keys=['img'])
-]
-data = dict(
-    samples_per_gpu=64,
-    workers_per_gpu=2,
-    train=dict(
-        type='BDD_Performance',
-        data_prefix='',
-        ann_file=
-        '/home/liyunzhe/Mobile-Inference/algorithm/labels/0129_real_world_multi_label_remo_xyxy_bdd_train.txt',
-        pipeline=[
-            dict(type='LoadImageFromFile'),
-            dict(type='Resize', size=(256, -1)),
-            dict(
-                type='Normalize',
-                mean=[123.675, 116.28, 103.53],
-                std=[58.395, 57.12, 57.375],
-                to_rgb=True),
-            dict(type='ImageToTensor', keys=['img']),
-            dict(type='ToTensor', keys=['gt_label']),
-            dict(type='Collect', keys=['img', 'gt_label'])
-        ]),
-    val=dict(
-        type='BDD_Performance',
-        data_prefix='',
-        ann_file=
-        '/home/liyunzhe/Mobile-Inference/algorithm/labels/0129_real_world_multi_label_remo_xyxy_bdd_val.txt',
-        pipeline=[
-            dict(type='LoadImageFromFile'),
-            dict(type='Resize', size=(256, -1)),
-            dict(
-                type='Normalize',
-                mean=[123.675, 116.28, 103.53],
-                std=[58.395, 57.12, 57.375],
-                to_rgb=True),
-            dict(type='ImageToTensor', keys=['img']),
-            dict(type='Collect', keys=['img'])
-        ]),
-    test=dict(
-        type='BDD_Performance',
-        data_prefix='',
-        ann_file=
-        '/home/liyunzhe/Mobile-Inference/algorithm/labels/0129_real_world_multi_label_remo_xyxy_bdd_val.txt',
-        pipeline=[
-            dict(type='LoadImageFromFile'),
-            dict(type='Resize', size=(256, -1)),
-            dict(
-                type='Normalize',
-                mean=[123.675, 116.28, 103.53],
-                std=[58.395, 57.12, 57.375],
-                to_rgb=True),
-            dict(type='ImageToTensor', keys=['img']),
-            dict(type='Collect', keys=['img'])
-        ]))
-evaluation = dict(interval=1, metric='mAP')
-optimizer = dict(type='SGD', lr=0.1, momentum=0.9, weight_decay=0.0001)
-optimizer_config = dict(grad_clip=None)
-lr_config = dict(policy='step', step=[30, 60, 90])
-runner = dict(type='EpochBasedRunner', max_epochs=100)
-checkpoint_config = dict(interval=1)
-log_config = dict(interval=100, hooks=[dict(type='TextLoggerHook')])
-dist_params = dict(backend='nccl')
-log_level = 'INFO'
-load_from = None
-resume_from = None
-workflow = [('train', 1)]
-work_dir = 'work_dirs/220208-bdd-best'
+model = dict(
+    type='ImageClassifier',
+    backbone=dict(
+        type='ResNet',
+        depth=18,
+        num_stages=4,
+        out_indices=(3, ),
+        style='pytorch'),
+    neck=dict(type='GlobalAveragePooling'),
+    head=dict(
+        type='MultiLabelLinearClsHead',
+        num_classes=20,
+        in_channels=512,
+        loss=dict(type='CrossEntropyLoss', loss_weight=1.0, use_soft=True)))
+dataset_type = 'BDD_Performance'
+img_norm_cfg = dict(
+    mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
+train_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(type='Resize', size=(256, -1)),
+    dict(
+        type='Normalize',
+        mean=[123.675, 116.28, 103.53],
+        std=[58.395, 57.12, 57.375],
+        to_rgb=True),
+    dict(type='ImageToTensor', keys=['img']),
+    dict(type='ToTensor', keys=['gt_label']),
+    dict(type='Collect', keys=['img', 'gt_label'])
+]
+test_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(type='Resize', size=(256, -1)),
+    dict(
+        type='Normalize',
+        mean=[123.675, 116.28, 103.53],
+        std=[58.395, 57.12, 57.375],
+        to_rgb=True),
+    dict(type='ImageToTensor', keys=['img']),
+    dict(type='Collect', keys=['img'])
+]
+data = dict(
+    samples_per_gpu=64,
+    workers_per_gpu=2,
+    train=dict(
+        type='BDD_Performance',
+        data_prefix='',
+        ann_file=
+        '/home/liyunzhe/Mobile-Inference/algorithm/labels/0129_real_world_multi_label_remo_xyxy_bdd_train.txt',
+        pipeline=[
+            dict(type='LoadImageFromFile'),
+            dict(type='Resize', size=(256, -1)),
+            dict(
+                type='Normalize',
+                mean=[123.675, 116.28, 103.53],
+                std=[58.395, 57.12, 57.375],
+                to_rgb=True),
+            dict(type='ImageToTensor', keys=['img']),
+            dict(type='ToTensor', keys=['gt_label']),
+            dict(type='Collect', keys=['img', 'gt_label'])
+        ]),
+    val=dict(
+        type='BDD_Performance',
+        data_prefix='',
+        ann_file=
+        '/home/liyunzhe/Mobile-Inference/algorithm/labels/0129_real_world_multi_label_remo_xyxy_bdd_val.txt',
+        pipeline=[
+            dict(type='LoadImageFromFile'),
+            dict(type='Resize', size=(256, -1)),
+            dict(
+                type='Normalize',
+                mean=[123.675, 116.28, 103.53],
+                std=[58.395, 57.12, 57.375],
+                to_rgb=True),
+            dict(type='ImageToTensor', keys=['img']),
+            dict(type='Collect', keys=['img'])
+        ]),
+    test=dict(
+        type='BDD_Performance',
+        data_prefix='',
+        ann_file=
+        '/home/liyunzhe/Mobile-Inference/algorithm/labels/0129_real_world_multi_label_remo_xyxy_bdd_val.txt',
+        pipeline=[
+            dict(type='LoadImageFromFile'),
+            dict(type='Resize', size=(256, -1)),
+            dict(
+                type='Normalize',
+                mean=[123.675, 116.28, 103.53],
+                std=[58.395, 57.12, 57.375],
+                to_rgb=True),
+            dict(type='ImageToTensor', keys=['img']),
+            dict(type='Collect', keys=['img'])
+        ]))
+evaluation = dict(interval=1, metric='mAP')
+optimizer = dict(type='SGD', lr=0.1, momentum=0.9, weight_decay=0.0001)
+optimizer_config = dict(grad_clip=None)
+lr_config = dict(policy='step', step=[30, 60, 90])
+runner = dict(type='EpochBasedRunner', max_epochs=100)
+checkpoint_config = dict(interval=1)
+log_config = dict(interval=100, hooks=[dict(type='TextLoggerHook')])
+dist_params = dict(backend='nccl')
+log_level = 'INFO'
+load_from = None
+resume_from = None
+workflow = [('train', 1)]
+work_dir = 'work_dirs/220208-bdd-best'
 gpu_ids = range(0, 1)
diff --git a/...orithms/yolo/task_allocation_by_origin.py → ...orithms/yolo/task_allocation_by_origin.py b/...orithms/yolo/task_allocation_by_origin.py → ...orithms/yolo/task_allocation_by_origin.py
diff --git a/...ch/testalgorithms/yolo/task_remodeling.py → ...on/testalgorithms/yolo/task_remodeling.py b/...ch/testalgorithms/yolo/task_remodeling.py → ...on/testalgorithms/yolo/task_remodeling.py
diff --git a/...h/testalgorithms/yolo/yolo_algorithm.yaml → ...n/testalgorithms/yolo/yolo_algorithm.yaml b/...h/testalgorithms/yolo/yolo_algorithm.yaml → ...n/testalgorithms/yolo/yolo_algorithm.yaml
diff --git a/...dd/lifelong_learning_bench/testenv/map.py → ...rning_bench/curb-detection/testenv/map.py b/...dd/lifelong_learning_bench/testenv/map.py → ...rning_bench/curb-detection/testenv/map.py
diff --git a/...elong_learning_bench/testenv/testenv.yaml → ...bench/curb-detection/testenv/testenv.yaml b/...elong_learning_bench/testenv/testenv.yaml → ...bench/curb-detection/testenv/testenv.yaml
diff --git a/...tection/lifelong_learning_bench/README.md → ...g_learning_bench/curb-detection/README.md b/...tection/lifelong_learning_bench/README.md → ...g_learning_bench/curb-detection/README.md
@@ -68,7 +68,7 @@ we have done that for you and the interested readers can refer to [testenv.yaml]
 
 Related algorithm is also ready in this quick start. 
 ``` shell
-export PYTHONPATH=$PYTHONPATH:/ianvs/project/ianvs/examples/curb-detection/lifelong_learning_bench/testalgorithms/rfnet/RFNet
+export PYTHONPATH=$PYTHONPATH:/ianvs/project/ianvs/examples/cityscapes-synthia/lifelong_learning_bench/curb-detection/testalgorithms/rfnet/RFNet
 ```
 
 The URL address of this algorithm then should be filled in the configuration file ``algorithm.yaml``. In this quick
@@ -80,7 +80,7 @@ We are now ready to run the ianvs for benchmarking.
 
 ``` shell
 cd /ianvs/project/ianvs
-ianvs -f examples/curb-detection/lifelong_learning_bench/benchmarkingjob.yaml
+ianvs -f examples/cityscapes-synthia/lifelong_learning_bench/curb-detection/benchmarkingjob.yaml
 ```
 
 Finally, the user can check the result of benchmarking on the console and also in the output path(

diff --git a/...elong_learning_bench/benchmarkingjob.yaml → ...bench/curb-detection/benchmarkingjob.yaml b/...elong_learning_bench/benchmarkingjob.yaml → ...bench/curb-detection/benchmarkingjob.yaml
diff --git a/...ch/testalgorithms/rfnet/RFNet/accuracy.py → ...on/testalgorithms/rfnet/RFNet/accuracy.py b/...ch/testalgorithms/rfnet/RFNet/accuracy.py → ...on/testalgorithms/rfnet/RFNet/accuracy.py
diff --git a/...h/testalgorithms/rfnet/RFNet/basemodel.py → ...n/testalgorithms/rfnet/RFNet/basemodel.py b/...h/testalgorithms/rfnet/RFNet/basemodel.py → ...n/testalgorithms/rfnet/RFNet/basemodel.py
diff --git a/...ithms/rfnet/RFNet/dataloaders/__init__.py → ...ithms/rfnet/RFNet/dataloaders/__init__.py b/...ithms/rfnet/RFNet/dataloaders/__init__.py → ...ithms/rfnet/RFNet/dataloaders/__init__.py
diff --git a/...et/RFNet/dataloaders/custom_transforms.py → ...et/RFNet/dataloaders/custom_transforms.py b/...et/RFNet/dataloaders/custom_transforms.py → ...et/RFNet/dataloaders/custom_transforms.py
diff --git a/...FNet/dataloaders/custom_transforms_rgb.py → ...FNet/dataloaders/custom_transforms_rgb.py b/...FNet/dataloaders/custom_transforms_rgb.py → ...FNet/dataloaders/custom_transforms_rgb.py
diff --git a/...t/ERFNet/dataloaders/datasets/__init__.py → ...et/RFNet/dataloaders/datasets/__init__.py b/...t/ERFNet/dataloaders/datasets/__init__.py → ...et/RFNet/dataloaders/datasets/__init__.py
diff --git a/...Net/dataloaders/datasets/citylostfound.py → ...Net/dataloaders/datasets/citylostfound.py b/...Net/dataloaders/datasets/citylostfound.py → ...Net/dataloaders/datasets/citylostfound.py
diff --git a/...t/ERFNet/dataloaders/datasets/cityrand.py → ...et/RFNet/dataloaders/datasets/cityrand.py b/...t/ERFNet/dataloaders/datasets/cityrand.py → ...et/RFNet/dataloaders/datasets/cityrand.py
diff --git a/.../RFNet/dataloaders/datasets/cityscapes.py → .../RFNet/dataloaders/datasets/cityscapes.py b/.../RFNet/dataloaders/datasets/cityscapes.py → .../RFNet/dataloaders/datasets/cityscapes.py
diff --git a/.../erfnet/ERFNet/dataloaders/datasets/e1.py → ...ms/rfnet/RFNet/dataloaders/datasets/e1.py b/.../erfnet/ERFNet/dataloaders/datasets/e1.py → ...ms/rfnet/RFNet/dataloaders/datasets/e1.py
diff --git a/.../ERFNet/dataloaders/datasets/mapillary.py → ...t/RFNet/dataloaders/datasets/mapillary.py b/.../ERFNet/dataloaders/datasets/mapillary.py → ...t/RFNet/dataloaders/datasets/mapillary.py
diff --git a/...net/ERFNet/dataloaders/datasets/target.py → ...fnet/RFNet/dataloaders/datasets/target.py b/...net/ERFNet/dataloaders/datasets/target.py → ...fnet/RFNet/dataloaders/datasets/target.py
diff --git a/...rfnet/RFNet/dataloaders/datasets/temp.txt → ...rfnet/RFNet/dataloaders/datasets/temp.txt b/...rfnet/RFNet/dataloaders/datasets/temp.txt → ...rfnet/RFNet/dataloaders/datasets/temp.txt
diff --git a/...fnet/ERFNet/dataloaders/datasets/xrlab.py → ...rfnet/RFNet/dataloaders/datasets/xrlab.py b/...fnet/ERFNet/dataloaders/datasets/xrlab.py → ...rfnet/RFNet/dataloaders/datasets/xrlab.py
diff --git a/...rithms/erfnet/ERFNet/dataloaders/utils.py → ...gorithms/rfnet/RFNet/dataloaders/utils.py b/...rithms/erfnet/ERFNet/dataloaders/utils.py → ...gorithms/rfnet/RFNet/dataloaders/utils.py
diff --git a/..._bench/testalgorithms/rfnet/RFNet/eval.py → ...ection/testalgorithms/rfnet/RFNet/eval.py b/..._bench/testalgorithms/rfnet/RFNet/eval.py → ...ection/testalgorithms/rfnet/RFNet/eval.py
diff --git a/...orithms/erfnet/ERFNet/models/replicate.py → ...lgorithms/rfnet/RFNet/models/replicate.py b/...orithms/erfnet/ERFNet/models/replicate.py → ...lgorithms/rfnet/RFNet/models/replicate.py
diff --git a/...lgorithms/erfnet/ERFNet/utils/__init__.py → ...hms/rfnet/RFNet/models/resnet/__init__.py b/...lgorithms/erfnet/ERFNet/utils/__init__.py → ...hms/rfnet/RFNet/models/resnet/__init__.py
diff --git a/...t/resnet_single_scale_single_attention.py → ...t/resnet_single_scale_single_attention.py b/...t/resnet_single_scale_single_attention.py → ...t/resnet_single_scale_single_attention.py
diff --git a/...t_single_scale_single_attention_unseen.py → ...t_single_scale_single_attention_unseen.py b/...t_single_scale_single_attention_unseen.py → ...t_single_scale_single_attention_unseen.py
diff --git a/...estalgorithms/rfnet/RFNet/models/rfnet.py → ...estalgorithms/rfnet/RFNet/models/rfnet.py b/...estalgorithms/rfnet/RFNet/models/rfnet.py → ...estalgorithms/rfnet/RFNet/models/rfnet.py
diff --git a/...ms/rfnet/RFNet/models/rfnet_for_unseen.py → ...ms/rfnet/RFNet/models/rfnet_for_unseen.py b/...ms/rfnet/RFNet/models/rfnet_for_unseen.py → ...ms/rfnet/RFNet/models/rfnet_for_unseen.py
diff --git a/...stalgorithms/erfnet/ERFNet/models/util.py → ...testalgorithms/rfnet/RFNet/models/util.py b/...stalgorithms/erfnet/ERFNet/models/util.py → ...testalgorithms/rfnet/RFNet/models/util.py
diff --git a/...ench/testalgorithms/rfnet/RFNet/mypath.py → ...tion/testalgorithms/rfnet/RFNet/mypath.py b/...ench/testalgorithms/rfnet/RFNet/mypath.py → ...tion/testalgorithms/rfnet/RFNet/mypath.py
diff --git a/...nch/testalgorithms/rfnet/RFNet/predict.py → ...ion/testalgorithms/rfnet/RFNet/predict.py b/...nch/testalgorithms/rfnet/RFNet/predict.py → ...ion/testalgorithms/rfnet/RFNet/predict.py
diff --git a/.../testalgorithms/rfnet/RFNet/run_server.py → .../testalgorithms/rfnet/RFNet/run_server.py b/.../testalgorithms/rfnet/RFNet/run_server.py → .../testalgorithms/rfnet/RFNet/run_server.py
diff --git a/...talgorithms/rfnet/RFNet/sedna_evaluate.py → ...talgorithms/rfnet/RFNet/sedna_evaluate.py b/...talgorithms/rfnet/RFNet/sedna_evaluate.py → ...talgorithms/rfnet/RFNet/sedna_evaluate.py
diff --git a/...stalgorithms/rfnet/RFNet/sedna_predict.py → ...stalgorithms/rfnet/RFNet/sedna_predict.py b/...stalgorithms/rfnet/RFNet/sedna_predict.py → ...stalgorithms/rfnet/RFNet/sedna_predict.py
diff --git a/...stalgorithms/erfnet/ERFNet/sedna_train.py → ...testalgorithms/rfnet/RFNet/sedna_train.py b/...stalgorithms/erfnet/ERFNet/sedna_train.py → ...testalgorithms/rfnet/RFNet/sedna_train.py
diff --git a/..._bench/testalgorithms/rfnet/RFNet/test.py → ...ection/testalgorithms/rfnet/RFNet/test.py b/..._bench/testalgorithms/rfnet/RFNet/test.py → ...ection/testalgorithms/rfnet/RFNet/test.py
diff --git a/...bench/testalgorithms/rfnet/RFNet/train.py → ...ction/testalgorithms/rfnet/RFNet/train.py b/...bench/testalgorithms/rfnet/RFNet/train.py → ...ction/testalgorithms/rfnet/RFNet/train.py
diff --git a/...et/RFNet/dataloaders/datasets/__init__.py → ...talgorithms/rfnet/RFNet/utils/__init__.py b/...et/RFNet/dataloaders/datasets/__init__.py → ...talgorithms/rfnet/RFNet/utils/__init__.py
diff --git a/.../testalgorithms/rfnet/RFNet/utils/args.py → .../testalgorithms/rfnet/RFNet/utils/args.py b/.../testalgorithms/rfnet/RFNet/utils/args.py → .../testalgorithms/rfnet/RFNet/utils/args.py
diff --git a/.../erfnet/ERFNet/utils/calculate_weights.py → ...ms/rfnet/RFNet/utils/calculate_weights.py b/.../erfnet/ERFNet/utils/calculate_weights.py → ...ms/rfnet/RFNet/utils/calculate_weights.py
diff --git a/...stalgorithms/rfnet/RFNet/utils/iouEval.py → ...stalgorithms/rfnet/RFNet/utils/iouEval.py b/...stalgorithms/rfnet/RFNet/utils/iouEval.py → ...stalgorithms/rfnet/RFNet/utils/iouEval.py
diff --git a/.../testalgorithms/rfnet/RFNet/utils/loss.py → .../testalgorithms/rfnet/RFNet/utils/loss.py b/.../testalgorithms/rfnet/RFNet/utils/loss.py → .../testalgorithms/rfnet/RFNet/utils/loss.py
diff --git a/...ithms/erfnet/ERFNet/utils/lr_scheduler.py → ...orithms/rfnet/RFNet/utils/lr_scheduler.py b/...ithms/erfnet/ERFNet/utils/lr_scheduler.py → ...orithms/rfnet/RFNet/utils/lr_scheduler.py
diff --git a/...stalgorithms/rfnet/RFNet/utils/metrics.py → ...stalgorithms/rfnet/RFNet/utils/metrics.py b/...stalgorithms/rfnet/RFNet/utils/metrics.py → ...stalgorithms/rfnet/RFNet/utils/metrics.py
diff --git a/...stalgorithms/erfnet/ERFNet/utils/saver.py → ...testalgorithms/rfnet/RFNet/utils/saver.py b/...stalgorithms/erfnet/ERFNet/utils/saver.py → ...testalgorithms/rfnet/RFNet/utils/saver.py
diff --git a/...gorithms/erfnet/ERFNet/utils/summaries.py → ...algorithms/rfnet/RFNet/utils/summaries.py b/...gorithms/erfnet/ERFNet/utils/summaries.py → ...algorithms/rfnet/RFNet/utils/summaries.py
diff --git a/...g_bench/testalgorithms/rfnet/basemodel.py → ...tection/testalgorithms/rfnet/basemodel.py b/...g_bench/testalgorithms/rfnet/basemodel.py → ...tection/testalgorithms/rfnet/basemodel.py
diff --git a/...testalgorithms/rfnet/rfnet_algorithm.yaml → ...testalgorithms/rfnet/rfnet_algorithm.yaml b/...testalgorithms/rfnet/rfnet_algorithm.yaml → ...testalgorithms/rfnet/rfnet_algorithm.yaml
diff --git a/...rithms/rfnet/task_allocation_by_origin.py → ...rithms/rfnet/task_allocation_by_origin.py b/...rithms/rfnet/task_allocation_by_origin.py → ...rithms/rfnet/task_allocation_by_origin.py
diff --git a/...rithms/rfnet/task_definition_by_origin.py → ...rithms/rfnet/task_definition_by_origin.py b/...rithms/rfnet/task_definition_by_origin.py → ...rithms/rfnet/task_definition_by_origin.py
diff --git a/...felong_learning_bench/testenv/accuracy.py → ..._bench/curb-detection/testenv/accuracy.py b/...felong_learning_bench/testenv/accuracy.py → ..._bench/curb-detection/testenv/accuracy.py
diff --git a/...elong_learning_bench/testenv/testenv.yaml → ...bench/curb-detection/testenv/testenv.yaml b/...elong_learning_bench/testenv/testenv.yaml → ...bench/curb-detection/testenv/testenv.yaml
diff --git a/...ntation/lifelong_learning_bench/README.md → ...ing_bench/semantic-segmentation/README.md b/...ntation/lifelong_learning_bench/README.md → ...ing_bench/semantic-segmentation/README.md
@@ -13,6 +13,7 @@ Before using Ianvs, you might want to have the device ready:
 - Internet connection for GitHub and pip, etc
 - Python 3.6+ installed
 
+
 In this example, we are using the Linux platform with Python 3.8.5. If you are using Windows, most steps should still apply but a few like commands and package requirements might be different. 
 
 ## Step 1. Ianvs Preparation
@@ -65,15 +66,15 @@ we have done that for you and the interested readers can refer to [testenv.yaml]
 Copy the index files of dataset.
 
 ``` shell
-cp /ianvs/project/ianvs/examples/semantic_segmentation/lifelong_learning_bench/indexes/* /root/data/semantic_segmentation_dataset/
+cp /ianvs/project/ianvs/examples/cityscapes-synthia/lifelong_learning_bench/semantic-segmentation/indexes/* /root/data/semantic_segmentation_dataset/
 ```
 
 <!-- Please put the downloaded dataset on the above dataset path, e.g., `/ianvs/dataset`. One can transfer the dataset to the path, e.g., on a remote Linux system using [XFTP].  -->
 
 
 Related algorithm is also ready in this quick start. 
 ``` shell
-export PYTHONPATH=$PYTHONPATH:/ianvs/project/ianvs/examples/semantic_segmentation/lifelong_learning_bench/testalgorithms/rfnet/RFNet
+export PYTHONPATH=$PYTHONPATH:/ianvs/project/ianvs/examples/cityscapes-synthia/lifelong_learning_bench/semantic-segmentation/testalgorithms/rfnet/RFNet
 ```
 
 The URL address of this algorithm then should be filled in the configuration file ``algorithm.yaml``. In this quick
@@ -85,7 +86,7 @@ We are now ready to run the ianvs for benchmarking.
 
 ``` shell
 cd /ianvs/project/ianvs
-ianvs -f examples/semantic_segmentation/lifelong_learning_bench/benchmarkingjob-smalltest.yaml
+ianvs -f examples/cityscapes-synthia/lifelong_learning_bench/semantic-segmentation/benchmarkingjob-smalltest.yaml
 ```
 
 Finally, the user can check the result of benchmarking on the console and also in the output path(

diff --git a/...rning_bench/benchmarkingjob-fulltest.yaml → ...egmentation/benchmarkingjob-fulltest.yaml b/...rning_bench/benchmarkingjob-fulltest.yaml → ...egmentation/benchmarkingjob-fulltest.yaml
diff --git a/...ning_bench/benchmarkingjob-smalltest.yaml → ...gmentation/benchmarkingjob-smalltest.yaml b/...ning_bench/benchmarkingjob-smalltest.yaml → ...gmentation/benchmarkingjob-smalltest.yaml
diff --git a/...ing_bench/benchmarkingjob-traveltest.yaml → ...mentation/benchmarkingjob-traveltest.yaml b/...ing_bench/benchmarkingjob-traveltest.yaml → ...mentation/benchmarkingjob-traveltest.yaml
diff --git a/...elong_learning_bench/benchmarkingjob.yaml → ...emantic-segmentation/benchmarkingjob.yaml b/...elong_learning_bench/benchmarkingjob.yaml → ...emantic-segmentation/benchmarkingjob.yaml