stable

configs/_base_/datasets/json/features_clips.py

@@ -1,16 +1,33 @@
 # classes = ("Medical",) 
-classes = 'datasets_jsons/soccernetv2/features/class.txt'
+classes = [
+    "Penalty",
+    "Kick-off",
+    "Goal",
+    "Substitution",
+    "Offside",
+    "Shots on target",
+    "Shots off target",
+    "Clearance",
+    "Ball out of play",
+    "Throw-in",
+    "Foul",
+    "Indirect free-kick",
+    "Direct free-kick",
+    "Corner",
+    "Yellow card",
+    "Red card",
+    "Yellow->red card",
+]
+# classes = 'datasets_jsons/soccernetv2/features/class.txt'
 # classes = '/scratch/users/ybenzakour/zip/features/class.txt'
 # classes = '/home/ybenzakour/datasets/SoccerNet/class.txt'
-extension = '.mkv'
 dataset = dict(
-    extension = extension,
     input_fps = 25,
     extract_fps = 2,
     train=dict(
         type="FeatureClipsfromJSON",
         path="train.json",
-        data_root = ["/home/ybenzakour/datasets/SoccerNet/","/home/ybenzakour/datasets/SoccerNet/"],
+        data_root = "/home/ybenzakour/datasets/SoccerNet/",
         framerate=2,
         window_size=20,
         classes=classes,
@@ -20,7 +37,7 @@
             shuffle=True,
             pin_memory=True,
         )),
-    val=dict(
+    valid=dict(
         type="FeatureClipsfromJSON",
         path="val.json",
         data_root = "/home/ybenzakour/datasets/SoccerNet/",

configs/_base_/datasets/json/features_clips_CALF.py

@@ -1,16 +1,33 @@
-# classes = ("Medical",) 
-classes = 'datasets_jsons/soccernetv2/features/class.txt'
+# classes = ("Medical",)
+classes = [
+    "Penalty",
+    "Kick-off",
+    "Goal",
+    "Substitution",
+    "Offside",
+    "Shots on target",
+    "Shots off target",
+    "Clearance",
+    "Ball out of play",
+    "Throw-in",
+    "Foul",
+    "Indirect free-kick",
+    "Direct free-kick",
+    "Corner",
+    "Yellow card",
+    "Red card",
+    "Yellow->red card",
+]
+# classes = 'datasets_jsons/soccernetv2/features/class.txt'
 # classes = '/scratch/users/ybenzakour/zip/features/class.txt'
 # classes = '/home/ybenzakour/datasets/SoccerNet/class.txt'
-extension = '.mkv'
 dataset = dict(
-    extension = extension,
-    input_fps = 25,
-    extract_fps = 2,
+    input_fps=25,
+    extract_fps=2,
     train=dict(
         type="FeatureClipChunksfromJson",
         path="train.json",
-        data_root = ["/home/ybenzakour/datasets/SoccerNet/","/home/ybenzakour/datasets/SoccerNet/"],
+        data_root="/home/ybenzakour/datasets/SoccerNet/",
         framerate=2,
         chunk_size=120,
         receptive_field=40,
@@ -21,11 +38,12 @@
             batch_size=256,
             shuffle=True,
             pin_memory=True,
-        )),
-    val=dict(
+        ),
+    ),
+    valid=dict(
         type="FeatureClipChunksfromJson",
         path="val.json",
-        data_root = "/home/ybenzakour/datasets/SoccerNet/",
+        data_root="/home/ybenzakour/datasets/SoccerNet/",
         framerate=2,
         chunk_size=120,
         receptive_field=40,
@@ -36,23 +54,25 @@
             batch_size=256,
             shuffle=True,
             pin_memory=True,
-        )),
+        ),
+    ),
     test=dict(
         type="FeatureVideosChunksfromJson",
         path="test.json",
-        data_root = "/home/ybenzakour/datasets/SoccerNet/",
+        data_root="/home/ybenzakour/datasets/SoccerNet/",
         framerate=2,
         chunk_size=120,
         receptive_field=40,
         chunks_per_epoch=6000,
         split=["test"],
         classes=classes,
-        metric = "loose",
-        results = "results_spotting_test",
+        metric="loose",
+        results="results_spotting_test",
         dataloader=dict(
             num_workers=1,
             batch_size=1,
             shuffle=False,
             pin_memory=True,
-        )),
+        ),
+    ),
 )

configs/_base_/datasets/json/video_dali.py

@@ -1,49 +1,41 @@
 classes = 'datasets_jsons/soccernetv2/2_fps/dali/class.txt'
-extension = '.mkv'
 dataset = dict(
-    batch_size = 8,
     epoch_num_frames  = 500000,
     mixup = True,
     modality = 'rgb',
     crop_dim = -1,
     dilate_len = 0,               # Dilate ground truth labels
     clip_len = 100,
-    extension = extension,
     input_fps = 25,
     extract_fps = 2,
     train=dict(
         type="VideoGameWithDali",
         classes=classes,
         output_map = ["data", "label"],
-        path = "datasets_jsons/soccernetv2/2_fps/dali/Train.json",               # path to label json
+        path = "/home/ybenzakour/224p/train/annotations.json",               # path to label json
         data_root = "/home/ybenzakour/datasets/SoccerNet/",
-        stride = 12,
         dataloader=dict(
             batch_size=8,
             shuffle=True,
         ),
     ),
-    val=dict(
+    valid=dict(
         type="VideoGameWithDali",
         classes=classes,
         output_map = ["data", "label"],
-        stride = 12,
-        path = "datasets_jsons/soccernetv2/2_fps/dali/Valid.json",                 # path to label json
+        path = "/home/ybenzakour/224p/valid/annotations.json",                 # path to label json
         data_root = "/home/ybenzakour/datasets/SoccerNet/",
-        extension = extension,
         dataloader=dict(
             batch_size=8,
             shuffle=True,
         ),
     ),
-    val_data_frames=dict(
+    valid_data_frames=dict(
         type="VideoGameWithDaliVideo",
         classes=classes,
-        stride = 12,
         output_map = ["data", "label"],
-        path = "datasets_jsons/soccernetv2/2_fps/dali/Valid.json",                 # path to label json
+        path = "/home/ybenzakour/224p/valid/annotations.json",                 # path to label json
         data_root = "/home/ybenzakour/datasets/SoccerNet/",
-        extension = extension,
         overlap_len = 0,
         dataloader=dict(
             batch_size=4,
@@ -52,12 +44,10 @@
     ),
     test = dict(
         type="VideoGameWithDaliVideo",
-        stride = 12,
         classes=classes,
         output_map = ["data", "label"],
-        path = "datasets_jsons/soccernetv2/2_fps/dali/Test.json",  # path to label json
+        path = "/home/ybenzakour/224p/test/annotations.json",  # path to label json
         data_root = "/home/ybenzakour/datasets/SoccerNet/",
-        extension = extension,
         split=["test"],
         results = "results_spotting_test",
         # results = "pred-test.141.recall.json.gz",
@@ -72,11 +62,9 @@
     challenge = dict(
         type="VideoGameWithDaliVideo",
         overlap_len = 50,
-        stride = 12,
         output_map = ["data", "label"],
-        path = "datasets_jsons/soccernetv2/2_fps/dali/Challenge.json",  # path to label json
+        path = "/home/ybenzakour/224p/challenge/annotations.json",  # path to label json
         data_root = "/home/ybenzakour/datasets/SoccerNet/",
-        extension = extension,
         dataloader=dict(
             batch_size=4,
             shuffle=False,

configs/_base_/datasets/json/video_ocv.py

@@ -1,8 +1,6 @@
 classes = 'datasets_jsons/soccernetv2/2_fps/dali/class.txt'
-extension = '.mkv'
 
 dataset = dict(
-    batch_size = 8,
     epoch_num_frames  = 500000,
     mixup = True,
     modality = 'rgb',
@@ -11,13 +9,11 @@
     clip_len = 100,
     input_fps = 25,
     extract_fps = 2,
-    extension = extension,
     train=dict(
         type="VideoGameWithOpencv",
         classes=classes,
-        path = "datasets_jsons/soccernetv2/2_fps/opencv/Train.json",                 # path to label json
+        path = "/home/ybenzakour/224p/train/annotations.json",                 # path to label json
         data_root = "/home/ybenzakour/datasets/SoccerNet/",
-        stride = 12,
         dataloader=dict(
             num_workers=8,
             batch_size=8,
@@ -26,12 +22,11 @@
             prefetch_factor = 1,
         ),
     ),
-    val=dict(
+    valid=dict(
         type="VideoGameWithOpencv",
         classes=classes,
-        path = "datasets_jsons/soccernetv2/2_fps/opencv/Valid.json",                 # path to label json
+        path = "/home/ybenzakour/224p/valid/annotations.json",                 # path to label json
         data_root = "/home/ybenzakour/datasets/SoccerNet/",
-        stride = 12,
         dataloader=dict(
             num_workers=8,
             batch_size=8,
@@ -40,12 +35,11 @@
             prefetch_factor = 1,
         ),
     ),
-    val_data_frames=dict(
+    valid_data_frames=dict(
         type="VideoGameWithOpencvVideo",
         classes=classes,
-        path = "datasets_jsons/soccernetv2/2_fps/opencv/Valid.json",                 # path to label json
+        path = "/home/ybenzakour/224p/valid/annotations.json",                 # path to label json
         data_root = "/home/ybenzakour/datasets/SoccerNet/",
-        stride = 12,
         overlap_len = 0,
         dataloader=dict(
             num_workers=8,
@@ -58,9 +52,8 @@
     test = dict(
         type="VideoGameWithOpencvVideo",
         classes=classes,
-        path = "datasets_jsons/soccernetv2/2_fps/opencv/Test.json",                 # path to label json
+        path = "/home/ybenzakour/224p/test/annotations.json",                 # path to label json
         data_root = "/home/ybenzakour/datasets/SoccerNet/",
-        stride = 12,
         split=["test"],
         results = "results_spotting_test_ocv",
         nms_window = 2,
@@ -76,9 +69,8 @@
     challenge = dict(
         type="VideoGameWithOpencvVideo",
         classes=classes,
-        path = "datasets_jsons/soccernetv2/2_fps/opencv/Challenge.json",                 # path to label json
+        path = "/home/ybenzakour/224p/challenge/annotations.json",                 # path to label json
         data_root = "/home/ybenzakour/datasets/SoccerNet/",
-        stride = 12,
         overlap_len = 50,
         dataloader=dict(
             num_workers=8,

configs/_base_/datasets/soccernet/features_clips.py

@@ -24,7 +24,7 @@
             shuffle=True,
             pin_memory=True,
         )),
-    val=dict(
+    valid=dict(
         type="SoccerNetClips",
         features="ResNET_TF2_PCA512.npy",
         version=2,

configs/_base_/datasets/soccernet/features_clips_CALF.py

@@ -26,7 +26,7 @@
             shuffle=True,
             pin_memory=True,
         )),
-    val=dict(
+    valid=dict(
         type="SoccerNetClipsCALF",
         features="ResNET_TF2_PCA512.npy",
         version=2,

configs/_base_/schedules/e2e_100_map.py

@@ -2,9 +2,9 @@
     type="trainer_e2e",
     num_epochs = 100,
     acc_grad_iter = 1,
-    base_num_val_epochs = 20,
-    start_val_epoch = None,
-    criterion_val = 'map',
+    base_num_valid_epochs = 20,
+    start_valid_epoch = None,
+    criterion_valid = 'map',
     inference_batch_size = 4,
     GPU = 1,
     criterion = dict(

configs/contextawarelossfunction/json_soccernet_calf_resnetpca512.py

@@ -7,10 +7,19 @@
 work_dir = "outputs/contextawarelossfunction/json_soccernet_calf_resnetpca512"
 
 dataset = dict(
-    train=dict(path=['datasets_jsons/soccernetv2/features/Train.json',"datasets_jsons/soccernetv2/features/Valid.json"]),
-    val=dict(path="datasets_jsons/soccernetv2/features/Valid.json"),
+    train=dict(path='datasets_jsons/soccernetv2/features/Train.json'),
+    valid=dict(path="datasets_jsons/soccernetv2/features/Valid.json"),
     test=dict(path="/scratch/users/ybenzakour/zip/features/Test.json")
 )
+log_level = 'INFO'  # The level of logging
+
 runner = dict(
     type="runner_JSON"
+)
+
+visualizer = dict(
+    threshold=0.0,
+    annotation_range=5000,  # ms
+    seconds_to_skip=30,
+    scale=1.5,
 )

configs/contextawarelossfunction/soccernet_resnetpca512.py

@@ -8,9 +8,10 @@
 
 dataset = dict(
     train=dict(features="ResNET_TF2_PCA512.npy"),
-    val=dict(features="ResNET_TF2_PCA512.npy"),
+    valid=dict(features="ResNET_TF2_PCA512.npy"),
     test=dict(features="ResNET_TF2_PCA512.npy")
 )
+log_level = 'INFO'  # The level of logging
 
 # model = dict(
 #     neck=dict(

configs/e2espot/e2espot.py

@@ -1,9 +1,18 @@
 _base_ = [
     "../_base_/datasets/json/video_dali.py",  # dataset config
     "../_base_/models/e2espot.py",  # model config,
-    "../_base_/schedules/e2e_100_map.py", #trainer config
+    "../_base_/schedules/e2e_100_map.py",  # trainer config
 ]
 
 work_dir = "outputs/e2e/rny008_gsm_150"
 
-dali = True
+log_level = "INFO"  # The level of logging
+
+dali = True
+
+visualizer = dict(
+    threshold=0.0,
+    annotation_range=5000,  # ms
+    seconds_to_skip=30,
+    scale=1.5,
+)

configs/e2espot/e2espot_ocv.py

@@ -6,4 +6,13 @@
 
 work_dir = "outputs/e2e/rny008_gsm_150"
 
-dali = False
+log_level = 'INFO'  # The level of logging
+
+dali = False
+
+visualizer = dict(
+    threshold=0.0,
+    annotation_range=5000,  # ms
+    seconds_to_skip=30,
+    scale=1.5,
+)