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config_.py
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config_.py
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model_config = dict(
dataset_type = "VidOR",
num_enti_cats = 81,
num_pred_cats = 51,
dim_ffn = 512,
dim_enti = 512,
dim_pred = 512,
dim_att = 512,
dim_feat = 1024, # dimension of each bbox's RoI feature, depend on the detector
dim_clsme = 300,
enco_pool_len = 4,
positive_vIoU_th= 0.5,
rt_triplets_topk = -1, # -1 for return all
EntiNameEmb_path= None,
use_clsme = True,
bias_matrix_path= "prepared_data/pred_bias_matrix_vidor.npy",
)
test_dataset_config = dict(
split = "val",
video_dir = '/home/gkf/project/VidVRD_VidOR/vidor-dataset/val_videos',
ann_dir = "/home/gkf/project/VidVRD_VidOR/vidor-dataset/annotation",
proposal_dir = "/home/gkf/project/deepSORT/tracking_results/miss60_minscore0p3/VidORval_freq1",
classeme_dir = "/home/gkf/project/deepSORT/tracking_results/miss60_minscore0p3/VidORval_freq1_classeme",
max_proposal = 180,
max_preds = 200,
score_th = 0.4,
dim_boxfeature = 1024,
min_frames_th = 15,
cache_tag = "MEGAv9_m60s0.3_freq1"
)
# test-dataset_cache_tag: v9
train_dataset_config = dict(
split = "train",
ann_dir = "/home/gkf/project/VidVRD_VidOR/vidor-dataset/annotation",
video_dir = "/home/gkf/project/VidVRD_VidOR/vidor-dataset/train_videos",
classeme_dir = "/home/gkf/project/deepSORT/tracking_results/miss60_minscore0p3/VidORtrain_freq1_classeme",
proposal_dir = {
0:"proposals/miss60_minscore0p3/VidORtrain_freq1_part01",
1:"proposals/miss60_minscore0p3/VidORtrain_freq1_part02",
2:"proposals/miss60_minscore0p3/VidORtrain_freq1_part03",
3:"proposals/miss60_minscore0p3/VidORtrain_freq1_part04",
4:"proposals/miss60_minscore0p3/VidORtrain_freq1_part05",
5:"proposals/miss60_minscore0p3/VidORtrain_freq1_part06",
6:"proposals/miss60_minscore0p3/VidORtrain_freq1_part07",
7:"proposals/miss60_minscore0p3/VidORtrain_freq1_part08",
8:"proposals/miss60_minscore0p3/VidORtrain_freq1_part09",
9:"proposals/miss60_minscore0p3/VidORtrain_freq1_part10",
10:"proposals/miss60_minscore0p3/VidORtrain_freq1_part11",
11:"proposals/miss60_minscore0p3/VidORtrain_freq1_part12",
12:"proposals/miss60_minscore0p3/VidORtrain_freq1_part13",
13:"proposals/miss60_minscore0p3/VidORtrain_freq1_part14",
},
cache_dir = "datasets/cache",
cache_tag = "MEGAv7",
dim_boxfeature = 1024,
min_frames_th = 15,
max_proposal = 180,
max_preds = 200,
score_th = 0.4
)
train_config = dict(
batch_size = 4,
total_epoch = 80,
initial_lr = 5e-5,
lr_decay = 0.2,
epoch_lr_milestones = [50],
)
inference_config = dict(
topk = 3,
)
extra_config = dict(
dataloader_name = "dataloader_vidor"
)
if __name__ == "__main__":
print(model_config)
print(train_dataset_config)