_base_ = ['./slowonly_k400_pretrained_r50_8x4x1_40e_ucf101_rgb.py']

# model settings
model = dict(cls_head=dict(num_classes=51))

# dataset settings
split = 1
dataset_type = 'RawframeDataset'
data_root = 'data/hmdb51/rawframes'
data_root_val = 'data/hmdb51/rawframes'
ann_file_train = f'data/hmdb51/hmdb51_train_split_{split}_rawframes.txt'
ann_file_val = f'data/hmdb51/hmdb51_val_split_{split}_rawframes.txt'
ann_file_test = f'data/hmdb51/hmdb51_val_split_{split}_rawframes.txt'
img_norm_cfg = dict(
    mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_bgr=False)

train_pipeline = [
    dict(type='SampleFrames', clip_len=8, frame_interval=4, num_clips=1),
    dict(type='RawFrameDecode'),
    dict(type='Resize', scale=(-1, 256)),
    dict(type='RandomResizedCrop'),
    dict(type='Resize', scale=(224, 224), keep_ratio=False),
    dict(type='Flip', flip_ratio=0.5),
    dict(type='Normalize', **img_norm_cfg),
    dict(type='FormatShape', input_format='NCTHW'),
    dict(type='PackActionInputs')
]
val_pipeline = [
    dict(
        type='SampleFrames',
        clip_len=8,
        frame_interval=4,
        num_clips=1,
        test_mode=True),
    dict(type='RawFrameDecode'),
    dict(type='Resize', scale=(-1, 256)),
    dict(type='CenterCrop', crop_size=224),
    dict(type='Normalize', **img_norm_cfg),
    dict(type='FormatShape', input_format='NCTHW'),
    dict(type='PackActionInputs')
]
test_pipeline = [
    dict(
        type='SampleFrames',
        clip_len=8,
        frame_interval=4,
        num_clips=10,
        test_mode=True),
    dict(type='RawFrameDecode'),
    dict(type='Resize', scale=(-1, 256)),
    dict(type='ThreeCrop', crop_size=256),
    dict(type='Normalize', **img_norm_cfg),
    dict(type='FormatShape', input_format='NCTHW'),
    dict(type='PackActionInputs')
]

train_dataloader = dict(
    batch_size=8,
    num_workers=2,
    persistent_workers=True,
    sampler=dict(type='DefaultSampler', shuffle=True),
    dataset=dict(
        type=dataset_type,
        ann_file=ann_file_train,
        data_prefix=dict(img=data_root),
        pipeline=train_pipeline))
val_dataloader = dict(
    batch_size=8,
    num_workers=2,
    persistent_workers=True,
    sampler=dict(type='DefaultSampler', shuffle=False),
    dataset=dict(
        type=dataset_type,
        ann_file=ann_file_val,
        data_prefix=dict(img=data_root_val),
        pipeline=val_pipeline,
        test_mode=True))
test_dataloader = dict(
    batch_size=1,
    num_workers=2,
    persistent_workers=True,
    sampler=dict(type='DefaultSampler', shuffle=False),
    dataset=dict(
        type=dataset_type,
        ann_file=ann_file_test,
        data_prefix=dict(img=data_root_val),
        pipeline=test_pipeline,
        test_mode=True))
