Delete config.py

config.py

@@ -1,127 +0,0 @@
-model = dict(
-    type='ImageClassifier',
-    backbone=dict(
-        type='ResNet',
-        depth=50,
-        num_stages=4,
-        out_indices=(3, ),
-        style='pytorch',
-        init_cfg=dict(
-            type='Pretrained',
-            checkpoint=
-            'https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_3rdparty-mill_in21k_20220331-faac000b.pth',
-            prefix='backbone')),
-    neck=dict(type='GlobalAveragePooling'),
-    head=dict(
-        type='LinearClsHead',
-        num_classes=2,
-        in_channels=2048,
-        loss=dict(type='CrossEntropyLoss', loss_weight=1.0),
-        topk=(1, )))
-dataset_type = 'CustomDataset'
-classes = ['No', 'Yes']
-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='RandomResizedCrop', size=224),
-    dict(type='RandomFlip', flip_prob=0.5, direction='horizontal'),
-    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='CenterCrop', crop_size=224),
-    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=16,
-    workers_per_gpu=4,
-    train=dict(
-        type='CustomDataset',
-        data_prefix='/work/home/acy25a367n/pornpics/pornpics-download-s',
-        ann_file=
-        '/work/home/acy25a367n/mmclassification/pornpics/outdoor/outdoor_train.csv',
-        pipeline=[
-            dict(type='LoadImageFromFile'),
-            dict(type='RandomResizedCrop', size=224),
-            dict(type='RandomFlip', flip_prob=0.5, direction='horizontal'),
-            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='CustomDataset',
-        data_prefix='/work/home/acy25a367n/pornpics/pornpics-download-s',
-        ann_file=
-        '/work/home/acy25a367n/mmclassification/pornpics/outdoor/outdoor_valid.csv',
-        pipeline=[
-            dict(type='LoadImageFromFile'),
-            dict(type='Resize', size=(256, -1)),
-            dict(type='CenterCrop', crop_size=224),
-            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='CustomDataset',
-        data_prefix='/work/home/acy25a367n/pornpics/pornpics-download-s',
-        ann_file=
-        '/work/home/acy25a367n/mmclassification/pornpics/outdoor/outdoor_valid.csv',
-        pipeline=[
-            dict(type='LoadImageFromFile'),
-            dict(type='Resize', size=(256, -1)),
-            dict(type='CenterCrop', crop_size=224),
-            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='accuracy', metric_options=dict(topk=(1, )))
-optimizer = dict(
-    type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0005, nesterov=True)
-optimizer_config = dict(grad_clip=None)
-lr_config = dict(
-    policy='CosineAnnealing',
-    min_lr=0,
-    warmup='linear',
-    warmup_iters=5,
-    warmup_ratio=0.01,
-    warmup_by_epoch=True)
-runner = dict(type='EpochBasedRunner', max_epochs=100)
-checkpoint_config = dict(interval=1)
-log_config = dict(interval=4, hooks=[dict(type='TextLoggerHook')])
-dist_params = dict(backend='nccl')
-log_level = 'INFO'
-load_from = None
-resume_from = None
-workflow = [('train', 1)]
-checkpoint = 'https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_3rdparty-mill_in21k_20220331-faac000b.pth'
-work_dir = 'work_dirs/resnet50_8xb32_outdoor'
-gpu_ids = [0]