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update config file
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configs/_base_/faster-rcnn_r50_fpn_1x_coco.py
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@@ -173,34 +173,34 @@ dataset_type = 'CocoDataset'
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data_root = 'data/'
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img_norm_cfg = dict(
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mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
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train_pipeline = [
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]
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test_pipeline = [
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]
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metainfo = {
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'classes': ('
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'palette': [
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(220, 20, 60),
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]
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data_root = 'data/'
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img_norm_cfg = dict(
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mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
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# train_pipeline = [
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# dict(type='LoadImageFromFile'),
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# dict(type='LoadAnnotations', with_bbox=True),
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# dict(type='Resize', img_scale=(1333, 800), keep_ratio=True),
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# dict(type='RandomFlip', flip_ratio=0.5),
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# dict(type='Normalize', **img_norm_cfg),
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# dict(type='Pad', size_divisor=32),
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# dict(type='DefaultFormatBundle'),
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# dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels']),
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# ]
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# test_pipeline = [
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# dict(type='LoadImageFromFile'),
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# dict(
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# type='MultiScaleFlipAug',
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# img_scale=(1333, 800),
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# flip=False,
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# transforms=[
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# dict(type='Resize', keep_ratio=True),
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# dict(type='RandomFlip'),
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# dict(type='Normalize', **img_norm_cfg),
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# dict(type='Pad', size_divisor=32),
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# dict(type='ImageToTensor', keys=['img']),
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# dict(type='Collect', keys=['img']),
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# ])
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# ]
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metainfo = {
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'classes': ('organoid', ),
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'palette': [
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(220, 20, 60),
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]
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