Uploaded all the public panel-segmentation files

automated_geotagging_config.py

@@ -0,0 +1,633 @@
+auto_scale_lr = dict(base_batch_size=16, enable=False)
+backend_args = None
+base_lr = 0.002
+custom_hooks = [
+    dict(
+        ema_type='ExpMomentumEMA',
+        momentum=0.0002,
+        priority=49,
+        type='EMAHook',
+        update_buffers=True),
+    dict(
+        switch_epoch=280,
+        switch_pipeline=[
+            dict(backend_args=None, type='LoadImageFromFile'),
+            dict(
+                poly2mask=False,
+                type='LoadAnnotations',
+                with_bbox=True,
+                with_mask=True),
+            dict(
+                keep_ratio=True,
+                ratio_range=(
+                    0.1,
+                    2.0,
+                ),
+                scale=(
+                    640,
+                    640,
+                ),
+                type='RandomResize'),
+            dict(
+                allow_negative_crop=True,
+                crop_size=(
+                    640,
+                    640,
+                ),
+                recompute_bbox=True,
+                type='RandomCrop'),
+            dict(min_gt_bbox_wh=(
+                1,
+                1,
+            ), type='FilterAnnotations'),
+            dict(type='YOLOXHSVRandomAug'),
+            dict(prob=0.5, type='RandomFlip'),
+            dict(
+                pad_val=dict(img=(
+                    114,
+                    114,
+                    114,
+                )),
+                size=(
+                    640,
+                    640,
+                ),
+                type='Pad'),
+            dict(type='PackDetInputs'),
+        ],
+        type='PipelineSwitchHook'),
+]
+data_root = '/kfs2/projects/pvfleets24/repos/cv-dl-framework'
+dataset_type = 'CocoDataset'
+default_hooks = dict(
+    checkpoint=dict(
+        rule='greater', save_best='coco/bbox_mAP_50', type='CheckpointHook'),
+    logger=dict(interval=50, type='LoggerHook'),
+    param_scheduler=dict(type='ParamSchedulerHook'),
+    sampler_seed=dict(type='DistSamplerSeedHook'),
+    timer=dict(type='IterTimerHook'),
+    visualization=dict(type='DetVisualizationHook'))
+default_scope = 'mmdet'
+env_cfg = dict(
+    cudnn_benchmark=False,
+    dist_cfg=dict(backend='nccl'),
+    mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0))
+img_scales = [
+    (
+        640,
+        640,
+    ),
+    (
+        320,
+        320,
+    ),
+    (
+        960,
+        960,
+    ),
+]
+interval = 10
+launcher = 'none'
+load_from = '/17_10_2025_14_11_24/best_coco_bbox_mAP_50_epoch_300.pth'
+log_level = 'INFO'
+log_processor = dict(by_epoch=True, type='LogProcessor', window_size=50)
+max_epochs = 300
+metainfo = dict(
+    classes=(
+        'tracker-row',
+        'inverter',
+        'dual-axis-tracker',
+        'fix-tilt-row',
+    ))
+model = dict(
+    backbone=dict(
+        act_cfg=dict(inplace=True, type='SiLU'),
+        arch='P5',
+        channel_attention=True,
+        deepen_factor=1.33,
+        expand_ratio=0.5,
+        norm_cfg=dict(type='SyncBN'),
+        type='CSPNeXt',
+        widen_factor=1.25),
+    bbox_head=dict(
+        act_cfg=dict(inplace=True, type='SiLU'),
+        anchor_generator=dict(
+            offset=0, strides=[
+                8,
+                16,
+                32,
+            ], type='MlvlPointGenerator'),
+        bbox_coder=dict(type='DistancePointBBoxCoder'),
+        feat_channels=320,
+        in_channels=320,
+        loss_bbox=dict(loss_weight=2.0, type='GIoULoss'),
+        loss_cls=dict(
+            beta=2.0,
+            loss_weight=1.0,
+            type='QualityFocalLoss',
+            use_sigmoid=True),
+        loss_mask=dict(
+            eps=5e-06, loss_weight=2.0, reduction='mean', type='DiceLoss'),
+        norm_cfg=dict(requires_grad=True, type='SyncBN'),
+        num_classes=4,
+        pred_kernel_size=1,
+        share_conv=True,
+        stacked_convs=2,
+        test_cfg=dict(
+            mask_thr_binary=0.5,
+            max_per_img=100,
+            min_bbox_size=0,
+            nms=dict(iou_threshold=0.6, type='nms'),
+            nms_pre=1000,
+            score_thr=0.05),
+        train_cfg=dict(
+            allowed_border=-1,
+            assigner=dict(topk=13, type='DynamicSoftLabelAssigner'),
+            debug=False,
+            pos_weight=-1),
+        type='RTMDetInsSepBNHead'),
+    data_preprocessor=dict(
+        batch_augments=None,
+        bgr_to_rgb=False,
+        mean=[
+            103.53,
+            116.28,
+            123.675,
+        ],
+        std=[
+            57.375,
+            57.12,
+            58.395,
+        ],
+        type='DetDataPreprocessor'),
+    neck=dict(
+        act_cfg=dict(inplace=True, type='SiLU'),
+        expand_ratio=0.5,
+        in_channels=[
+            320,
+            640,
+            1280,
+        ],
+        norm_cfg=dict(type='SyncBN'),
+        num_csp_blocks=4,
+        out_channels=320,
+        type='CSPNeXtPAFPN'),
+    test_cfg=dict(
+        mask_thr_binary=0.5,
+        max_per_img=100,
+        min_bbox_size=0,
+        nms=dict(iou_threshold=0.6, type='nms'),
+        nms_pre=1000,
+        score_thr=0.05),
+    train_cfg=dict(
+        allowed_border=-1,
+        assigner=dict(topk=13, type='DynamicSoftLabelAssigner'),
+        debug=False,
+        pos_weight=-1),
+    type='RTMDet')
+optim_wrapper = dict(
+    optimizer=dict(lr=0.001, type='AdamW', weight_decay=0.05),
+    paramwise_cfg=dict(
+        bias_decay_mult=0, bypass_duplicate=True, norm_decay_mult=0),
+    type='OptimWrapper')
+param_scheduler = [
+    dict(
+        begin=0, by_epoch=False, end=1000, start_factor=1e-05,
+        type='LinearLR'),
+    dict(
+        T_max=150,
+        begin=150,
+        by_epoch=True,
+        convert_to_iter_based=True,
+        end=300,
+        eta_min=0.0001,
+        type='CosineAnnealingLR'),
+]
+resume = False
+stage2_num_epochs = 20
+test_cfg = dict(type='TestLoop')
+test_dataloader = dict(
+    batch_size=5,
+    dataset=dict(
+        ann_file='/cv-dl-framework/test/label_json.json',
+        backend_args=None,
+        data_prefix=dict(
+            img='/kfs2/projects/pvfleets24/repos/cv-dl-framework/test/images/'
+        ),
+        data_root='/kfs2/projects/pvfleets24/repos/cv-dl-framework',
+        metainfo=dict(
+            classes=(
+                'tracker-row',
+                'inverter',
+                'dual-axis-tracker',
+                'fix-tilt-row',
+            )),
+        pipeline=[
+            dict(backend_args=None, type='LoadImageFromFile'),
+            dict(keep_ratio=True, scale=(
+                640,
+                640,
+            ), type='Resize'),
+            dict(
+                pad_val=dict(img=(
+                    114,
+                    114,
+                    114,
+                )),
+                size=(
+                    640,
+                    640,
+                ),
+                type='Pad'),
+            dict(type='LoadAnnotations', with_bbox=True),
+            dict(
+                meta_keys=(
+                    'img_id',
+                    'img_path',
+                    'ori_shape',
+                    'img_shape',
+                    'scale_factor',
+                ),
+                type='PackDetInputs'),
+        ],
+        test_mode=True,
+        type='CocoDataset'),
+    drop_last=False,
+    num_workers=10,
+    persistent_workers=True,
+    sampler=dict(shuffle=False, type='DefaultSampler'))
+test_evaluator = dict(
+    ann_file='/cv-dl-framework/test/label_json.json',
+    backend_args=None,
+    format_only=False,
+    metric=[
+        'bbox',
+        'segm',
+    ],
+    proposal_nums=(
+        100,
+        1,
+        10,
+    ),
+    type='CocoMetric')
+test_pipeline = [
+    dict(backend_args=None, type='LoadImageFromFile'),
+    dict(keep_ratio=True, scale=(
+        640,
+        640,
+    ), type='Resize'),
+    dict(pad_val=dict(img=(
+        114,
+        114,
+        114,
+    )), size=(
+        640,
+        640,
+    ), type='Pad'),
+    dict(type='LoadAnnotations', with_bbox=True),
+    dict(
+        meta_keys=(
+            'img_id',
+            'img_path',
+            'ori_shape',
+            'img_shape',
+            'scale_factor',
+        ),
+        type='PackDetInputs'),
+]
+train_cfg = dict(
+    dynamic_intervals=[
+        (
+            280,
+            1,
+        ),
+    ],
+    max_epochs=300,
+    type='EpochBasedTrainLoop',
+    val_interval=3)
+train_dataloader = dict(
+    batch_sampler=None,
+    batch_size=4,
+    dataset=dict(
+        ann_file='/cv-dl-framework/train/label_json.json',
+        backend_args=None,
+        data_prefix=dict(
+            img='/cv-dl-framework/train/images/'
+        ),
+        data_root='/cv-dl-framework',
+        filter_cfg=dict(filter_empty_gt=True, min_size=32),
+        metainfo=dict(
+            classes=(
+                'tracker-row',
+                'inverter',
+                'dual-axis-tracker',
+                'fix-tilt-row',
+            )),
+        pipeline=[
+            dict(backend_args=None, type='LoadImageFromFile'),
+            dict(
+                poly2mask=False,
+                type='LoadAnnotations',
+                with_bbox=True,
+                with_mask=True),
+            dict(img_scale=(
+                640,
+                640,
+            ), pad_val=114.0, type='CachedMosaic'),
+            dict(
+                keep_ratio=True,
+                ratio_range=(
+                    0.1,
+                    2.0,
+                ),
+                scale=(
+                    1280,
+                    1280,
+                ),
+                type='RandomResize'),
+            dict(
+                allow_negative_crop=True,
+                crop_size=(
+                    640,
+                    640,
+                ),
+                recompute_bbox=True,
+                type='RandomCrop'),
+            dict(type='YOLOXHSVRandomAug'),
+            dict(prob=0.5, type='RandomFlip'),
+            dict(
+                pad_val=dict(img=(
+                    114,
+                    114,
+                    114,
+                )),
+                size=(
+                    640,
+                    640,
+                ),
+                type='Pad'),
+            dict(
+                img_scale=(
+                    640,
+                    640,
+                ),
+                max_cached_images=20,
+                pad_val=(
+                    114,
+                    114,
+                    114,
+                ),
+                ratio_range=(
+                    1.0,
+                    1.0,
+                ),
+                type='CachedMixUp'),
+            dict(min_gt_bbox_wh=(
+                1,
+                1,
+            ), type='FilterAnnotations'),
+            dict(type='PackDetInputs'),
+        ],
+        type='CocoDataset'),
+    num_workers=10,
+    persistent_workers=True,
+    pin_memory=True,
+    sampler=dict(shuffle=True, type='DefaultSampler'))
+train_pipeline = [
+    dict(backend_args=None, type='LoadImageFromFile'),
+    dict(
+        poly2mask=False,
+        type='LoadAnnotations',
+        with_bbox=True,
+        with_mask=True),
+    dict(img_scale=(
+        640,
+        640,
+    ), pad_val=114.0, type='CachedMosaic'),
+    dict(
+        keep_ratio=True,
+        ratio_range=(
+            0.1,
+            2.0,
+        ),
+        scale=(
+            1280,
+            1280,
+        ),
+        type='RandomResize'),
+    dict(
+        allow_negative_crop=True,
+        crop_size=(
+            640,
+            640,
+        ),
+        recompute_bbox=True,
+        type='RandomCrop'),
+    dict(type='YOLOXHSVRandomAug'),
+    dict(prob=0.5, type='RandomFlip'),
+    dict(pad_val=dict(img=(
+        114,
+        114,
+        114,
+    )), size=(
+        640,
+        640,
+    ), type='Pad'),
+    dict(
+        img_scale=(
+            640,
+            640,
+        ),
+        max_cached_images=20,
+        pad_val=(
+            114,
+            114,
+            114,
+        ),
+        ratio_range=(
+            1.0,
+            1.0,
+        ),
+        type='CachedMixUp'),
+    dict(min_gt_bbox_wh=(
+        1,
+        1,
+    ), type='FilterAnnotations'),
+    dict(type='PackDetInputs'),
+]
+train_pipeline_stage2 = [
+    dict(backend_args=None, type='LoadImageFromFile'),
+    dict(
+        poly2mask=False,
+        type='LoadAnnotations',
+        with_bbox=True,
+        with_mask=True),
+    dict(
+        keep_ratio=True,
+        ratio_range=(
+            0.1,
+            2.0,
+        ),
+        scale=(
+            640,
+            640,
+        ),
+        type='RandomResize'),
+    dict(
+        allow_negative_crop=True,
+        crop_size=(
+            640,
+            640,
+        ),
+        recompute_bbox=True,
+        type='RandomCrop'),
+    dict(min_gt_bbox_wh=(
+        1,
+        1,
+    ), type='FilterAnnotations'),
+    dict(type='YOLOXHSVRandomAug'),
+    dict(prob=0.5, type='RandomFlip'),
+    dict(pad_val=dict(img=(
+        114,
+        114,
+        114,
+    )), size=(
+        640,
+        640,
+    ), type='Pad'),
+    dict(type='PackDetInputs'),
+]
+tta_model = dict(
+    tta_cfg=dict(max_per_img=100, nms=dict(iou_threshold=0.6, type='nms')),
+    type='DetTTAModel')
+tta_pipeline = [
+    dict(backend_args=None, type='LoadImageFromFile'),
+    dict(
+        transforms=[
+            [
+                dict(keep_ratio=True, scale=(
+                    640,
+                    640,
+                ), type='Resize'),
+                dict(keep_ratio=True, scale=(
+                    320,
+                    320,
+                ), type='Resize'),
+                dict(keep_ratio=True, scale=(
+                    960,
+                    960,
+                ), type='Resize'),
+            ],
+            [
+                dict(prob=1.0, type='RandomFlip'),
+                dict(prob=0.0, type='RandomFlip'),
+            ],
+            [
+                dict(
+                    pad_val=dict(img=(
+                        114,
+                        114,
+                        114,
+                    )),
+                    size=(
+                        960,
+                        960,
+                    ),
+                    type='Pad'),
+            ],
+            [
+                dict(type='LoadAnnotations', with_bbox=True),
+            ],
+            [
+                dict(
+                    meta_keys=(
+                        'img_id',
+                        'img_path',
+                        'ori_shape',
+                        'img_shape',
+                        'scale_factor',
+                        'flip',
+                        'flip_direction',
+                    ),
+                    type='PackDetInputs'),
+            ],
+        ],
+        type='TestTimeAug'),
+]
+val_cfg = dict(type='ValLoop')
+val_dataloader = dict(
+    batch_size=5,
+    dataset=dict(
+        ann_file='/cv-dl-framework/test/label_json.json',
+        backend_args=None,
+        data_prefix=dict(
+            img='/cv-dl-framework/test/images/'
+        ),
+        data_root='/cv-dl-framework',
+        metainfo=dict(
+            classes=(
+                'tracker-row',
+                'inverter',
+                'dual-axis-tracker',
+                'fix-tilt-row',
+            )),
+        pipeline=[
+            dict(backend_args=None, type='LoadImageFromFile'),
+            dict(keep_ratio=True, scale=(
+                640,
+                640,
+            ), type='Resize'),
+            dict(
+                pad_val=dict(img=(
+                    114,
+                    114,
+                    114,
+                )),
+                size=(
+                    640,
+                    640,
+                ),
+                type='Pad'),
+            dict(type='LoadAnnotations', with_bbox=True),
+            dict(
+                meta_keys=(
+                    'img_id',
+                    'img_path',
+                    'ori_shape',
+                    'img_shape',
+                    'scale_factor',
+                ),
+                type='PackDetInputs'),
+        ],
+        test_mode=True,
+        type='CocoDataset'),
+    drop_last=False,
+    num_workers=10,
+    persistent_workers=True,
+    sampler=dict(shuffle=False, type='DefaultSampler'))
+val_evaluator = dict(
+    ann_file='/cv-dl-framework/test/label_json.json',
+    backend_args=None,
+    format_only=False,
+    metric=[
+        'bbox',
+        'segm',
+    ],
+    proposal_nums=(
+        100,
+        1,
+        10,
+    ),
+    type='CocoMetric')
+vis_backends = [
+    dict(type='LocalVisBackend'),
+]
+visualizer = dict(
+    name='visualizer',
+    type='DetLocalVisualizer',
+    vis_backends=[
+        dict(
+            save_dir='/17_10_2025_14_11_24',
+            type='LocalVisBackend'),
+    ])
+work_dir = '/17_10_2025_14_11_24'

automated_geotagging_model.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3cc8086021d8884d06d68208c0cb28cf15f02af2399ee284155cb2ef524249ec
+size 873105261

hail_config.py

@@ -0,0 +1,632 @@
+auto_scale_lr = dict(base_batch_size=16, enable=False)
+backend_args = None
+base_lr = 0.002
+custom_hooks = [
+    dict(
+        ema_type='ExpMomentumEMA',
+        momentum=0.0002,
+        priority=49,
+        type='EMAHook',
+        update_buffers=True),
+    dict(
+        switch_epoch=280,
+        switch_pipeline=[
+            dict(backend_args=None, type='LoadImageFromFile'),
+            dict(
+                poly2mask=False,
+                type='LoadAnnotations',
+                with_bbox=True,
+                with_mask=True),
+            dict(
+                keep_ratio=True,
+                ratio_range=(
+                    0.1,
+                    2.0,
+                ),
+                scale=(
+                    640,
+                    640,
+                ),
+                type='RandomResize'),
+            dict(
+                allow_negative_crop=True,
+                crop_size=(
+                    640,
+                    640,
+                ),
+                recompute_bbox=True,
+                type='RandomCrop'),
+            dict(min_gt_bbox_wh=(
+                1,
+                1,
+            ), type='FilterAnnotations'),
+            dict(type='YOLOXHSVRandomAug'),
+            dict(prob=0.5, type='RandomFlip'),
+            dict(
+                pad_val=dict(img=(
+                    114,
+                    114,
+                    114,
+                )),
+                size=(
+                    640,
+                    640,
+                ),
+                type='Pad'),
+            dict(type='PackDetInputs'),
+        ],
+        type='PipelineSwitchHook'),
+]
+data_root = '/kfs2/projects/pvfleets24/repos/cv-dl-framework-kirsten'
+dataset_type = 'CocoDataset'
+default_hooks = dict(
+    checkpoint=dict(
+        rule='greater', save_best='coco/bbox_mAP_50', type='CheckpointHook'),
+    logger=dict(interval=50, type='LoggerHook'),
+    param_scheduler=dict(type='ParamSchedulerHook'),
+    sampler_seed=dict(type='DistSamplerSeedHook'),
+    timer=dict(type='IterTimerHook'),
+    visualization=dict(type='DetVisualizationHook'))
+default_scope = 'mmdet'
+env_cfg = dict(
+    cudnn_benchmark=False,
+    dist_cfg=dict(backend='nccl'),
+    mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0))
+img_scales = [
+    (
+        640,
+        640,
+    ),
+    (
+        320,
+        320,
+    ),
+    (
+        960,
+        960,
+    ),
+]
+interval = 10
+launcher = 'none'
+load_from = ('/kfs2/projects/pvfleets24/repos/cv-dl-framework-kirsten/runs/' +
+             '16_05_2025_15_06_47/best_coco_bbox_mAP_50_epoch_298.pth')
+log_level = 'INFO'
+log_processor = dict(by_epoch=True, type='LogProcessor', window_size=50)
+max_epochs = 300
+metainfo = dict(classes=(
+    'damage',
+    'panel',
+))
+model = dict(
+    backbone=dict(
+        act_cfg=dict(inplace=True, type='SiLU'),
+        arch='P5',
+        channel_attention=True,
+        deepen_factor=1.33,
+        expand_ratio=0.5,
+        norm_cfg=dict(type='SyncBN'),
+        type='CSPNeXt',
+        widen_factor=1.25),
+    bbox_head=dict(
+        act_cfg=dict(inplace=True, type='SiLU'),
+        anchor_generator=dict(
+            offset=0, strides=[
+                8,
+                16,
+                32,
+            ], type='MlvlPointGenerator'),
+        bbox_coder=dict(type='DistancePointBBoxCoder'),
+        feat_channels=320,
+        in_channels=320,
+        loss_bbox=dict(loss_weight=2.0, type='GIoULoss'),
+        loss_cls=dict(
+            beta=2.0,
+            loss_weight=1.0,
+            type='QualityFocalLoss',
+            use_sigmoid=True),
+        loss_mask=dict(
+            eps=5e-06, loss_weight=2.0, reduction='mean', type='DiceLoss'),
+        norm_cfg=dict(requires_grad=True, type='SyncBN'),
+        num_classes=2,
+        pred_kernel_size=1,
+        share_conv=True,
+        stacked_convs=2,
+        test_cfg=dict(
+            mask_thr_binary=0.5,
+            max_per_img=100,
+            min_bbox_size=0,
+            nms=dict(iou_threshold=0.6, type='nms'),
+            nms_pre=1000,
+            score_thr=0.05),
+        train_cfg=dict(
+            allowed_border=-1,
+            assigner=dict(topk=13, type='DynamicSoftLabelAssigner'),
+            debug=False,
+            pos_weight=-1),
+        type='RTMDetInsSepBNHead'),
+    data_preprocessor=dict(
+        batch_augments=None,
+        bgr_to_rgb=False,
+        mean=[
+            103.53,
+            116.28,
+            123.675,
+        ],
+        std=[
+            57.375,
+            57.12,
+            58.395,
+        ],
+        type='DetDataPreprocessor'),
+    neck=dict(
+        act_cfg=dict(inplace=True, type='SiLU'),
+        expand_ratio=0.5,
+        in_channels=[
+            320,
+            640,
+            1280,
+        ],
+        norm_cfg=dict(type='SyncBN'),
+        num_csp_blocks=4,
+        out_channels=320,
+        type='CSPNeXtPAFPN'),
+    test_cfg=dict(
+        mask_thr_binary=0.5,
+        max_per_img=100,
+        min_bbox_size=0,
+        nms=dict(iou_threshold=0.6, type='nms'),
+        nms_pre=1000,
+        score_thr=0.05),
+    train_cfg=dict(
+        allowed_border=-1,
+        assigner=dict(topk=13, type='DynamicSoftLabelAssigner'),
+        debug=False,
+        pos_weight=-1),
+    type='RTMDet')
+optim_wrapper = dict(
+    optimizer=dict(lr=0.002, type='AdamW', weight_decay=0.05),
+    paramwise_cfg=dict(
+        bias_decay_mult=0, bypass_duplicate=True, norm_decay_mult=0),
+    type='OptimWrapper')
+param_scheduler = [
+    dict(
+        begin=0, by_epoch=False, end=1000, start_factor=1e-05,
+        type='LinearLR'),
+    dict(
+        T_max=150,
+        begin=150,
+        by_epoch=True,
+        convert_to_iter_based=True,
+        end=300,
+        eta_min=0.0001,
+        type='CosineAnnealingLR'),
+]
+resume = False
+stage2_num_epochs = 20
+test_cfg = dict(type='TestLoop')
+test_dataloader = dict(
+    batch_size=5,
+    dataset=dict(
+        ann_file=('/kfs2/projects/pvfleets24/repos/cv-dl-framework-kirsten/' +
+                  'test/label_json.json'),
+        backend_args=None,
+        data_prefix=dict(
+            img=('/kfs2/projects/pvfleets24/repos/' +
+                 'cv-dl-framework-kirsten/test/images/')
+        ),
+        data_root='/kfs2/projects/pvfleets24/repos/cv-dl-framework-kirsten',
+        metainfo=dict(classes=(
+            'damage',
+            'panel',
+        )),
+        pipeline=[
+            dict(backend_args=None, type='LoadImageFromFile'),
+            dict(keep_ratio=True, scale=(
+                640,
+                640,
+            ), type='Resize'),
+            dict(
+                pad_val=dict(img=(
+                    114,
+                    114,
+                    114,
+                )),
+                size=(
+                    640,
+                    640,
+                ),
+                type='Pad'),
+            dict(type='LoadAnnotations', with_bbox=True),
+            dict(
+                meta_keys=(
+                    'img_id',
+                    'img_path',
+                    'ori_shape',
+                    'img_shape',
+                    'scale_factor',
+                ),
+                type='PackDetInputs'),
+        ],
+        test_mode=True,
+        type='CocoDataset'),
+    drop_last=False,
+    num_workers=10,
+    persistent_workers=True,
+    sampler=dict(shuffle=False, type='DefaultSampler'))
+test_evaluator = dict(
+    ann_file=('/kfs2/projects/pvfleets24/repos/cv-dl-framework-kirsten/' +
+              'test/label_json.json'),
+    backend_args=None,
+    format_only=False,
+    metric=[
+        'bbox',
+        'segm',
+    ],
+    proposal_nums=(
+        100,
+        1,
+        10,
+    ),
+    type='CocoMetric')
+test_pipeline = [
+    dict(backend_args=None, type='LoadImageFromFile'),
+    dict(keep_ratio=True, scale=(
+        640,
+        640,
+    ), type='Resize'),
+    dict(pad_val=dict(img=(
+        114,
+        114,
+        114,
+    )), size=(
+        640,
+        640,
+    ), type='Pad'),
+    dict(type='LoadAnnotations', with_bbox=True),
+    dict(
+        meta_keys=(
+            'img_id',
+            'img_path',
+            'ori_shape',
+            'img_shape',
+            'scale_factor',
+        ),
+        type='PackDetInputs'),
+]
+train_cfg = dict(
+    dynamic_intervals=[
+        (
+            280,
+            1,
+        ),
+    ],
+    max_epochs=300,
+    type='EpochBasedTrainLoop',
+    val_interval=3)
+train_dataloader = dict(
+    batch_sampler=None,
+    batch_size=4,
+    dataset=dict(
+        ann_file=('/kfs2/projects/pvfleets24/repos/cv-dl-framework-kirsten/' +
+                  'train/label_json.json'),
+        backend_args=None,
+        data_prefix=dict(
+            img=('/kfs2/projects/pvfleets24/repos/cv-dl-framework-kirsten/' +
+                 'train/images/')
+        ),
+        data_root='/kfs2/projects/pvfleets24/repos/cv-dl-framework-kirsten',
+        filter_cfg=dict(filter_empty_gt=True, min_size=32),
+        metainfo=dict(classes=(
+            'damage',
+            'panel',
+        )),
+        pipeline=[
+            dict(backend_args=None, type='LoadImageFromFile'),
+            dict(
+                poly2mask=False,
+                type='LoadAnnotations',
+                with_bbox=True,
+                with_mask=True),
+            dict(img_scale=(
+                640,
+                640,
+            ), pad_val=114.0, type='CachedMosaic'),
+            dict(
+                keep_ratio=True,
+                ratio_range=(
+                    0.1,
+                    2.0,
+                ),
+                scale=(
+                    1280,
+                    1280,
+                ),
+                type='RandomResize'),
+            dict(
+                allow_negative_crop=True,
+                crop_size=(
+                    640,
+                    640,
+                ),
+                recompute_bbox=True,
+                type='RandomCrop'),
+            dict(type='YOLOXHSVRandomAug'),
+            dict(prob=0.5, type='RandomFlip'),
+            dict(
+                pad_val=dict(img=(
+                    114,
+                    114,
+                    114,
+                )),
+                size=(
+                    640,
+                    640,
+                ),
+                type='Pad'),
+            dict(
+                img_scale=(
+                    640,
+                    640,
+                ),
+                max_cached_images=20,
+                pad_val=(
+                    114,
+                    114,
+                    114,
+                ),
+                ratio_range=(
+                    1.0,
+                    1.0,
+                ),
+                type='CachedMixUp'),
+            dict(min_gt_bbox_wh=(
+                1,
+                1,
+            ), type='FilterAnnotations'),
+            dict(type='PackDetInputs'),
+        ],
+        type='CocoDataset'),
+    num_workers=10,
+    persistent_workers=True,
+    pin_memory=True,
+    sampler=dict(shuffle=True, type='DefaultSampler'))
+train_pipeline = [
+    dict(backend_args=None, type='LoadImageFromFile'),
+    dict(
+        poly2mask=False,
+        type='LoadAnnotations',
+        with_bbox=True,
+        with_mask=True),
+    dict(img_scale=(
+        640,
+        640,
+    ), pad_val=114.0, type='CachedMosaic'),
+    dict(
+        keep_ratio=True,
+        ratio_range=(
+            0.1,
+            2.0,
+        ),
+        scale=(
+            1280,
+            1280,
+        ),
+        type='RandomResize'),
+    dict(
+        allow_negative_crop=True,
+        crop_size=(
+            640,
+            640,
+        ),
+        recompute_bbox=True,
+        type='RandomCrop'),
+    dict(type='YOLOXHSVRandomAug'),
+    dict(prob=0.5, type='RandomFlip'),
+    dict(pad_val=dict(img=(
+        114,
+        114,
+        114,
+    )), size=(
+        640,
+        640,
+    ), type='Pad'),
+    dict(
+        img_scale=(
+            640,
+            640,
+        ),
+        max_cached_images=20,
+        pad_val=(
+            114,
+            114,
+            114,
+        ),
+        ratio_range=(
+            1.0,
+            1.0,
+        ),
+        type='CachedMixUp'),
+    dict(min_gt_bbox_wh=(
+        1,
+        1,
+    ), type='FilterAnnotations'),
+    dict(type='PackDetInputs'),
+]
+train_pipeline_stage2 = [
+    dict(backend_args=None, type='LoadImageFromFile'),
+    dict(
+        poly2mask=False,
+        type='LoadAnnotations',
+        with_bbox=True,
+        with_mask=True),
+    dict(
+        keep_ratio=True,
+        ratio_range=(
+            0.1,
+            2.0,
+        ),
+        scale=(
+            640,
+            640,
+        ),
+        type='RandomResize'),
+    dict(
+        allow_negative_crop=True,
+        crop_size=(
+            640,
+            640,
+        ),
+        recompute_bbox=True,
+        type='RandomCrop'),
+    dict(min_gt_bbox_wh=(
+        1,
+        1,
+    ), type='FilterAnnotations'),
+    dict(type='YOLOXHSVRandomAug'),
+    dict(prob=0.5, type='RandomFlip'),
+    dict(pad_val=dict(img=(
+        114,
+        114,
+        114,
+    )), size=(
+        640,
+        640,
+    ), type='Pad'),
+    dict(type='PackDetInputs'),
+]
+tta_model = dict(
+    tta_cfg=dict(max_per_img=100, nms=dict(iou_threshold=0.6, type='nms')),
+    type='DetTTAModel')
+tta_pipeline = [
+    dict(backend_args=None, type='LoadImageFromFile'),
+    dict(
+        transforms=[
+            [
+                dict(keep_ratio=True, scale=(
+                    640,
+                    640,
+                ), type='Resize'),
+                dict(keep_ratio=True, scale=(
+                    320,
+                    320,
+                ), type='Resize'),
+                dict(keep_ratio=True, scale=(
+                    960,
+                    960,
+                ), type='Resize'),
+            ],
+            [
+                dict(prob=1.0, type='RandomFlip'),
+                dict(prob=0.0, type='RandomFlip'),
+            ],
+            [
+                dict(
+                    pad_val=dict(img=(
+                        114,
+                        114,
+                        114,
+                    )),
+                    size=(
+                        960,
+                        960,
+                    ),
+                    type='Pad'),
+            ],
+            [
+                dict(type='LoadAnnotations', with_bbox=True),
+            ],
+            [
+                dict(
+                    meta_keys=(
+                        'img_id',
+                        'img_path',
+                        'ori_shape',
+                        'img_shape',
+                        'scale_factor',
+                        'flip',
+                        'flip_direction',
+                    ),
+                    type='PackDetInputs'),
+            ],
+        ],
+        type='TestTimeAug'),
+]
+val_cfg = dict(type='ValLoop')
+val_dataloader = dict(
+    batch_size=5,
+    dataset=dict(
+        ann_file=('/kfs2/projects/pvfleets24/repos/cv-dl-framework-kirsten/' +
+                  'test/label_json.json'),
+        backend_args=None,
+        data_prefix=dict(
+            img='/kfs2/projects/pvfleets24/repos/' +
+            'cv-dl-framework-kirsten/test/images/'
+        ),
+        data_root='/kfs2/projects/pvfleets24/repos/cv-dl-framework-kirsten',
+        metainfo=dict(classes=(
+            'damage',
+            'panel',
+        )),
+        pipeline=[
+            dict(backend_args=None, type='LoadImageFromFile'),
+            dict(keep_ratio=True, scale=(
+                640,
+                640,
+            ), type='Resize'),
+            dict(
+                pad_val=dict(img=(
+                    114,
+                    114,
+                    114,
+                )),
+                size=(
+                    640,
+                    640,
+                ),
+                type='Pad'),
+            dict(type='LoadAnnotations', with_bbox=True),
+            dict(
+                meta_keys=(
+                    'img_id',
+                    'img_path',
+                    'ori_shape',
+                    'img_shape',
+                    'scale_factor',
+                ),
+                type='PackDetInputs'),
+        ],
+        test_mode=True,
+        type='CocoDataset'),
+    drop_last=False,
+    num_workers=10,
+    persistent_workers=True,
+    sampler=dict(shuffle=False, type='DefaultSampler'))
+val_evaluator = dict(
+    ann_file=('/kfs2/projects/pvfleets24/repos/cv-dl-framework-kirsten/' +
+              'test/label_json.json'),
+    backend_args=None,
+    format_only=False,
+    metric=[
+        'bbox',
+        'segm',
+    ],
+    proposal_nums=(
+        100,
+        1,
+        10,
+    ),
+    type='CocoMetric')
+vis_backends = [
+    dict(type='LocalVisBackend'),
+]
+visualizer = dict(
+    name='visualizer',
+    type='DetLocalVisualizer',
+    vis_backends=[
+        dict(
+            save_dir=('/kfs2/projects/pvfleets24/repos/' +
+                      'cv-dl-framework-kirsten/runs/16_05_2025_15_06_47'),
+            type='LocalVisBackend'),
+    ])
+work_dir = ('/kfs2/projects/pvfleets24/repos/cv-dl-framework-kirsten/' +
+            'runs/16_05_2025_15_06_47')

hail_model.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ef8533aef7e34292a357c149baa1c7b2ba0cfcfaff8a3114cf80eba79c9f5e35
+size 873715053

panel_detection_config.py

@@ -0,0 +1,637 @@
+auto_scale_lr = dict(base_batch_size=16, enable=False)
+backend_args = None
+base_lr = 0.002
+custom_hooks = [
+    dict(
+        ema_type='ExpMomentumEMA',
+        momentum=0.0002,
+        priority=49,
+        type='EMAHook',
+        update_buffers=True),
+    dict(
+        switch_epoch=280,
+        switch_pipeline=[
+            dict(backend_args=None, type='LoadImageFromFile'),
+            dict(
+                poly2mask=False,
+                type='LoadAnnotations',
+                with_bbox=True,
+                with_mask=True),
+            dict(
+                keep_ratio=True,
+                ratio_range=(
+                    0.1,
+                    2.0,
+                ),
+                scale=(
+                    640,
+                    640,
+                ),
+                type='RandomResize'),
+            dict(
+                allow_negative_crop=True,
+                crop_size=(
+                    640,
+                    640,
+                ),
+                recompute_bbox=True,
+                type='RandomCrop'),
+            dict(min_gt_bbox_wh=(
+                1,
+                1,
+            ), type='FilterAnnotations'),
+            dict(type='YOLOXHSVRandomAug'),
+            dict(prob=0.5, type='RandomFlip'),
+            dict(
+                pad_val=dict(img=(
+                    114,
+                    114,
+                    114,
+                )),
+                size=(
+                    640,
+                    640,
+                ),
+                type='Pad'),
+            dict(type='PackDetInputs'),
+        ],
+        type='PipelineSwitchHook'),
+]
+data_root = '/kfs2/projects/pvfleets24/repos/cv-dl-framework'
+dataset_type = 'CocoDataset'
+default_hooks = dict(
+    checkpoint=dict(
+        rule='greater', save_best='coco/bbox_mAP_50', type='CheckpointHook'),
+    logger=dict(interval=50, type='LoggerHook'),
+    param_scheduler=dict(type='ParamSchedulerHook'),
+    sampler_seed=dict(type='DistSamplerSeedHook'),
+    timer=dict(type='IterTimerHook'),
+    visualization=dict(type='DetVisualizationHook'))
+default_scope = 'mmdet'
+env_cfg = dict(
+    cudnn_benchmark=False,
+    dist_cfg=dict(backend='nccl'),
+    mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0))
+img_scales = [
+    (
+        640,
+        640,
+    ),
+    (
+        320,
+        320,
+    ),
+    (
+        960,
+        960,
+    ),
+]
+interval = 10
+launcher = 'none'
+load_from = 'best_coco_bbox_mAP_50_epoch_291.pth'
+log_level = 'INFO'
+log_processor = dict(by_epoch=True, type='LogProcessor', window_size=50)
+max_epochs = 300
+metainfo = dict(
+    classes=(
+        'carport-fixed-tilt',
+        'ground-dual-axis-tracker',
+        'ground-fixed-tilt',
+        'ground-single-axis-tracker',
+        'rooftop-fixed-tilt',
+    ))
+model = dict(
+    backbone=dict(
+        act_cfg=dict(inplace=True, type='SiLU'),
+        arch='P5',
+        channel_attention=True,
+        deepen_factor=1.33,
+        expand_ratio=0.5,
+        norm_cfg=dict(type='SyncBN'),
+        type='CSPNeXt',
+        widen_factor=1.25),
+    bbox_head=dict(
+        act_cfg=dict(inplace=True, type='SiLU'),
+        anchor_generator=dict(
+            offset=0, strides=[
+                8,
+                16,
+                32,
+            ], type='MlvlPointGenerator'),
+        bbox_coder=dict(type='DistancePointBBoxCoder'),
+        feat_channels=320,
+        in_channels=320,
+        loss_bbox=dict(loss_weight=2.0, type='GIoULoss'),
+        loss_cls=dict(
+            beta=2.0,
+            loss_weight=1.0,
+            type='QualityFocalLoss',
+            use_sigmoid=True),
+        loss_mask=dict(
+            eps=5e-06, loss_weight=2.0, reduction='mean', type='DiceLoss'),
+        norm_cfg=dict(requires_grad=True, type='SyncBN'),
+        num_classes=5,
+        pred_kernel_size=1,
+        share_conv=True,
+        stacked_convs=2,
+        test_cfg=dict(
+            mask_thr_binary=0.5,
+            max_per_img=100,
+            min_bbox_size=0,
+            nms=dict(iou_threshold=0.6, type='nms'),
+            nms_pre=1000,
+            score_thr=0.05),
+        train_cfg=dict(
+            allowed_border=-1,
+            assigner=dict(topk=13, type='DynamicSoftLabelAssigner'),
+            debug=False,
+            pos_weight=-1),
+        type='RTMDetInsSepBNHead'),
+    data_preprocessor=dict(
+        batch_augments=None,
+        bgr_to_rgb=False,
+        mean=[
+            103.53,
+            116.28,
+            123.675,
+        ],
+        std=[
+            57.375,
+            57.12,
+            58.395,
+        ],
+        type='DetDataPreprocessor'),
+    neck=dict(
+        act_cfg=dict(inplace=True, type='SiLU'),
+        expand_ratio=0.5,
+        in_channels=[
+            320,
+            640,
+            1280,
+        ],
+        norm_cfg=dict(type='SyncBN'),
+        num_csp_blocks=4,
+        out_channels=320,
+        type='CSPNeXtPAFPN'),
+    test_cfg=dict(
+        mask_thr_binary=0.5,
+        max_per_img=100,
+        min_bbox_size=0,
+        nms=dict(iou_threshold=0.6, type='nms'),
+        nms_pre=1000,
+        score_thr=0.05),
+    train_cfg=dict(
+        allowed_border=-1,
+        assigner=dict(topk=13, type='DynamicSoftLabelAssigner'),
+        debug=False,
+        pos_weight=-1),
+    type='RTMDet')
+optim_wrapper = dict(
+    optimizer=dict(lr=0.001, type='AdamW', weight_decay=0.05),
+    paramwise_cfg=dict(
+        bias_decay_mult=0, bypass_duplicate=True, norm_decay_mult=0),
+    type='OptimWrapper')
+param_scheduler = [
+    dict(
+        begin=0, by_epoch=False, end=1000, start_factor=1e-05,
+        type='LinearLR'),
+    dict(
+        T_max=150,
+        begin=150,
+        by_epoch=True,
+        convert_to_iter_based=True,
+        end=300,
+        eta_min=0.0001,
+        type='CosineAnnealingLR'),
+]
+resume = False
+stage2_num_epochs = 20
+test_cfg = dict(type='TestLoop')
+test_dataloader = dict(
+    batch_size=5,
+    dataset=dict(
+        ann_file='/cv-dl-framework/test/label_json.json',
+        backend_args=None,
+        data_prefix=dict(
+            img='/kfs2/projects/pvfleets24/repos/cv-dl-framework/test/images/'
+        ),
+        data_root='/kfs2/projects/pvfleets24/repos/cv-dl-framework',
+        metainfo=dict(
+            classes=(
+                'carport-fixed-tilt',
+                'ground-dual-axis-tracker',
+                'ground-fixed-tilt',
+                'ground-single-axis-tracker',
+                'rooftop-fixed-tilt',
+            )),
+        pipeline=[
+            dict(backend_args=None, type='LoadImageFromFile'),
+            dict(keep_ratio=True, scale=(
+                640,
+                640,
+            ), type='Resize'),
+            dict(
+                pad_val=dict(img=(
+                    114,
+                    114,
+                    114,
+                )),
+                size=(
+                    640,
+                    640,
+                ),
+                type='Pad'),
+            dict(type='LoadAnnotations', with_bbox=True),
+            dict(
+                meta_keys=(
+                    'img_id',
+                    'img_path',
+                    'ori_shape',
+                    'img_shape',
+                    'scale_factor',
+                ),
+                type='PackDetInputs'),
+        ],
+        test_mode=True,
+        type='CocoDataset'),
+    drop_last=False,
+    num_workers=10,
+    persistent_workers=True,
+    sampler=dict(shuffle=False, type='DefaultSampler'))
+test_evaluator = dict(
+    ann_file='/cv-dl-framework/test/label_json.json',
+    backend_args=None,
+    format_only=False,
+    metric=[
+        'bbox',
+        'segm',
+    ],
+    proposal_nums=(
+        100,
+        1,
+        10,
+    ),
+    type='CocoMetric')
+test_pipeline = [
+    dict(backend_args=None, type='LoadImageFromFile'),
+    dict(keep_ratio=True, scale=(
+        640,
+        640,
+    ), type='Resize'),
+    dict(pad_val=dict(img=(
+        114,
+        114,
+        114,
+    )), size=(
+        640,
+        640,
+    ), type='Pad'),
+    dict(type='LoadAnnotations', with_bbox=True),
+    dict(
+        meta_keys=(
+            'img_id',
+            'img_path',
+            'ori_shape',
+            'img_shape',
+            'scale_factor',
+        ),
+        type='PackDetInputs'),
+]
+train_cfg = dict(
+    dynamic_intervals=[
+        (
+            280,
+            1,
+        ),
+    ],
+    max_epochs=300,
+    type='EpochBasedTrainLoop',
+    val_interval=3)
+train_dataloader = dict(
+    batch_sampler=None,
+    batch_size=4,
+    dataset=dict(
+        ann_file='/cv-dl-framework/train/label_json.json',
+        backend_args=None,
+        data_prefix=dict(
+            img='/kfs2/projects/pvfleets24/repos/cv-dl-framework/train/images/'
+        ),
+        data_root='/kfs2/projects/pvfleets24/repos/cv-dl-framework',
+        filter_cfg=dict(filter_empty_gt=True, min_size=32),
+        metainfo=dict(
+            classes=(
+                'carport-fixed-tilt',
+                'ground-dual-axis-tracker',
+                'ground-fixed-tilt',
+                'ground-single-axis-tracker',
+                'rooftop-fixed-tilt',
+            )),
+        pipeline=[
+            dict(backend_args=None, type='LoadImageFromFile'),
+            dict(
+                poly2mask=False,
+                type='LoadAnnotations',
+                with_bbox=True,
+                with_mask=True),
+            dict(img_scale=(
+                640,
+                640,
+            ), pad_val=114.0, type='CachedMosaic'),
+            dict(
+                keep_ratio=True,
+                ratio_range=(
+                    0.1,
+                    2.0,
+                ),
+                scale=(
+                    1280,
+                    1280,
+                ),
+                type='RandomResize'),
+            dict(
+                allow_negative_crop=True,
+                crop_size=(
+                    640,
+                    640,
+                ),
+                recompute_bbox=True,
+                type='RandomCrop'),
+            dict(type='YOLOXHSVRandomAug'),
+            dict(prob=0.5, type='RandomFlip'),
+            dict(
+                pad_val=dict(img=(
+                    114,
+                    114,
+                    114,
+                )),
+                size=(
+                    640,
+                    640,
+                ),
+                type='Pad'),
+            dict(
+                img_scale=(
+                    640,
+                    640,
+                ),
+                max_cached_images=20,
+                pad_val=(
+                    114,
+                    114,
+                    114,
+                ),
+                ratio_range=(
+                    1.0,
+                    1.0,
+                ),
+                type='CachedMixUp'),
+            dict(min_gt_bbox_wh=(
+                1,
+                1,
+            ), type='FilterAnnotations'),
+            dict(type='PackDetInputs'),
+        ],
+        type='CocoDataset'),
+    num_workers=10,
+    persistent_workers=True,
+    pin_memory=True,
+    sampler=dict(shuffle=True, type='DefaultSampler'))
+train_pipeline = [
+    dict(backend_args=None, type='LoadImageFromFile'),
+    dict(
+        poly2mask=False,
+        type='LoadAnnotations',
+        with_bbox=True,
+        with_mask=True),
+    dict(img_scale=(
+        640,
+        640,
+    ), pad_val=114.0, type='CachedMosaic'),
+    dict(
+        keep_ratio=True,
+        ratio_range=(
+            0.1,
+            2.0,
+        ),
+        scale=(
+            1280,
+            1280,
+        ),
+        type='RandomResize'),
+    dict(
+        allow_negative_crop=True,
+        crop_size=(
+            640,
+            640,
+        ),
+        recompute_bbox=True,
+        type='RandomCrop'),
+    dict(type='YOLOXHSVRandomAug'),
+    dict(prob=0.5, type='RandomFlip'),
+    dict(pad_val=dict(img=(
+        114,
+        114,
+        114,
+    )), size=(
+        640,
+        640,
+    ), type='Pad'),
+    dict(
+        img_scale=(
+            640,
+            640,
+        ),
+        max_cached_images=20,
+        pad_val=(
+            114,
+            114,
+            114,
+        ),
+        ratio_range=(
+            1.0,
+            1.0,
+        ),
+        type='CachedMixUp'),
+    dict(min_gt_bbox_wh=(
+        1,
+        1,
+    ), type='FilterAnnotations'),
+    dict(type='PackDetInputs'),
+]
+train_pipeline_stage2 = [
+    dict(backend_args=None, type='LoadImageFromFile'),
+    dict(
+        poly2mask=False,
+        type='LoadAnnotations',
+        with_bbox=True,
+        with_mask=True),
+    dict(
+        keep_ratio=True,
+        ratio_range=(
+            0.1,
+            2.0,
+        ),
+        scale=(
+            640,
+            640,
+        ),
+        type='RandomResize'),
+    dict(
+        allow_negative_crop=True,
+        crop_size=(
+            640,
+            640,
+        ),
+        recompute_bbox=True,
+        type='RandomCrop'),
+    dict(min_gt_bbox_wh=(
+        1,
+        1,
+    ), type='FilterAnnotations'),
+    dict(type='YOLOXHSVRandomAug'),
+    dict(prob=0.5, type='RandomFlip'),
+    dict(pad_val=dict(img=(
+        114,
+        114,
+        114,
+    )), size=(
+        640,
+        640,
+    ), type='Pad'),
+    dict(type='PackDetInputs'),
+]
+tta_model = dict(
+    tta_cfg=dict(max_per_img=100, nms=dict(iou_threshold=0.6, type='nms')),
+    type='DetTTAModel')
+tta_pipeline = [
+    dict(backend_args=None, type='LoadImageFromFile'),
+    dict(
+        transforms=[
+            [
+                dict(keep_ratio=True, scale=(
+                    640,
+                    640,
+                ), type='Resize'),
+                dict(keep_ratio=True, scale=(
+                    320,
+                    320,
+                ), type='Resize'),
+                dict(keep_ratio=True, scale=(
+                    960,
+                    960,
+                ), type='Resize'),
+            ],
+            [
+                dict(prob=1.0, type='RandomFlip'),
+                dict(prob=0.0, type='RandomFlip'),
+            ],
+            [
+                dict(
+                    pad_val=dict(img=(
+                        114,
+                        114,
+                        114,
+                    )),
+                    size=(
+                        960,
+                        960,
+                    ),
+                    type='Pad'),
+            ],
+            [
+                dict(type='LoadAnnotations', with_bbox=True),
+            ],
+            [
+                dict(
+                    meta_keys=(
+                        'img_id',
+                        'img_path',
+                        'ori_shape',
+                        'img_shape',
+                        'scale_factor',
+                        'flip',
+                        'flip_direction',
+                    ),
+                    type='PackDetInputs'),
+            ],
+        ],
+        type='TestTimeAug'),
+]
+val_cfg = dict(type='ValLoop')
+val_dataloader = dict(
+    batch_size=5,
+    dataset=dict(
+        ann_file='/cv-dl-framework/test/label_json.json',
+        backend_args=None,
+        data_prefix=dict(
+            img='/kfs2/projects/pvfleets24/repos/cv-dl-framework/test/images/'
+        ),
+        data_root='/kfs2/projects/pvfleets24/repos/cv-dl-framework',
+        metainfo=dict(
+            classes=(
+                'carport-fixed-tilt',
+                'ground-dual-axis-tracker',
+                'ground-fixed-tilt',
+                'ground-single-axis-tracker',
+                'rooftop-fixed-tilt',
+            )),
+        pipeline=[
+            dict(backend_args=None, type='LoadImageFromFile'),
+            dict(keep_ratio=True, scale=(
+                640,
+                640,
+            ), type='Resize'),
+            dict(
+                pad_val=dict(img=(
+                    114,
+                    114,
+                    114,
+                )),
+                size=(
+                    640,
+                    640,
+                ),
+                type='Pad'),
+            dict(type='LoadAnnotations', with_bbox=True),
+            dict(
+                meta_keys=(
+                    'img_id',
+                    'img_path',
+                    'ori_shape',
+                    'img_shape',
+                    'scale_factor',
+                ),
+                type='PackDetInputs'),
+        ],
+        test_mode=True,
+        type='CocoDataset'),
+    drop_last=False,
+    num_workers=10,
+    persistent_workers=True,
+    sampler=dict(shuffle=False, type='DefaultSampler'))
+val_evaluator = dict(
+    ann_file='/cv-dl-framework/test/label_json.json',
+    backend_args=None,
+    format_only=False,
+    metric=[
+        'bbox',
+        'segm',
+    ],
+    proposal_nums=(
+        100,
+        1,
+        10,
+    ),
+    type='CocoMetric')
+vis_backends = [
+    dict(type='LocalVisBackend'),
+]
+visualizer = dict(
+    name='visualizer',
+    type='DetLocalVisualizer',
+    vis_backends=[
+        dict(
+            save_dir='/12_03_2026_12_24_40',
+            type='LocalVisBackend'),
+    ])
+work_dir = '/12_03_2026_12_24_40'

panel_detection_model.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b99123151bbe20ad02e742c91df2e4f3f3b63f0603d117a08412d5665238992c
+size 870056877

post_hurricane_config.py

@@ -0,0 +1,454 @@
+auto_scale_lr = dict(base_batch_size=16, enable=False)
+backend_args = None
+data_root = '/kfs2/projects/pvfleets24/repos/cv-dl-framework'
+dataset_type = 'CocoDataset'
+default_hooks = dict(
+    checkpoint=dict(
+        rule='greater', save_best='coco/bbox_mAP_50', type='CheckpointHook'),
+    logger=dict(interval=50, type='LoggerHook'),
+    param_scheduler=dict(type='ParamSchedulerHook'),
+    sampler_seed=dict(type='DistSamplerSeedHook'),
+    timer=dict(type='IterTimerHook'),
+    visualization=dict(type='DetVisualizationHook'))
+default_scope = 'mmdet'
+env_cfg = dict(
+    cudnn_benchmark=False,
+    dist_cfg=dict(backend='nccl'),
+    mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0))
+launcher = 'none'
+load_from = \
+    ('/kfs2/projects/pvfleets24/repos/cv-dl-framework/runs/' +
+     '02_06_2025_20_53_05/best_coco_bbox_mAP_50_epoch_15.pth')
+log_level = 'INFO'
+log_processor = dict(by_epoch=True, type='LogProcessor', window_size=50)
+metainfo = dict(classes=('panel', ))
+model = dict(
+    backbone=dict(
+        base_width=4,
+        depth=101,
+        frozen_stages=1,
+        groups=64,
+        init_cfg=None,
+        norm_cfg=dict(requires_grad=True, type='BN'),
+        norm_eval=True,
+        num_stages=4,
+        out_indices=(
+            0,
+            1,
+            2,
+            3,
+        ),
+        style='pytorch',
+        type='ResNeXt'),
+    data_preprocessor=dict(
+        bgr_to_rgb=True,
+        mean=[
+            123.675,
+            116.28,
+            103.53,
+        ],
+        pad_mask=True,
+        pad_size_divisor=32,
+        std=[
+            58.395,
+            57.12,
+            57.375,
+        ],
+        type='DetDataPreprocessor'),
+    neck=dict(
+        in_channels=[
+            256,
+            512,
+            1024,
+            2048,
+        ],
+        num_outs=5,
+        out_channels=256,
+        type='FPN'),
+    roi_head=dict(
+        bbox_head=dict(
+            bbox_coder=dict(
+                target_means=[
+                    0.0,
+                    0.0,
+                    0.0,
+                    0.0,
+                ],
+                target_stds=[
+                    0.1,
+                    0.1,
+                    0.2,
+                    0.2,
+                ],
+                type='DeltaXYWHBBoxCoder'),
+            fc_out_channels=1024,
+            in_channels=256,
+            loss_bbox=dict(loss_weight=1.0, type='L1Loss'),
+            loss_cls=dict(
+                loss_weight=1.0, type='CrossEntropyLoss', use_sigmoid=False),
+            num_classes=1,
+            reg_class_agnostic=False,
+            roi_feat_size=7,
+            type='Shared2FCBBoxHead'),
+        bbox_roi_extractor=dict(
+            featmap_strides=[
+                4,
+                8,
+                16,
+                32,
+            ],
+            out_channels=256,
+            roi_layer=dict(output_size=7, sampling_ratio=0, type='RoIAlign'),
+            type='SingleRoIExtractor'),
+        mask_head=dict(
+            conv_out_channels=256,
+            in_channels=256,
+            loss_mask=dict(
+                loss_weight=1.0, type='CrossEntropyLoss', use_mask=True),
+            num_classes=1,
+            num_convs=4,
+            type='FCNMaskHead'),
+        mask_roi_extractor=dict(
+            featmap_strides=[
+                4,
+                8,
+                16,
+                32,
+            ],
+            out_channels=256,
+            roi_layer=dict(output_size=14, sampling_ratio=0, type='RoIAlign'),
+            type='SingleRoIExtractor'),
+        test_cfg=dict(
+            mask_thr_binary=0.5,
+            max_per_img=100,
+            nms=dict(iou_threshold=0.5, type='nms'),
+            score_thr=0.05),
+        train_cfg=dict(
+            assigner=dict(
+                ignore_iof_thr=-1,
+                match_low_quality=True,
+                min_pos_iou=0.5,
+                neg_iou_thr=0.5,
+                pos_iou_thr=0.5,
+                type='MaxIoUAssigner'),
+            debug=False,
+            mask_size=28,
+            pos_weight=-1,
+            sampler=dict(
+                add_gt_as_proposals=True,
+                neg_pos_ub=-1,
+                num=512,
+                pos_fraction=0.25,
+                type='RandomSampler')),
+        type='StandardRoIHead'),
+    rpn_head=dict(
+        anchor_generator=dict(
+            ratios=[
+                0.5,
+                1.0,
+                2.0,
+            ],
+            scales=[
+                8,
+            ],
+            strides=[
+                4,
+                8,
+                16,
+                32,
+                64,
+            ],
+            type='AnchorGenerator'),
+        bbox_coder=dict(
+            target_means=[
+                0.0,
+                0.0,
+                0.0,
+                0.0,
+            ],
+            target_stds=[
+                1.0,
+                1.0,
+                1.0,
+                1.0,
+            ],
+            type='DeltaXYWHBBoxCoder'),
+        feat_channels=256,
+        in_channels=256,
+        loss_bbox=dict(loss_weight=1.0, type='L1Loss'),
+        loss_cls=dict(
+            loss_weight=1.0, type='CrossEntropyLoss', use_sigmoid=True),
+        type='RPNHead'),
+    test_cfg=dict(
+        rcnn=dict(
+            mask_thr_binary=0.5,
+            max_per_img=100,
+            nms=dict(iou_threshold=0.5, type='nms'),
+            score_thr=0.05),
+        rpn=dict(
+            max_per_img=1000,
+            min_bbox_size=0,
+            nms=dict(iou_threshold=0.7, type='nms'),
+            nms_pre=1000)),
+    train_cfg=dict(
+        rcnn=dict(
+            assigner=dict(
+                ignore_iof_thr=-1,
+                match_low_quality=True,
+                min_pos_iou=0.5,
+                neg_iou_thr=0.5,
+                pos_iou_thr=0.5,
+                type='MaxIoUAssigner'),
+            debug=False,
+            mask_size=28,
+            pos_weight=-1,
+            sampler=dict(
+                add_gt_as_proposals=True,
+                neg_pos_ub=-1,
+                num=512,
+                pos_fraction=0.25,
+                type='RandomSampler')),
+        rpn=dict(
+            allowed_border=-1,
+            assigner=dict(
+                ignore_iof_thr=-1,
+                match_low_quality=True,
+                min_pos_iou=0.3,
+                neg_iou_thr=0.3,
+                pos_iou_thr=0.7,
+                type='MaxIoUAssigner'),
+            debug=False,
+            pos_weight=-1,
+            sampler=dict(
+                add_gt_as_proposals=False,
+                neg_pos_ub=-1,
+                num=256,
+                pos_fraction=0.5,
+                type='RandomSampler')),
+        rpn_proposal=dict(
+            max_per_img=1000,
+            min_bbox_size=0,
+            nms=dict(iou_threshold=0.7, type='nms'),
+            nms_pre=2000)),
+    type='MaskRCNN')
+optim_wrapper = dict(
+    optimizer=dict(
+        lr=0.0006313442216876994,
+        momentum=0.9076082930433617,
+        type='SGD',
+        weight_decay=0.008844292412907089),
+    type='OptimWrapper')
+param_scheduler = [
+    dict(
+        begin=0, by_epoch=False, end=500, start_factor=0.001, type='LinearLR'),
+    dict(
+        begin=0,
+        by_epoch=True,
+        end=12,
+        gamma=0.1,
+        milestones=[
+            9,
+            11,
+        ],
+        type='MultiStepLR'),
+]
+resume = False
+test_cfg = dict(type='TestLoop')
+test_dataloader = dict(
+    batch_size=2,
+    dataset=dict(
+        ann_file=('/kfs2/projects/pvfleets24/repos/cv-dl-framework' +
+                  '/test/label_json.json'),
+        backend_args=None,
+        data_prefix=dict(
+            img='/kfs2/projects/pvfleets24/repos/cv-dl-framework/test/images/'
+        ),
+        data_root='/kfs2/projects/pvfleets24/repos/cv-dl-framework',
+        metainfo=dict(classes=('panel', )),
+        pipeline=[
+            dict(backend_args=None, type='LoadImageFromFile'),
+            dict(keep_ratio=True, scale=(
+                1333,
+                800,
+            ), type='Resize'),
+            dict(
+                poly2mask=False,
+                type='LoadAnnotations',
+                with_bbox=True,
+                with_mask=True),
+            dict(
+                meta_keys=(
+                    'img_id',
+                    'img_path',
+                    'ori_shape',
+                    'img_shape',
+                    'scale_factor',
+                ),
+                type='PackDetInputs'),
+        ],
+        test_mode=True,
+        type='CocoDataset'),
+    drop_last=False,
+    num_workers=2,
+    persistent_workers=True,
+    sampler=dict(shuffle=False, type='DefaultSampler'))
+test_evaluator = dict(
+    ann_file=('/kfs2/projects/pvfleets24/repos/cv-dl-framework/' +
+              'test/label_json.json'),
+    backend_args=None,
+    metric=[
+        'bbox',
+        'segm',
+    ],
+    type='CocoMetric')
+test_pipeline = [
+    dict(backend_args=None, type='LoadImageFromFile'),
+    dict(keep_ratio=True, scale=(
+        1333,
+        800,
+    ), type='Resize'),
+    dict(
+        poly2mask=False,
+        type='LoadAnnotations',
+        with_bbox=True,
+        with_mask=True),
+    dict(
+        meta_keys=(
+            'img_id',
+            'img_path',
+            'ori_shape',
+            'img_shape',
+            'scale_factor',
+        ),
+        type='PackDetInputs'),
+]
+train_cfg = dict(max_epochs=80, type='EpochBasedTrainLoop', val_interval=3)
+train_dataloader = dict(
+    batch_sampler=dict(type='AspectRatioBatchSampler'),
+    batch_size=2,
+    dataset=dict(
+        dataset=dict(
+            ann_file=('/kfs2/projects/pvfleets24/repos/cv-dl-framework/' +
+                      'train/label_json.json'),
+            backend_args=None,
+            data_prefix=dict(
+                img=('/kfs2/projects/pvfleets24/repos/cv-dl-framework/' +
+                     'train/images/')
+            ),
+            data_root='/kfs2/projects/pvfleets24/repos/cv-dl-framework',
+            filter_cfg=dict(filter_empty_gt=True, min_size=32),
+            metainfo=dict(classes=('panel', )),
+            pipeline=[
+                dict(backend_args=None, type='LoadImageFromFile'),
+                dict(
+                    poly2mask=False,
+                    type='LoadAnnotations',
+                    with_bbox=True,
+                    with_mask=True),
+                dict(
+                    keep_ratio=True,
+                    scale=[
+                        (
+                            1333,
+                            640,
+                        ),
+                        (
+                            1333,
+                            800,
+                        ),
+                    ],
+                    type='RandomResize'),
+                dict(prob=0.5, type='RandomFlip'),
+                dict(type='PackDetInputs'),
+            ],
+            type='CocoDataset'),
+        times=3,
+        type='RepeatDataset'),
+    num_workers=2,
+    persistent_workers=True,
+    sampler=dict(shuffle=True, type='DefaultSampler'))
+train_pipeline = [
+    dict(backend_args=None, type='LoadImageFromFile'),
+    dict(
+        poly2mask=False,
+        type='LoadAnnotations',
+        with_bbox=True,
+        with_mask=True),
+    dict(
+        keep_ratio=True,
+        scale=[
+            (
+                1333,
+                640,
+            ),
+            (
+                1333,
+                800,
+            ),
+        ],
+        type='RandomResize'),
+    dict(prob=0.5, type='RandomFlip'),
+    dict(type='PackDetInputs'),
+]
+val_cfg = dict(type='ValLoop')
+val_dataloader = dict(
+    batch_size=2,
+    dataset=dict(
+        ann_file=('/kfs2/projects/pvfleets24/repos/cv-dl-framework/' +
+                  'test/label_json.json'),
+        backend_args=None,
+        data_prefix=dict(
+            img='/kfs2/projects/pvfleets24/repos/cv-dl-framework/test/images/'
+        ),
+        data_root='/kfs2/projects/pvfleets24/repos/cv-dl-framework',
+        metainfo=dict(classes=('panel', )),
+        pipeline=[
+            dict(backend_args=None, type='LoadImageFromFile'),
+            dict(keep_ratio=True, scale=(
+                1333,
+                800,
+            ), type='Resize'),
+            dict(
+                poly2mask=False,
+                type='LoadAnnotations',
+                with_bbox=True,
+                with_mask=True),
+            dict(
+                meta_keys=(
+                    'img_id',
+                    'img_path',
+                    'ori_shape',
+                    'img_shape',
+                    'scale_factor',
+                ),
+                type='PackDetInputs'),
+        ],
+        test_mode=True,
+        type='CocoDataset'),
+    drop_last=False,
+    num_workers=2,
+    persistent_workers=True,
+    sampler=dict(shuffle=False, type='DefaultSampler'))
+val_evaluator = dict(
+    ann_file=('/kfs2/projects/pvfleets24/repos/' +
+              'cv-dl-framework/test/label_json.json'),
+    backend_args=None,
+    metric=[
+        'bbox',
+        'segm',
+    ],
+    type='CocoMetric')
+vis_backends = [
+    dict(type='LocalVisBackend'),
+]
+visualizer = dict(
+    name='visualizer',
+    type='DetLocalVisualizer',
+    vis_backends=[
+        dict(
+            save_dir=('/kfs2/projects/pvfleets24/repos/' +
+                      'cv-dl-framework/runs/02_06_2025_20_53_05'),
+            type='LocalVisBackend'),
+    ])
+work_dir = ('/)kfs2/projects/pvfleets24/repos/cv-dl-framework' +
+            '/runs/02_06_2025_20_53_05')

post_hurricane_model.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:daa29aea6fc0246aa08f044d53c5364294536e6a7ce2a5b39ce0035ede7d6738
+size 409652222

pre_hurricane_config.py

@@ -0,0 +1,617 @@
+auto_scale_lr = dict(base_batch_size=16, enable=False)
+backend_args = None
+base_lr = 0.004
+custom_hooks = [
+    dict(
+        ema_type='ExpMomentumEMA',
+        momentum=0.0002,
+        priority=49,
+        type='EMAHook',
+        update_buffers=True),
+    dict(
+        switch_epoch=280,
+        switch_pipeline=[
+            dict(backend_args=None, type='LoadImageFromFile'),
+            dict(
+                poly2mask=False,
+                type='LoadAnnotations',
+                with_bbox=True,
+                with_mask=True),
+            dict(
+                keep_ratio=True,
+                ratio_range=(
+                    0.1,
+                    2.0,
+                ),
+                scale=(
+                    640,
+                    640,
+                ),
+                type='RandomResize'),
+            dict(
+                allow_negative_crop=True,
+                crop_size=(
+                    640,
+                    640,
+                ),
+                recompute_bbox=True,
+                type='RandomCrop'),
+            dict(min_gt_bbox_wh=(
+                1,
+                1,
+            ), type='FilterAnnotations'),
+            dict(type='YOLOXHSVRandomAug'),
+            dict(prob=0.5, type='RandomFlip'),
+            dict(
+                pad_val=dict(img=(
+                    114,
+                    114,
+                    114,
+                )),
+                size=(
+                    640,
+                    640,
+                ),
+                type='Pad'),
+            dict(type='PackDetInputs'),
+        ],
+        type='PipelineSwitchHook'),
+]
+data_root = '/kfs2/projects/pvfleets24/repos/cv-dl-framework'
+dataset_type = 'CocoDataset'
+default_hooks = dict(
+    checkpoint=dict(
+        rule='greater', save_best='coco/bbox_mAP_50', type='CheckpointHook'),
+    logger=dict(interval=50, type='LoggerHook'),
+    param_scheduler=dict(type='ParamSchedulerHook'),
+    sampler_seed=dict(type='DistSamplerSeedHook'),
+    timer=dict(type='IterTimerHook'),
+    visualization=dict(type='DetVisualizationHook'))
+default_scope = 'mmdet'
+env_cfg = dict(
+    cudnn_benchmark=False,
+    dist_cfg=dict(backend='nccl'),
+    mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0))
+img_scales = [
+    (
+        640,
+        640,
+    ),
+    (
+        320,
+        320,
+    ),
+    (
+        960,
+        960,
+    ),
+]
+interval = 10
+launcher = 'none'
+load_from = ('/kfs2/projects/pvfleets24/repos/cv-dl-framework/runs/' +
+             '03_06_2025_11_26_36/best_coco_bbox_mAP_50_epoch_283.pth')
+log_level = 'INFO'
+log_processor = dict(by_epoch=True, type='LogProcessor', window_size=50)
+max_epochs = 300
+metainfo = dict(classes=('panel', ))
+model = dict(
+    backbone=dict(
+        act_cfg=dict(inplace=True, type='SiLU'),
+        arch='P5',
+        channel_attention=True,
+        deepen_factor=1,
+        expand_ratio=0.5,
+        norm_cfg=dict(type='SyncBN'),
+        type='CSPNeXt',
+        widen_factor=1),
+    bbox_head=dict(
+        act_cfg=dict(inplace=True, type='SiLU'),
+        anchor_generator=dict(
+            offset=0, strides=[
+                8,
+                16,
+                32,
+            ], type='MlvlPointGenerator'),
+        bbox_coder=dict(type='DistancePointBBoxCoder'),
+        feat_channels=256,
+        in_channels=256,
+        loss_bbox=dict(loss_weight=2.0, type='GIoULoss'),
+        loss_cls=dict(
+            beta=2.0,
+            loss_weight=1.0,
+            type='QualityFocalLoss',
+            use_sigmoid=True),
+        loss_mask=dict(
+            eps=5e-06, loss_weight=2.0, reduction='mean', type='DiceLoss'),
+        norm_cfg=dict(requires_grad=True, type='SyncBN'),
+        num_classes=1,
+        pred_kernel_size=1,
+        share_conv=True,
+        stacked_convs=2,
+        test_cfg=dict(
+            mask_thr_binary=0.5,
+            max_per_img=100,
+            min_bbox_size=0,
+            nms=dict(iou_threshold=0.6, type='nms'),
+            nms_pre=1000,
+            score_thr=0.05),
+        train_cfg=dict(
+            allowed_border=-1,
+            assigner=dict(topk=13, type='DynamicSoftLabelAssigner'),
+            debug=False,
+            pos_weight=-1),
+        type='RTMDetInsSepBNHead'),
+    data_preprocessor=dict(
+        batch_augments=None,
+        bgr_to_rgb=False,
+        mean=[
+            103.53,
+            116.28,
+            123.675,
+        ],
+        std=[
+            57.375,
+            57.12,
+            58.395,
+        ],
+        type='DetDataPreprocessor'),
+    neck=dict(
+        act_cfg=dict(inplace=True, type='SiLU'),
+        expand_ratio=0.5,
+        in_channels=[
+            256,
+            512,
+            1024,
+        ],
+        norm_cfg=dict(type='SyncBN'),
+        num_csp_blocks=3,
+        out_channels=256,
+        type='CSPNeXtPAFPN'),
+    test_cfg=dict(
+        mask_thr_binary=0.5,
+        max_per_img=100,
+        min_bbox_size=0,
+        nms=dict(iou_threshold=0.6, type='nms'),
+        nms_pre=1000,
+        score_thr=0.05),
+    train_cfg=dict(
+        allowed_border=-1,
+        assigner=dict(topk=13, type='DynamicSoftLabelAssigner'),
+        debug=False,
+        pos_weight=-1),
+    type='RTMDet')
+optim_wrapper = dict(
+    optimizer=dict(lr=0.004, type='AdamW', weight_decay=0.05),
+    paramwise_cfg=dict(
+        bias_decay_mult=0, bypass_duplicate=True, norm_decay_mult=0),
+    type='OptimWrapper')
+param_scheduler = [
+    dict(
+        begin=0, by_epoch=False, end=1000, start_factor=1e-05,
+        type='LinearLR'),
+    dict(
+        T_max=150,
+        begin=150,
+        by_epoch=True,
+        convert_to_iter_based=True,
+        end=300,
+        eta_min=0.0002,
+        type='CosineAnnealingLR'),
+]
+resume = False
+stage2_num_epochs = 20
+test_cfg = dict(type='TestLoop')
+test_dataloader = dict(
+    batch_size=5,
+    dataset=dict(
+        ann_file=('/kfs2/projects/pvfleets24/repos/cv-dl-framework/' +
+                  'test/label_json.json'),
+        backend_args=None,
+        data_prefix=dict(
+            img='/kfs2/projects/pvfleets24/repos/cv-dl-framework/test/images/'
+        ),
+        data_root='/kfs2/projects/pvfleets24/repos/cv-dl-framework',
+        metainfo=dict(classes=('panel', )),
+        pipeline=[
+            dict(backend_args=None, type='LoadImageFromFile'),
+            dict(keep_ratio=True, scale=(
+                640,
+                640,
+            ), type='Resize'),
+            dict(
+                pad_val=dict(img=(
+                    114,
+                    114,
+                    114,
+                )),
+                size=(
+                    640,
+                    640,
+                ),
+                type='Pad'),
+            dict(type='LoadAnnotations', with_bbox=True),
+            dict(
+                meta_keys=(
+                    'img_id',
+                    'img_path',
+                    'ori_shape',
+                    'img_shape',
+                    'scale_factor',
+                ),
+                type='PackDetInputs'),
+        ],
+        test_mode=True,
+        type='CocoDataset'),
+    drop_last=False,
+    num_workers=10,
+    persistent_workers=True,
+    sampler=dict(shuffle=False, type='DefaultSampler'))
+test_evaluator = dict(
+    ann_file=('/kfs2/projects/pvfleets24/repos/cv-dl-framework/' +
+              'test/label_json.json'),
+    backend_args=None,
+    format_only=False,
+    metric=[
+        'bbox',
+        'segm',
+    ],
+    proposal_nums=(
+        100,
+        1,
+        10,
+    ),
+    type='CocoMetric')
+test_pipeline = [
+    dict(backend_args=None, type='LoadImageFromFile'),
+    dict(keep_ratio=True, scale=(
+        640,
+        640,
+    ), type='Resize'),
+    dict(pad_val=dict(img=(
+        114,
+        114,
+        114,
+    )), size=(
+        640,
+        640,
+    ), type='Pad'),
+    dict(type='LoadAnnotations', with_bbox=True),
+    dict(
+        meta_keys=(
+            'img_id',
+            'img_path',
+            'ori_shape',
+            'img_shape',
+            'scale_factor',
+        ),
+        type='PackDetInputs'),
+]
+train_cfg = dict(
+    dynamic_intervals=[
+        (
+            280,
+            1,
+        ),
+    ],
+    max_epochs=300,
+    type='EpochBasedTrainLoop',
+    val_interval=3)
+train_dataloader = dict(
+    batch_sampler=None,
+    batch_size=32,
+    dataset=dict(
+        ann_file=('/kfs2/projects/pvfleets24/repos/cv-dl-framework/' +
+                  'train/label_json.json'),
+        backend_args=None,
+        data_prefix=dict(
+            img='/kfs2/projects/pvfleets24/repos/cv-dl-framework/train/images/'
+        ),
+        data_root='/kfs2/projects/pvfleets24/repos/cv-dl-framework',
+        filter_cfg=dict(filter_empty_gt=True, min_size=32),
+        metainfo=dict(classes=('panel', )),
+        pipeline=[
+            dict(backend_args=None, type='LoadImageFromFile'),
+            dict(
+                poly2mask=False,
+                type='LoadAnnotations',
+                with_bbox=True,
+                with_mask=True),
+            dict(img_scale=(
+                640,
+                640,
+            ), pad_val=114.0, type='CachedMosaic'),
+            dict(
+                keep_ratio=True,
+                ratio_range=(
+                    0.1,
+                    2.0,
+                ),
+                scale=(
+                    1280,
+                    1280,
+                ),
+                type='RandomResize'),
+            dict(
+                allow_negative_crop=True,
+                crop_size=(
+                    640,
+                    640,
+                ),
+                recompute_bbox=True,
+                type='RandomCrop'),
+            dict(type='YOLOXHSVRandomAug'),
+            dict(prob=0.5, type='RandomFlip'),
+            dict(
+                pad_val=dict(img=(
+                    114,
+                    114,
+                    114,
+                )),
+                size=(
+                    640,
+                    640,
+                ),
+                type='Pad'),
+            dict(
+                img_scale=(
+                    640,
+                    640,
+                ),
+                max_cached_images=20,
+                pad_val=(
+                    114,
+                    114,
+                    114,
+                ),
+                ratio_range=(
+                    1.0,
+                    1.0,
+                ),
+                type='CachedMixUp'),
+            dict(min_gt_bbox_wh=(
+                1,
+                1,
+            ), type='FilterAnnotations'),
+            dict(type='PackDetInputs'),
+        ],
+        type='CocoDataset'),
+    num_workers=10,
+    persistent_workers=True,
+    pin_memory=True,
+    sampler=dict(shuffle=True, type='DefaultSampler'))
+train_pipeline = [
+    dict(backend_args=None, type='LoadImageFromFile'),
+    dict(
+        poly2mask=False,
+        type='LoadAnnotations',
+        with_bbox=True,
+        with_mask=True),
+    dict(img_scale=(
+        640,
+        640,
+    ), pad_val=114.0, type='CachedMosaic'),
+    dict(
+        keep_ratio=True,
+        ratio_range=(
+            0.1,
+            2.0,
+        ),
+        scale=(
+            1280,
+            1280,
+        ),
+        type='RandomResize'),
+    dict(
+        allow_negative_crop=True,
+        crop_size=(
+            640,
+            640,
+        ),
+        recompute_bbox=True,
+        type='RandomCrop'),
+    dict(type='YOLOXHSVRandomAug'),
+    dict(prob=0.5, type='RandomFlip'),
+    dict(pad_val=dict(img=(
+        114,
+        114,
+        114,
+    )), size=(
+        640,
+        640,
+    ), type='Pad'),
+    dict(
+        img_scale=(
+            640,
+            640,
+        ),
+        max_cached_images=20,
+        pad_val=(
+            114,
+            114,
+            114,
+        ),
+        ratio_range=(
+            1.0,
+            1.0,
+        ),
+        type='CachedMixUp'),
+    dict(min_gt_bbox_wh=(
+        1,
+        1,
+    ), type='FilterAnnotations'),
+    dict(type='PackDetInputs'),
+]
+train_pipeline_stage2 = [
+    dict(backend_args=None, type='LoadImageFromFile'),
+    dict(
+        poly2mask=False,
+        type='LoadAnnotations',
+        with_bbox=True,
+        with_mask=True),
+    dict(
+        keep_ratio=True,
+        ratio_range=(
+            0.1,
+            2.0,
+        ),
+        scale=(
+            640,
+            640,
+        ),
+        type='RandomResize'),
+    dict(
+        allow_negative_crop=True,
+        crop_size=(
+            640,
+            640,
+        ),
+        recompute_bbox=True,
+        type='RandomCrop'),
+    dict(min_gt_bbox_wh=(
+        1,
+        1,
+    ), type='FilterAnnotations'),
+    dict(type='YOLOXHSVRandomAug'),
+    dict(prob=0.5, type='RandomFlip'),
+    dict(pad_val=dict(img=(
+        114,
+        114,
+        114,
+    )), size=(
+        640,
+        640,
+    ), type='Pad'),
+    dict(type='PackDetInputs'),
+]
+tta_model = dict(
+    tta_cfg=dict(max_per_img=100, nms=dict(iou_threshold=0.6, type='nms')),
+    type='DetTTAModel')
+tta_pipeline = [
+    dict(backend_args=None, type='LoadImageFromFile'),
+    dict(
+        transforms=[
+            [
+                dict(keep_ratio=True, scale=(
+                    640,
+                    640,
+                ), type='Resize'),
+                dict(keep_ratio=True, scale=(
+                    320,
+                    320,
+                ), type='Resize'),
+                dict(keep_ratio=True, scale=(
+                    960,
+                    960,
+                ), type='Resize'),
+            ],
+            [
+                dict(prob=1.0, type='RandomFlip'),
+                dict(prob=0.0, type='RandomFlip'),
+            ],
+            [
+                dict(
+                    pad_val=dict(img=(
+                        114,
+                        114,
+                        114,
+                    )),
+                    size=(
+                        960,
+                        960,
+                    ),
+                    type='Pad'),
+            ],
+            [
+                dict(type='LoadAnnotations', with_bbox=True),
+            ],
+            [
+                dict(
+                    meta_keys=(
+                        'img_id',
+                        'img_path',
+                        'ori_shape',
+                        'img_shape',
+                        'scale_factor',
+                        'flip',
+                        'flip_direction',
+                    ),
+                    type='PackDetInputs'),
+            ],
+        ],
+        type='TestTimeAug'),
+]
+val_cfg = dict(type='ValLoop')
+val_dataloader = dict(
+    batch_size=5,
+    dataset=dict(
+        ann_file=('/kfs2/projects/pvfleets24/repos/cv-dl-framework/' +
+                  'test/label_json.json'),
+        backend_args=None,
+        data_prefix=dict(
+            img='/kfs2/projects/pvfleets24/repos/cv-dl-framework/test/images/'
+        ),
+        data_root='/kfs2/projects/pvfleets24/repos/cv-dl-framework',
+        metainfo=dict(classes=('panel', )),
+        pipeline=[
+            dict(backend_args=None, type='LoadImageFromFile'),
+            dict(keep_ratio=True, scale=(
+                640,
+                640,
+            ), type='Resize'),
+            dict(
+                pad_val=dict(img=(
+                    114,
+                    114,
+                    114,
+                )),
+                size=(
+                    640,
+                    640,
+                ),
+                type='Pad'),
+            dict(type='LoadAnnotations', with_bbox=True),
+            dict(
+                meta_keys=(
+                    'img_id',
+                    'img_path',
+                    'ori_shape',
+                    'img_shape',
+                    'scale_factor',
+                ),
+                type='PackDetInputs'),
+        ],
+        test_mode=True,
+        type='CocoDataset'),
+    drop_last=False,
+    num_workers=10,
+    persistent_workers=True,
+    sampler=dict(shuffle=False, type='DefaultSampler'))
+val_evaluator = dict(
+    ann_file=('/kfs2/projects/pvfleets24/repos/cv-dl-framework/' +
+              'test/label_json.json'),
+    backend_args=None,
+    format_only=False,
+    metric=[
+        'bbox',
+        'segm',
+    ],
+    proposal_nums=(
+        100,
+        1,
+        10,
+    ),
+    type='CocoMetric')
+vis_backends = [
+    dict(type='LocalVisBackend'),
+]
+visualizer = dict(
+    name='visualizer',
+    type='DetLocalVisualizer',
+    vis_backends=[
+        dict(
+            save_dir=('/kfs2/projects/pvfleets24/repos/cv-dl-framework/' +
+                      'runs/03_06_2025_11_26_36'),
+            type='LocalVisBackend'),
+    ])
+work_dir = ('/kfs2/projects/pvfleets24/repos/cv-dl-framework/' +
+            'runs/03_06_2025_11_26_36')

pre_hurricane_model.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a404a586b82d2afbb6c04b5ac175a7414cb992ee4da0ccebe08d1afdd7aa9d12
+size 485264789

sol_searcher_config.py

@@ -0,0 +1,566 @@
+auto_scale_lr = dict(base_batch_size=16, enable=False)
+backend_args = None
+base_lr = 0.004
+custom_hooks = [
+    dict(
+        ema_type='ExpMomentumEMA',
+        momentum=0.0002,
+        priority=49,
+        type='EMAHook',
+        update_buffers=True),
+    dict(
+        switch_epoch=280,
+        switch_pipeline=[
+            dict(backend_args=None, type='LoadImageFromFile'),
+            dict(type='LoadAnnotations', with_bbox=True),
+            dict(
+                keep_ratio=True,
+                ratio_range=(
+                    0.1,
+                    2.0,
+                ),
+                scale=(
+                    640,
+                    640,
+                ),
+                type='RandomResize'),
+            dict(crop_size=(
+                640,
+                640,
+            ), type='RandomCrop'),
+            dict(type='YOLOXHSVRandomAug'),
+            dict(prob=0.5, type='RandomFlip'),
+            dict(
+                pad_val=dict(img=(
+                    114,
+                    114,
+                    114,
+                )),
+                size=(
+                    640,
+                    640,
+                ),
+                type='Pad'),
+            dict(type='PackDetInputs'),
+        ],
+        type='PipelineSwitchHook'),
+]
+data_root = '/kfs2/projects/pvfleets24/repos/cv-dl-framework'
+dataset_type = 'CocoDataset'
+default_hooks = dict(
+    checkpoint=dict(
+        rule='greater', save_best='coco/bbox_mAP_50', type='CheckpointHook'),
+    logger=dict(interval=50, type='LoggerHook'),
+    param_scheduler=dict(type='ParamSchedulerHook'),
+    sampler_seed=dict(type='DistSamplerSeedHook'),
+    timer=dict(type='IterTimerHook'),
+    visualization=dict(type='DetVisualizationHook'))
+default_scope = 'mmdet'
+env_cfg = dict(
+    cudnn_benchmark=False,
+    dist_cfg=dict(backend='nccl'),
+    mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0))
+img_scales = [
+    (
+        640,
+        640,
+    ),
+    (
+        320,
+        320,
+    ),
+    (
+        960,
+        960,
+    ),
+]
+interval = 10
+launcher = 'none'
+load_from = ('/kfs2/projects/pvfleets24/repos/cv-dl-framework/runs/' +
+             'sol-searcher.v1i.coco-segmentation/07_06_2025_03_44_01/' +
+             'best_coco_bbox_mAP_50_epoch_324.pth')
+log_level = 'INFO'
+log_processor = dict(by_epoch=True, type='LogProcessor', window_size=50)
+max_epochs = 300
+metainfo = dict(classes=('panel', ))
+model = dict(
+    backbone=dict(
+        act_cfg=dict(inplace=True, type='SiLU'),
+        arch='P5',
+        channel_attention=True,
+        deepen_factor=1.33,
+        expand_ratio=0.5,
+        norm_cfg=dict(type='SyncBN'),
+        type='CSPNeXt',
+        widen_factor=1.25),
+    bbox_head=dict(
+        act_cfg=dict(inplace=True, type='SiLU'),
+        anchor_generator=dict(
+            offset=0, strides=[
+                8,
+                16,
+                32,
+            ], type='MlvlPointGenerator'),
+        bbox_coder=dict(type='DistancePointBBoxCoder'),
+        exp_on_reg=True,
+        feat_channels=320,
+        in_channels=320,
+        loss_bbox=dict(loss_weight=2.0, type='GIoULoss'),
+        loss_cls=dict(
+            beta=2.0,
+            loss_weight=1.0,
+            type='QualityFocalLoss',
+            use_sigmoid=True),
+        norm_cfg=dict(type='SyncBN'),
+        num_classes=1,
+        pred_kernel_size=1,
+        share_conv=True,
+        stacked_convs=2,
+        test_cfg=dict(
+            max_per_img=300,
+            min_bbox_size=0,
+            nms=dict(iou_threshold=0.65, type='nms'),
+            nms_pre=30000,
+            score_thr=0.001),
+        train_cfg=dict(
+            allowed_border=-1,
+            assigner=dict(topk=13, type='DynamicSoftLabelAssigner'),
+            debug=False,
+            pos_weight=-1),
+        type='RTMDetSepBNHead',
+        with_objectness=False),
+    data_preprocessor=dict(
+        batch_augments=None,
+        bgr_to_rgb=False,
+        mean=[
+            103.53,
+            116.28,
+            123.675,
+        ],
+        std=[
+            57.375,
+            57.12,
+            58.395,
+        ],
+        type='DetDataPreprocessor'),
+    neck=dict(
+        act_cfg=dict(inplace=True, type='SiLU'),
+        expand_ratio=0.5,
+        in_channels=[
+            320,
+            640,
+            1280,
+        ],
+        norm_cfg=dict(type='SyncBN'),
+        num_csp_blocks=4,
+        out_channels=320,
+        type='CSPNeXtPAFPN'),
+    test_cfg=dict(
+        max_per_img=300,
+        min_bbox_size=0,
+        nms=dict(iou_threshold=0.65, type='nms'),
+        nms_pre=30000,
+        score_thr=0.001),
+    train_cfg=dict(
+        allowed_border=-1,
+        assigner=dict(topk=13, type='DynamicSoftLabelAssigner'),
+        debug=False,
+        pos_weight=-1),
+    type='RTMDet')
+optim_wrapper = dict(
+    optimizer=dict(
+        lr=0.0013396075094963768,
+        type='AdamW',
+        weight_decay=0.0764032184205418),
+    paramwise_cfg=dict(
+        bias_decay_mult=0, bypass_duplicate=True, norm_decay_mult=0),
+    type='OptimWrapper')
+param_scheduler = [
+    dict(
+        begin=0, by_epoch=False, end=1000, start_factor=1e-05,
+        type='LinearLR'),
+    dict(
+        T_max=150,
+        begin=150,
+        by_epoch=True,
+        convert_to_iter_based=True,
+        end=300,
+        eta_min=0.0002,
+        type='CosineAnnealingLR'),
+]
+resume = False
+stage2_num_epochs = 20
+test_cfg = dict(type='TestLoop')
+test_dataloader = dict(
+    batch_size=5,
+    dataset=dict(
+        ann_file=('/kfs2/projects/pvfleets24/repos/cv-dl-framework' +
+                  '/test/label_json.json'),
+        backend_args=None,
+        data_prefix=dict(
+            img='/kfs2/projects/pvfleets24/repos/cv-dl-framework/test/images/'
+        ),
+        data_root='/kfs2/projects/pvfleets24/repos/cv-dl-framework',
+        metainfo=dict(classes=('panel', )),
+        pipeline=[
+            dict(backend_args=None, type='LoadImageFromFile'),
+            dict(keep_ratio=True, scale=(
+                640,
+                640,
+            ), type='Resize'),
+            dict(
+                pad_val=dict(img=(
+                    114,
+                    114,
+                    114,
+                )),
+                size=(
+                    640,
+                    640,
+                ),
+                type='Pad'),
+            dict(type='LoadAnnotations', with_bbox=True),
+            dict(
+                meta_keys=(
+                    'img_id',
+                    'img_path',
+                    'ori_shape',
+                    'img_shape',
+                    'scale_factor',
+                ),
+                type='PackDetInputs'),
+        ],
+        test_mode=True,
+        type='CocoDataset'),
+    drop_last=False,
+    num_workers=10,
+    persistent_workers=True,
+    sampler=dict(shuffle=False, type='DefaultSampler'))
+test_evaluator = dict(
+    ann_file=('/kfs2/projects/pvfleets24/repos/cv-dl-framework' +
+              '/test/label_json.json'),
+    backend_args=None,
+    format_only=False,
+    metric='bbox',
+    proposal_nums=(
+        100,
+        1,
+        10,
+    ),
+    type='CocoMetric')
+test_pipeline = [
+    dict(backend_args=None, type='LoadImageFromFile'),
+    dict(keep_ratio=True, scale=(
+        640,
+        640,
+    ), type='Resize'),
+    dict(pad_val=dict(img=(
+        114,
+        114,
+        114,
+    )), size=(
+        640,
+        640,
+    ), type='Pad'),
+    dict(type='LoadAnnotations', with_bbox=True),
+    dict(
+        meta_keys=(
+            'img_id',
+            'img_path',
+            'ori_shape',
+            'img_shape',
+            'scale_factor',
+        ),
+        type='PackDetInputs'),
+]
+train_cfg = dict(
+    dynamic_intervals=[
+        (
+            280,
+            1,
+        ),
+    ],
+    max_epochs=400,
+    type='EpochBasedTrainLoop',
+    val_interval=3)
+train_dataloader = dict(
+    batch_sampler=None,
+    batch_size=32,
+    dataset=dict(
+        ann_file=('/kfs2/projects/pvfleets24/repos/cv-dl-framework' +
+                  '/train/label_json.json'),
+        backend_args=None,
+        data_prefix=dict(
+            img='/kfs2/projects/pvfleets24/repos/cv-dl-framework/train/images/'
+        ),
+        data_root='/kfs2/projects/pvfleets24/repos/cv-dl-framework',
+        filter_cfg=dict(filter_empty_gt=True, min_size=32),
+        metainfo=dict(classes=('panel', )),
+        pipeline=[
+            dict(backend_args=None, type='LoadImageFromFile'),
+            dict(type='LoadAnnotations', with_bbox=True),
+            dict(img_scale=(
+                640,
+                640,
+            ), pad_val=114.0, type='CachedMosaic'),
+            dict(
+                keep_ratio=True,
+                ratio_range=(
+                    0.1,
+                    2.0,
+                ),
+                scale=(
+                    1280,
+                    1280,
+                ),
+                type='RandomResize'),
+            dict(crop_size=(
+                640,
+                640,
+            ), type='RandomCrop'),
+            dict(type='YOLOXHSVRandomAug'),
+            dict(prob=0.5, type='RandomFlip'),
+            dict(
+                pad_val=dict(img=(
+                    114,
+                    114,
+                    114,
+                )),
+                size=(
+                    640,
+                    640,
+                ),
+                type='Pad'),
+            dict(
+                img_scale=(
+                    640,
+                    640,
+                ),
+                max_cached_images=20,
+                pad_val=(
+                    114,
+                    114,
+                    114,
+                ),
+                ratio_range=(
+                    1.0,
+                    1.0,
+                ),
+                type='CachedMixUp'),
+            dict(type='PackDetInputs'),
+        ],
+        type='CocoDataset'),
+    num_workers=10,
+    persistent_workers=True,
+    pin_memory=True,
+    sampler=dict(shuffle=True, type='DefaultSampler'))
+train_pipeline = [
+    dict(backend_args=None, type='LoadImageFromFile'),
+    dict(type='LoadAnnotations', with_bbox=True),
+    dict(img_scale=(
+        640,
+        640,
+    ), pad_val=114.0, type='CachedMosaic'),
+    dict(
+        keep_ratio=True,
+        ratio_range=(
+            0.1,
+            2.0,
+        ),
+        scale=(
+            1280,
+            1280,
+        ),
+        type='RandomResize'),
+    dict(crop_size=(
+        640,
+        640,
+    ), type='RandomCrop'),
+    dict(type='YOLOXHSVRandomAug'),
+    dict(prob=0.5, type='RandomFlip'),
+    dict(pad_val=dict(img=(
+        114,
+        114,
+        114,
+    )), size=(
+        640,
+        640,
+    ), type='Pad'),
+    dict(
+        img_scale=(
+            640,
+            640,
+        ),
+        max_cached_images=20,
+        pad_val=(
+            114,
+            114,
+            114,
+        ),
+        ratio_range=(
+            1.0,
+            1.0,
+        ),
+        type='CachedMixUp'),
+    dict(type='PackDetInputs'),
+]
+train_pipeline_stage2 = [
+    dict(backend_args=None, type='LoadImageFromFile'),
+    dict(type='LoadAnnotations', with_bbox=True),
+    dict(
+        keep_ratio=True,
+        ratio_range=(
+            0.1,
+            2.0,
+        ),
+        scale=(
+            640,
+            640,
+        ),
+        type='RandomResize'),
+    dict(crop_size=(
+        640,
+        640,
+    ), type='RandomCrop'),
+    dict(type='YOLOXHSVRandomAug'),
+    dict(prob=0.5, type='RandomFlip'),
+    dict(pad_val=dict(img=(
+        114,
+        114,
+        114,
+    )), size=(
+        640,
+        640,
+    ), type='Pad'),
+    dict(type='PackDetInputs'),
+]
+tta_model = dict(
+    tta_cfg=dict(max_per_img=100, nms=dict(iou_threshold=0.6, type='nms')),
+    type='DetTTAModel')
+tta_pipeline = [
+    dict(backend_args=None, type='LoadImageFromFile'),
+    dict(
+        transforms=[
+            [
+                dict(keep_ratio=True, scale=(
+                    640,
+                    640,
+                ), type='Resize'),
+                dict(keep_ratio=True, scale=(
+                    320,
+                    320,
+                ), type='Resize'),
+                dict(keep_ratio=True, scale=(
+                    960,
+                    960,
+                ), type='Resize'),
+            ],
+            [
+                dict(prob=1.0, type='RandomFlip'),
+                dict(prob=0.0, type='RandomFlip'),
+            ],
+            [
+                dict(
+                    pad_val=dict(img=(
+                        114,
+                        114,
+                        114,
+                    )),
+                    size=(
+                        960,
+                        960,
+                    ),
+                    type='Pad'),
+            ],
+            [
+                dict(type='LoadAnnotations', with_bbox=True),
+            ],
+            [
+                dict(
+                    meta_keys=(
+                        'img_id',
+                        'img_path',
+                        'ori_shape',
+                        'img_shape',
+                        'scale_factor',
+                        'flip',
+                        'flip_direction',
+                    ),
+                    type='PackDetInputs'),
+            ],
+        ],
+        type='TestTimeAug'),
+]
+val_cfg = dict(type='ValLoop')
+val_dataloader = dict(
+    batch_size=5,
+    dataset=dict(
+        ann_file=('/kfs2/projects/pvfleets24/repos/cv-dl-framework' +
+                  '/test/label_json.json'),
+        backend_args=None,
+        data_prefix=dict(
+            img='/kfs2/projects/pvfleets24/repos/cv-dl-framework/test/images/'
+        ),
+        data_root='/kfs2/projects/pvfleets24/repos/cv-dl-framework',
+        metainfo=dict(classes=('panel', )),
+        pipeline=[
+            dict(backend_args=None, type='LoadImageFromFile'),
+            dict(keep_ratio=True, scale=(
+                640,
+                640,
+            ), type='Resize'),
+            dict(
+                pad_val=dict(img=(
+                    114,
+                    114,
+                    114,
+                )),
+                size=(
+                    640,
+                    640,
+                ),
+                type='Pad'),
+            dict(type='LoadAnnotations', with_bbox=True),
+            dict(
+                meta_keys=(
+                    'img_id',
+                    'img_path',
+                    'ori_shape',
+                    'img_shape',
+                    'scale_factor',
+                ),
+                type='PackDetInputs'),
+        ],
+        test_mode=True,
+        type='CocoDataset'),
+    drop_last=False,
+    num_workers=10,
+    persistent_workers=True,
+    sampler=dict(shuffle=False, type='DefaultSampler'))
+val_evaluator = dict(
+    ann_file=('/kfs2/projects/pvfleets24/repos/cv-dl-framework' +
+              '/test/label_json.json'),
+    backend_args=None,
+    format_only=False,
+    metric='bbox',
+    proposal_nums=(
+        100,
+        1,
+        10,
+    ),
+    type='CocoMetric')
+vis_backends = [
+    dict(type='LocalVisBackend'),
+]
+visualizer = dict(
+    name='visualizer',
+    type='DetLocalVisualizer',
+    vis_backends=[
+        dict(
+            save_dir=('/kfs2/projects/pvfleets24/repos/cv-dl-framework/runs' +
+                      '/sol-searcher.v1i.coco-segmentation/' +
+                      '07_06_2025_03_44_01'),
+            type='LocalVisBackend'),
+    ])
+work_dir = ('/kfs2/projects/pvfleets24/repos/cv-dl-framework/runs' +
+            '/sol-searcher.v1i.coco-segmentation/07_06_2025_03_44_01')

sol_searcher_model.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2c71b0ecd523e78487444c19a8de0edf9748494473476cde48779b39a2693405
+size 791335897