diff --git a/app.py b/app.py index 432f138439f9ab13ce995262bfda465375a0c023..26de1e6bbc1e87fbab7d828868ca58503c89268a 100644 --- a/app.py +++ b/app.py @@ -81,7 +81,7 @@ with gr.Blocks(css='style.css') as demo: label='Model Type') with gr.Row(): model_name = gr.Dropdown(([ - 'Faster R-CNN (R-50-FPN']), + 'Faster R-CNN (R-50-FPN)']), value=DEFAULT_MODEL_NAME, label='Model') with gr.Row(): diff --git a/configs/_base_/faster-rcnn_r50_fpn_1x_coco.py b/configs/_base_/faster-rcnn_r50_fpn_1x_coco.py index 48a08558b9918c1ca1fd836530e82ae5b88eb8a3..5ce05dab5601888cbc61e8c943861ec8c3ed366c 100644 --- a/configs/_base_/faster-rcnn_r50_fpn_1x_coco.py +++ b/configs/_base_/faster-rcnn_r50_fpn_1x_coco.py @@ -166,4 +166,73 @@ test_pipeline = [ ]) ] -evaluation = dict(interval=1, metric='bbox') \ No newline at end of file +evaluation = dict(interval=1, metric='bbox') + +data_root = 'data/' # dataset root + +train_batch_size_per_gpu = 16 +train_num_workers = 1 + +max_epochs = 105 +base_lr = 0.00001 + + +metainfo = { + 'classes': ('orgaquant', ), + 'palette': [ + (220, 20, 60), + ] +} + +train_dataloader = dict( + batch_size=train_batch_size_per_gpu, + num_workers=train_num_workers, + dataset=dict( + data_root=data_root, + metainfo=metainfo, + data_prefix=dict(img='train/'), + ann_file='train.json')) + +val_dataloader = dict( + dataset=dict( + data_root=data_root, + metainfo=metainfo, + data_prefix=dict(img='val/'), + ann_file='val.json')) + +test_dataloader = val_dataloader + +val_evaluator = dict(ann_file=data_root + 'val.json') + +test_evaluator = val_evaluator + +model = dict( + roi_head=dict( + bbox_head=dict(num_classes=1))) + + + +# optimizer +optim_wrapper = dict( + _delete_=True, + type='OptimWrapper', + optimizer=dict(type='AdamW', lr=base_lr, weight_decay=0.05), + paramwise_cfg=dict( + norm_decay_mult=0, bias_decay_mult=0, bypass_duplicate=True)) + +default_hooks = dict( + checkpoint=dict( + interval=5, + max_keep_ckpts=2, # only keep latest 2 checkpoints + save_best='auto' + ), + logger=dict(type='LoggerHook', interval=5)) + + +# load COCO pre-trained weight + +# load_from = './work_dirs/faster-rcnn_r50_fpn_organoid/best_coco_bbox_mAP_epoch_12.pth' + + +train_cfg = dict(type='EpochBasedTrainLoop', max_epochs=max_epochs, val_interval=1) +visualizer = dict(vis_backends=[dict(type='LocalVisBackend'),dict(type='TensorboardVisBackend')]) diff --git a/configs/faster-rcnn_r50_fpn_organoid_orgaquant.py b/configs/_base_/faster-rcnn_r50_fpn_organoid_orgaquant.py similarity index 97% rename from configs/faster-rcnn_r50_fpn_organoid_orgaquant.py rename to configs/_base_/faster-rcnn_r50_fpn_organoid_orgaquant.py index 6260fe6b1115107681c56268cc32b3e2922f37fb..66053137f77e95638362a37bdf90814ef909857b 100644 --- a/configs/faster-rcnn_r50_fpn_organoid_orgaquant.py +++ b/configs/_base_/faster-rcnn_r50_fpn_organoid_orgaquant.py @@ -2,7 +2,7 @@ # Inherit and overwrite part of the config based on this config _base_ = './faster-rcnn_r50_fpn_1x_coco.py' -data_root = 'data/' # dataset root +data_root = 'orgaquant_dataset/' # dataset root train_batch_size_per_gpu = 16 train_num_workers = 1 diff --git a/model.py b/model.py index bde16e0721bbdfbeb248ce324b2537cc446a396d..52b7583fdfa913bb201c3ba608b2d401ab138ca0 100644 --- a/model.py +++ b/model.py @@ -23,7 +23,7 @@ class Model: def _load_model(self, name: str) -> nn.Module: - return init_detector('configs/_base_/faster-rcnn_r50_fpn_1x_coco.py', 'models/orgaquant_pretrained.pth' , device=self.device) + return init_detector('configs/_base_/faster-rcnn_r50_organoid_orgaquant.py', 'models/orgaquant_pretrained.pth' , device=self.device) def set_model(self, name: str) -> None: if name == self.model_name: diff --git a/orgaquant_dataset/test.json b/orgaquant_dataset/test.json new file mode 100644 index 0000000000000000000000000000000000000000..e678a02e54e27b2ece581e6208f0162855a3c7b4 --- /dev/null +++ b/orgaquant_dataset/test.json @@ -0,0 +1 @@ +{"images": [{"id": 0, "file_name": "Subset_1_450x450_001.jpg", "height": 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