CODEWITHSUNDEEP
deep-learningpytorchdetectron
Ajay Pyatha
Ajay Pyatha

Reputation: 164

How to save and load models of custom dataset in Detectron2?

I have tried to save and load the model using: All keys are mapped but there is no prediction in output #1

from detectron2.modeling import build_model
model = build_model(cfg)
torch.save(model.state_dict(), 'checkpoint.pth') 
model.load_state_dict(torch.load(checkpoint_path,map_location='cpu'))

I also tried doing it using the official doc but can't understand the input format part

from detectron2.checkpoint import DetectionCheckpointer
DetectionCheckpointer(model).load(file_path_or_url)  # load a file, usually from cfg.MODEL.WEIGHTS
checkpointer = DetectionCheckpointer(model, save_dir="output")
checkpointer.save("model_999")  # save to output/model_999.pth

Upvotes: 5

Views: 7251

Answers (1)

Ali Mustofa
Ali Mustofa

Reputation: 185

cfg = get_cfg()
cfg.merge_from_file(model_zoo.get_config_file('COCO-Detection/faster_rcnn_R_101_FPN_3x.yaml'))
cfg.MODEL.ROI_HEADS.SCORE_THRESH_TEST = 0.5 # Set threshold for this model
cfg.MODEL.WEIGHTS = '/content/model_final.pth' # Set path model .pth
cfg.MODEL.ROI_HEADS.NUM_CLASSES = 1
predictor = DefaultPredictor(cfg)

My code to load custom model works.

Upvotes: 9

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