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import pytorch_lightning as pl | |
from src.ss.det_models.model import POIDetection | |
from src.ss.datasets_signboard_detection.datamodule import POIDataModule | |
from src.ss.det_models.inference_signboard_detection import POIDetectionTask | |
def load_model(checkpoint_path): | |
model = POIDetection.load_from_checkpoint(checkpoint_path=checkpoint_path) | |
return model | |
def inference_signboard(image_path, checkpoint, score): | |
dm = POIDataModule(data_path=image_path, | |
seed=42) | |
dm.setup("predict") | |
model = load_model(checkpoint) | |
from src.ss.det_models.inference_signboard_detection import POIDetectionTask | |
task = POIDetectionTask(model, | |
data_path=image_path, | |
score=score) | |
# accelerator='gpu', devices=1 | |
trainer = pl.Trainer(gpus=1, | |
max_epochs=-1) | |
trainer.predict(task, datamodule=dm) | |
return task.output | |
class SignBoardDetector(): | |
def __init__(self, | |
checkpoint) -> None: | |
self.model = POIDetection.load_from_checkpoint( | |
checkpoint_path=checkpoint) | |
def inference_signboard(self, image, score): | |
dm = POIDataModule(data_path=image, | |
seed=42) | |
dm.setup("predict") | |
task = POIDetectionTask(self.model, | |
score=score) | |
trainer = pl.Trainer(gpus=1, | |
max_epochs=-1) | |
trainer.predict(task, datamodule=dm) | |
return task.output | |