if __name__ == '__main__':
# dataset = 'dataset-sample' # 0.5 GB download
dataset = 'dataset-medium' # 9.0 GB download
config = {
'name' : 'baseline-focal-fastai',
'dataset' : dataset,
}
wandb.init(config=config)
datasets.download_dataset(dataset)
# train the baseline model and save it in models folder
custom_training.train_model(dataset)
# use the train model to run inference on all test scenes
inference.run_inference(dataset)
# scores all the test images compared to the ground truth labels then
# send the scores (f1, precision, recall) and prediction images to wandb
score, predictions = scoring.score_predictions(dataset)
print(score)
wandb.log(score)
for f1, f2 in predictions:
wandb.save( f1 )
wandb.save( f2 )
from libs import inference_keras
from libs import scoring
import wandb
if __name__ == '__main__':
dataset = 'dataset-sample' # 0.5 GB download
#dataset = 'dataset-medium' # 9.0 GB download
config = {
'name' : 'baseline-keras',
'dataset' : dataset,
}
wandb.init(config=config)
datasets.download_dataset(dataset)
# train the model
model = models_keras.build_unet(encoder='resnet18')
training_keras.train_model(dataset, model)
# use the train model to run inference on all test scenes
inference_keras.run_inference(dataset, model=model, basedir=wandb.run.dir)
# scores all the test images compared to the ground truth labels then
# send the scores (f1, precision, recall) and prediction images to wandb
score, _ = scoring.score_predictions(dataset, basedir=wandb.run.dir)
print(score)
wandb.log(score)
custom_objects={'tf': tf},
compile=False)
model_vgg.summary()
dataset = 'dataset-medium'
config = {
'name': 'baseline-keras',
'dataset': dataset,
}
#wandb.init(config=config)
inference_keras.run_inference(dataset,
model=model_res,
basedir='predictions_resnet18')
score, _ = scoring.score_predictions(dataset, basedir='predictions_resnet18')
print(score)
inference_keras.run_inference(dataset,
model=model_vgg,
basedir='predictions_vgg16')
score, _ = scoring.score_predictions(dataset, basedir='predictions_vgg16')
print(score)
acc_res = []
acc_gmm = []
acc_vgg = []
acc = []
for predict in predict_ids: #or some list
img_res = f'./predictions_resnet18/{predict}-prediction.png'
img_vgg = f'./predictions_vgg16/{predict}-prediction.png'
img_gmm = Main.runcluster(dataset, predict, basedir='predictions_cluster')