mutli_label.py

# Load train data from the train directory
datamodule = ImageClassificationData.from_folders(train_folder="./train")

# Build the model
model = ImageClassifier(
    backbone="resnet200d",
    num_classes=datamodule.num_classes,
    multi_label=True,
    metrics=F1(num_classes=datamodule.num_classes),
    serializer=Labels(genres, multi_label=True, threshold=0.25),
)

# Create the trainer.
trainer = flash.Trainer()

# Train the model
trainer.finetune(model, datamodule=datamodule, strategy="freeze")

# Predict what's on a few images!
prediction = model.predict(["data/movie_posters/predict/tt0085318.jpg"])