Add metrics to object detection example

🤗Transformers
1

Hello everybody,

im new with huggingface and wanted to try out the object detection. So i ran the transformers object detection example from the huggingface docs (this one here: Object detection) and wanted to add some metrics while training the model. Everytime i get the following error:

TypeError: Can’t pad the values of type <class ‘transformers.image_processing_utils.BatchFeature’>, only of nested list/tuple/dicts of tensors.

I create a eval_dataset like this:

cppe5["test"] = cppe5["test"].with_transform(transform_aug_ann)

and add it to the trainer:

metric = evaluate.load("accuracy")

def compute_metrics(eval_pred):
    print("here")
    logits, labels = eval_pred
    predictions = np.argmax(logits, axis=-1)
    return metric.compute(predictions=predictions, references=labels)

trainer = Trainer(
    model=model,
    args=training_args,
    data_collator=collate_fn,
    train_dataset=splitted_ds_encoded["train"],
    eval_dataset=splitted_ds_encoded['test'],
    tokenizer=image_processor,
    compute_metrics=compute_metrics,
)

Maybe someone here can help me?

Thanks in advance. Greetings Christoph