|
|
|
import sys |
|
from pathlib import Path |
|
sys.path.append(Path(__file__).parents[1].__str__()) |
|
from dronescapes_reader import MultiTaskDataset, dronescapes_task_types |
|
from pprint import pprint |
|
from torch.utils.data import DataLoader |
|
import random |
|
|
|
def main(): |
|
reader = MultiTaskDataset(sys.argv[1], handle_missing_data="fill_none", task_types=dronescapes_task_types, |
|
files_per_repr_overwrites={"hsv": "rgb"}) |
|
print(reader) |
|
|
|
print("== Shapes ==") |
|
pprint(reader.data_shape) |
|
|
|
print("== Random loaded item ==") |
|
rand_ix = random.randint(0, len(reader)) |
|
data, name, repr_names = reader[rand_ix] |
|
pprint({k: v for k, v in data.items()}) |
|
|
|
print("== Random loaded batch ==") |
|
batch_data, name, repr_names = reader[rand_ix: min(len(reader), rand_ix + 5)] |
|
pprint({k: v for k, v in batch_data.items()}) |
|
|
|
print("== Random loaded batch using torch DataLoader ==") |
|
loader = DataLoader(reader, collate_fn=reader.collate_fn, batch_size=5, shuffle=True) |
|
batch_data, name, repr_names = next(iter(loader)) |
|
pprint({k: v for k, v in batch_data.items()}) |
|
|
|
if __name__ == "__main__": |
|
main() |
|
|