Emergent-NCA-Sequences-5M / sample_usage.py
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import argparse
import os
import numpy as np
def iter_transitions(data_dir: str):
shard_files = sorted(
f for f in os.listdir(data_dir) if f.startswith("shard_") and f.endswith(".npz")
)
for name in shard_files:
path = os.path.join(data_dir, name)
data = np.load(path, allow_pickle=True)
frames_list = data["frames"]
w_list = data["w"]
h_list = data["h"]
for i in range(len(frames_list)):
frames = frames_list[i]
w = int(w_list[i])
h = int(h_list[i])
for t in range(frames.shape[0] - 1):
yield w, h, frames[t], frames[t + 1]
def main() -> None:
parser = argparse.ArgumentParser()
parser.add_argument("--data", default="./nca_dataset_set2/data")
parser.add_argument("--limit", type=int, default=5)
args = parser.parse_args()
for i, (w, h, frame_t, frame_t1) in enumerate(iter_transitions(args.data), start=1):
print(f"sample={i} w={w} h={h} unique_t={np.unique(frame_t).size}")
if i >= args.limit:
break
if __name__ == "__main__":
main()