Datasets:
File size: 1,799 Bytes
27ecb57 6c9d7cd 27ecb57 6c9d7cd 27ecb57 c6136d8 27ecb57 c6136d8 27ecb57 c6136d8 27ecb57 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 |
from datasets import load_dataset, DatasetDict
import polars as pl
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
from scipy.io import loadmat
def draw_animation(id, rgb, depth, radar):
fig, ax = plt.subplots(1, 3, figsize=(15, 5))
fig.suptitle(f"ID: {id}")
def update(frame):
ax[0].clear()
ax[0].set_title("Depth")
ax[0].imshow(depth[frame])
ax[1].clear()
ax[1].set_title("RGB")
ax[1].imshow(rgb[frame])
radar_data = radar[frame]["spec_db_slice"][::-1]
radar_data = (radar_data - radar_data.min()) / (
radar_data.max() - radar_data.min()
)
ax[2].clear()
ax[2].set_title("Radar")
ax[2].imshow(radar_data, aspect="auto", cmap="jet")
ani = FuncAnimation(fig, update, frames=len(depth), interval=15)
plt.show()
if __name__ == "__main__":
datasets = load_dataset("parquet", data_files="./train.parquet")
df_polars = datasets["train"].to_polars()
ids = df_polars["id"].unique().to_list()
for id in ids:
frames = df_polars.filter(
pl.col("id").eq(id)
& pl.col("selected_range_bin").eq(76)
& pl.col("sub_index_frame").eq(1)
).sort("index_frame")
print(
frames.select(
"file_path_radar",
"file_path_depth",
"file_path_rgb",
"index_frame",
"id",
)
)
rgb = [np.load(f) for f in frames["file_path_rgb"].to_list()]
depth = [np.load(f) for f in frames["file_path_depth"].to_list()]
radar = [loadmat(f) for f in frames["file_path_radar"].to_list()]
draw_animation(id, rgb, depth, radar)
break
|