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import argparse
import numpy as np
import matplotlib.pyplot as plt
from frame_field_learning import plot_utils
def get_args():
argparser = argparse.ArgumentParser(description=__doc__)
argparser.add_argument(
'-f', '--filepath',
required=True,
type=str,
help='Path to the .npy to plot the framefield from.')
argparser.add_argument(
'-o', '--out_filepath',
required=True,
type=str,
help='Path to save the image.')
args = argparser.parse_args()
return args
def save_plot_framefield(framefield, out_filepath):
# Setup plot
height = framefield.shape[0]
width = framefield.shape[1]
f, axis = plt.subplots(1, 1, figsize=(width // 10, height // 10))
# axis.imshow(im)
transparent_im = np.zeros((height, width, 4))
axis.imshow(transparent_im)
framefield_stride = 8
plot_utils.plot_framefield(axis, framefield, framefield_stride, alpha=1, width=2)
axis.autoscale(False)
axis.axis('equal')
axis.axis('off')
# f.tight_layout()
plt.subplots_adjust(left=0, right=1, top=1, bottom=0) # Plot without margins
plt.savefig(out_filepath, transparent=True)
plt.close()
# plt.show()
def main():
# --- Process args --- #
args = get_args()
# Read
framefield = np.load(args.filepath)
# Cut bbox
# bbox = [2700, 2300, 3200, 2900]
# framefield = framefield[bbox[0]:bbox[2], bbox[1]:bbox[3]]
save_plot_framefield(framefield, args.out_filepath)
if __name__ == '__main__':
main()
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