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import os | |
import numpy as np | |
import pandas as pd | |
from PIL import Image | |
import matplotlib.pyplot as plt | |
from atoms_detection.image_preprocessing import dl_prepro_image | |
from utils.paths import PT_DATASET, FE_DATASET, IMG_PATH, PREPRO_VIS_PATH | |
def generate_prepro_plots(dataset_path: str, vis_folder: str): | |
if not os.path.exists(vis_folder): | |
os.makedirs(vis_folder) | |
df = pd.read_csv(dataset_path) | |
for image_name in df['Filename']: | |
image_filename = os.path.join(IMG_PATH, image_name) | |
img = Image.open(image_filename) | |
np_img = np.array(img).astype(np.float32) | |
np_prepro_img = dl_prepro_image(np_img) | |
plt.figure() | |
plt.axis('off') | |
plt.imshow(np_prepro_img) | |
vis_path = os.path.join(vis_folder, '{}.png'.format(os.path.splitext(image_name)[0])) | |
plt.savefig(vis_path, bbox_inches='tight', pad_inches=0.0) | |
plt.close() | |
if __name__ == "__main__": | |
generate_prepro_plots(PT_DATASET, os.path.join(PREPRO_VIS_PATH, 'Pt-Catalyst')) | |
generate_prepro_plots(FE_DATASET, os.path.join(PREPRO_VIS_PATH, 'Fe-Catalyst')) | |