print('\nNormalising csvs...')
for index, file in enumerate(data_files):
file_path = os.path.join(img_dir, file)
img, file_name = io.csv_in(file_path=file_path)
_, img_no = file_name.split('_')
io.png_out(image_data=img,
file_name=file_name,
dir_name=img_dir,
image_title=f'Image: {img_no}',
out_name=f'{file_name}.png',
plot_show=False)
norm_img = dp.pwr_norm(image_data=img,
file_name=file_name,
norm_power=norm_power,
dir_name=img_dir)
io.png_out(image_data=norm_img,
file_name=file_name,
dir_name=img_dir,
image_title=f'Normalised image: {img_no}',
out_name=f'corrected_{file_name}.png',
plot_show=False)
io.array_out(array_name=norm_img,
file_name=f'corrected_{file_name}',
dir_name=os.path.join(img_dir, 'corrected_imgs'))
io.update_progress(index / len(data_files))
main_dir = io.config_dir_path()
exp_settings = io.exp_in(main_dir)
print(f'Experiment Settings:\n {exp_settings}\n')
for hs_img in exp_settings['hs_imgs']:
img_dir = os.path.join(main_dir, hs_img)
if not os.path.isdir(img_dir):
continue
corrected_img_dir = os.path.join(img_dir, 'corrected_imgs')
data_files = io.extract_files(dir_name=corrected_img_dir,
file_string='corrected_img_')
print(len(data_files))
data_cube = []
print('\nBuilding data cube...')
for index, file in enumerate(data_files):
file_path = os.path.join(corrected_img_dir, file)
corrected_img, file_name = io.array_in(file_path, mode='r')
data_cube.append(corrected_img)
io.update_progress(index / len(data_files))
print('\nSaving data cube...approximately 1min per 100 imgs')
io.array_out(array_name=data_cube,
file_name=f'{hs_img}_datacube',
dir_name=main_dir)
norm_img = dp.pwr_norm(image_data=img,
file_name=file_name,
norm_power=norm_power,
dir_name=img_dir)
if norm_save:
io.png_out(image_data=norm_img,
file_name=file_name,
dir_name=img_dir,
image_title=f'Normalised image: {img_no}',
out_name=f'corrected_{file_name}.png',
plot_show=False)
io.array_out(array_name=norm_img,
file_name=f'corrected_{file_name}',
dir_name=os.path.join(img_dir, 'corrected_imgs'))
io.update_progress(index / len(data_files))
if datacube:
data_files = io.extract_files(dir_name=corrected_img_dir,
file_string='corrected_img_')
data_cube = []
print(f'\nBuilding data cube for {hs_img}...')
for index, file in enumerate(data_files):
file_path = os.path.join(corrected_img_dir, file)
corrected_img, file_name = io.array_in(file_path, mode='r')
data_cube.append(corrected_img)