print(
f'Starting postprocessing of {batch_name} with parameter set {param_set_name}...'
)
for f in os.listdir(path_to_test_preds):
if count == config.POST_MAX_NUM_IMAGES_TOPROCESS:
break
ext = os.path.splitext(f)[1]
if ext.lower() != '.png':
continue
pred_img = Image.open(os.path.join(path_to_test_preds, f))
pred_arr = util.to_array(pred_img)
id = get_id_from_filename(f)
img = Image.open(path_to_test_imgs + f'test_{id}.png')
img_arr = np.asarray(img)
if config.POST_DO_CRFPROCESSING:
print(f' processing {f}...')
processed_pred = post.crf(img_arr, pred_arr)
# add to submission
if config.POST_WRITE_SUBMISSION:
submission.add(prediction=processed_pred, img_id=id)
else:
processed_img = util.to_image(processed_pred)
processed_img.save(out_dir + f'post_{id}.png')
count += 1
print(f'Postprocessing finished (processed {count} predictions)')
if config.POST_WRITE_SUBMISSION:
submission.write()
