def non_interactive_demo(model, args):
renderer = create_renderer()
show_window = not args.no_show
for rec in tqdm(model.images_list):
log.info("Starting inference for %s", rec['img_name'])
image = rec['img']
distribution, targets = model.infer_sync(image)
prob = calculate_probability(distribution)
log.info("Confidence score is %s", prob)
if prob >= args.conf_thresh ** len(distribution):
phrase = model.vocab.construct_phrase(targets)
if args.output_file:
with open(args.output_file, 'a') as output_file:
output_file.write(rec['img_name'] + '\t' + phrase + '\n')
else:
print("\n\tImage name: {}\n\tFormula: {}\n".format(rec['img_name'], phrase))
if renderer is not None:
rendered_formula, _ = renderer.render(phrase)
if rendered_formula is not None and show_window:
cv.imshow("Predicted formula", rendered_formula)
cv.waitKey(0)
else:
log.info("Confidence score is low. The formula was not recognized.")
if args.perf_counts:
log.info("Encoder performance statistics")
print_stats(model.exec_net_encoder)
log.info("Decoder performance statistics")
print_stats(model.exec_net_decoder)
def __init__(self, input_model_shape, resolution):
self.resolution = resolution
self._tgt_shape = input_model_shape
self.start_point, self.end_point = self._create_input_window()
self._prev_rendered_formula = None
self._prev_formula_img = None
self._latex_h = 0
self._renderer = create_renderer()
def non_interactive_demo(model, args):
renderer = create_renderer()
show_window = not args.no_show
for rec in tqdm(model.images_list):
image = rec.img
distribution, targets = model.infer_sync(image)
prob = calculate_probability(distribution)
log.info("Confidence score is {}".format(prob))
if prob >= args.conf_thresh**len(distribution):
phrase = model.vocab.construct_phrase(targets)
if args.output_file:
with open(args.output_file, 'a') as output_file:
output_file.write(rec.img_name + '\t' + phrase + '\n')
else:
print("\n\tImage name: {}\n\tFormula: {}\n".format(
rec.img_name, phrase))
if renderer is not None:
rendered_formula, _ = renderer.render(phrase)
if rendered_formula is not None and show_window:
cv.imshow("Predicted formula", rendered_formula)
cv.waitKey(0)
else:
log.info(
"Confidence score is low. The formula was not recognized.")