with tf.Session() as sess:
assert (captioner_ckpt is not None)
captioner_saver.restore(sess, captioner_ckpt)
used_ids = set()
json_dump = []
for i in itertools.count():
time_start = time.time()
try:
_ids, _target_seq, _image_id = sess.run(
[ids, target_seq, image_id])
except:
break
the_captions = recursive_ids_to_string(_ids[:, 0, :].tolist(),
vocab)
the_labels = recursive_ids_to_string(
_target_seq[:, :].tolist(), vocab)
the_image_ids = _image_id.tolist()
for j, x, y in zip(the_image_ids, the_captions, the_labels):
if not j in used_ids:
used_ids.add(j)
json_dump.append({"image_id": j, "caption": x})
print(
PRINT_STRING.format(
i, the_captions[0], the_labels[0],
BATCH_SIZE / (time.time() - time_start)))
print("Finishing evaluating.")
coco_get_metrics(json_dump, "ckpts/show_and_tell/",
get_train_annotations_file())
#model_insert = recursive_ids_to_string(_ids.tolist(), vocab)
#label_insert = recursive_ids_to_string(_next_id.tolist(), vocab)
current_caption = _caption.tolist()
model_insert = _ids.tolist()
label_insert = _next_id.tolist()
model_pointer = _model_pointer.tolist()
label_pointer = _label_pointer.tolist()
the_image_ids = _image_id.tolist()
for cap, mins, lins, mptr, lptr, iid in zip(
current_caption, model_insert, label_insert,
model_pointer, label_pointer, the_image_ids):
model_cap = cap.copy()
model_cap.insert(mptr, mins)
label_cap = cap.copy()
label_cap.insert(lptr, lins)
cap = recursive_ids_to_string(cap, vocab)
model_cap = recursive_ids_to_string(model_cap, vocab)
label_cap = recursive_ids_to_string(label_cap, vocab)
if not iid in used_ids:
used_ids.add(iid)
json_dump.append({
"image_id": iid,
"caption": model_cap
})
print(
PRINT_STRING.format(
BATCH_SIZE / (time.time() - time_start), i, cap,
model_cap, label_cap))
print("Finishing evaluating.")
coco_get_metrics(json_dump, "ckpts/show_and_tell/",
