def compute_score(gts, val_caps, train_imgids, val_imgids, i, j):
res = {}
for imgid in train_imgids:
res[imgid] = [val_caps[val_imgids[i]][j]]
scorer = Meteor()
score, scores = scorer.compute_score(gts, res, train_imgids)
#print(score)
#print(len(scores))
return np.array(scores)
def evaluate(ref, hyp):
with open(hyp, 'r') as r:
hypothesis = r.readlines()
res = {
k: [" ".join(v.strip().lower().split())]
for k, v in enumerate(hypothesis)
}
with open(ref, 'r') as r:
references = r.readlines()
gts = {k: [v.strip().lower()] for k, v in enumerate(references)}
meteor = Meteor()
score_Meteor = meteor.compute_score(gts, res)
print("Meteor: " + str(score_Meteor))
rouge = Rouge()
scores_Rouge = rouge.get_scores([i[0] for i in gts.values()],
[i[0] for i in res.values()],
avg=True)
print("Rouge: " + str(scores_Rouge))