pycocoevalcap_caption_metrics_bleu_meteor_rouge_cider_spice.py

1from pycocotools.coco import COCO
2from pycocoevalcap.eval import COCOEvalCap
3
4# Define the paths to the ground truth (annFile) and candidate results (resFile)
5# In a real scenario, these would be paths to your JSON files
6annFile = 'captions_val2014.json'
7resFile = 'captions_val2014_fake_results.json'
8
9# Initialize COCO ground truth api
10coco = COCO(annFile)
11
12# Initialize COCO result api
13cocoRes = coco.loadRes(resFile)
14
15# Create cocoEval object by taking coco and cocoRes
16cocoEval = COCOEvalCap(coco, cocoRes)
17
18# Evaluate on a subset of images if desired by setting params
19# cocoEval.params['image_id'] = cocoRes.getImgIds()
20
21# Run the evaluation
22cocoEval.evaluate()
23
24# Print output evaluation scores
25for metric, score in cocoEval.eval.items():
26    print(f'{metric}: {score:.3f}')