| | import sys |
| | from vlmeval import * |
| | from vlmeval.dataset import SUPPORTED_DATASETS |
| | FAIL_MSG = 'Failed to obtain answer via API.' |
| |
|
| | root = sys.argv[1] |
| | if root[-1] in '/\\': |
| | root = root[:-1] |
| |
|
| | model_name = root.split('/')[-1] |
| |
|
| | for d in SUPPORTED_DATASETS: |
| | fname = f'{model_name}_{d}.xlsx' |
| | pth = osp.join(root, fname) |
| | if osp.exists(pth): |
| | data = load(pth) |
| | |
| | assert 'prediction' in data |
| | data['prediction'] = [str(x) for x in data['prediction']] |
| | fail = [FAIL_MSG in x for x in data['prediction']] |
| | if sum(fail): |
| | nfail = sum(fail) |
| | ntot = len(fail) |
| | print(f'Model {model_name} x Dataset {d}: {nfail} out of {ntot} failed. {nfail / ntot * 100: .2f}%. ') |
| |
|
| | eval_files = ls(root, match=f'{model_name}_{d}_') |
| | eval_files = [x for x in eval_files if listinstr([f'{d}_openai', f'{d}_gpt'], x) and x.endswith('.xlsx')] |
| |
|
| | if len(eval_files) == 0: |
| | print(f'Model {model_name} x Dataset {d} openai missing') |
| | continue |
| | |
| | assert len(eval_files) == 1 |
| | eval_file = eval_files[0] |
| | data = load(eval_file) |
| | |
| | if 'MMVet' in d: |
| | bad = [x for x in data['log'] if 'All 5 retries failed.' in str(x)] |
| | if len(bad): |
| | print(f'Model {model_name} x Dataset {d} Evaluation: {len(bad)} out of {len(data)} failed.') |
| | elif 'MathVista' in d: |
| | bad = [x for x in data['res'] if FAIL_MSG in str(x)] |
| | if len(bad): |
| | print(f'Model {model_name} x Dataset {d} Evaluation: {len(bad)} out of {len(data)} failed.') |
| | |
| | elif d == 'LLaVABench': |
| | sub = data[data['gpt4_score'] == -1] |
| | sub = sub[sub['gpt4_score'] == -1] |
| | if len(sub): |
| | print(f'Model {model_name} x Dataset {d} Evaluation: {len(sub)} out of {len(data)} failed.') |
| | else: |
| | bad = [x for x in data['log'] if FAIL_MSG in str(x)] |
| | if len(bad): |
| | print(f'Model {model_name} x Dataset {d} Evaluation: {len(bad)} out of {len(data)} failed.') |
| | |
