| 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.') |
| |
