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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)
# Detect Failure
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.')
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