Add eval_mm dir

eval_mm/vqaeval/eval_utils/cal_metric.py

@@ -0,0 +1,40 @@
+import json
+import glob
+import re
+
+def has_word(sentence, word):
+    pattern = r"\b" + re.escape(word) + r"\b"
+    match = re.search(pattern, sentence)
+    if match:
+        return True
+    else:
+        return False
+def remove_special_chars(s):
+    pattern = r"[^a-zA-Z0-9\s]"
+    s = re.sub(pattern, "", s)
+    return s
+
+for model in glob.glob('./answer_save/*'):
+    print(model, ':')
+    result_list = sorted(glob.glob(f'{model}/*.json'))
+    for task_result_path in result_list:
+        taskname = task_result_path.split('/')[-1]
+        taskname = taskname.split('.')[0]
+        if taskname not in ['IIIT5K', 'svt', 'IC13_857', 'IC15_1811', 'svtp', 'ct80',
+                            'cocotext', 'ctw', 'totaltext', 'HOST']:
+            continue
+
+        correct = 0
+        num = 0
+        with open(task_result_path, 'r') as f:
+            dict = json.load(f)[:100]
+            for i in range(len(dict)):
+                gt_answers = dict[i]['gt_answers']
+                answer = dict[i]['answer']
+                gt_answers = remove_special_chars(gt_answers).lower()
+                answer = remove_special_chars(answer).lower()
+                if has_word(answer, gt_answers):
+                    correct+=1
+                num+=1
+        print(f'{taskname:10s}:{float(correct)/num*100:.2f}')
+    print('=' * 32)