add simple word2vec

@@ -55,7 +55,7 @@ solver:
     # name: 'CrossEntropyLoss'
     args:
       reduction: "mean"
-      alpha: 0.95
+      alpha: 0.8
 
   logger:
     log_root: '/Users/zhouweiqi/Downloads/test/logs'

@@ -7,34 +7,55 @@ import uuid
 import cv2
 import pandas as pd
 from tools import get_file_paths, load_json
+from word2vec import simple_word2vec
 
 
 def clean_go_res(go_res_dir):
-    max_seq_count = None
-    seq_sum = 0
-    file_count = 0
-
     go_res_json_paths = get_file_paths(go_res_dir, ['.json', ])
     for go_res_json_path in go_res_json_paths:
         print('Info: start {0}'.format(go_res_json_path))
     
-        remove_key_set = set()
-        go_res = load_json(go_res_json_path)
-        for key, (_, text) in go_res.items():
+        remove_idx_set = set()
+        src_go_res_list = load_json(go_res_json_path)
+        for idx, (_, text) in enumerate(src_go_res_list):
             if text.strip() == '':
-                remove_key_set.add(key)
+                remove_idx_set.add(idx)
                 print(text)
         
-        if len(remove_key_set) > 0:
-            for del_key in remove_key_set:
-                del go_res[del_key]
+        if len(remove_idx_set) > 0:
+            for del_idx in remove_idx_set:
+                del src_go_res_list[del_idx]
         
-        go_res_list = sorted(list(go_res.values()), key=lambda x: (x[0][1], x[0][0]), reverse=False)
+        go_res_list = sorted(src_go_res_list, key=lambda x: (x[0][1], x[0][0]), reverse=False)
 
         with open(go_res_json_path, 'w') as fp:
             json.dump(go_res_list, fp)
             print('Rerewirte {0}'.format(go_res_json_path))
 
+
+def char_length_statistics(go_res_dir):
+    max_char_length = None
+    target_file_name = None
+    go_res_json_paths = get_file_paths(go_res_dir, ['.json', ])
+    for go_res_json_path in go_res_json_paths:
+        print('Info: start {0}'.format(go_res_json_path))
+        src_go_res_list = load_json(go_res_json_path)
+        for _, text in src_go_res_list:
+            if max_char_length is None or len(text.strip()) > max_char_length:
+                max_char_length = len(text.strip())
+                target_file_name = go_res_json_path
+    return max_char_length, target_file_name
+
+def bbox_statistics(go_res_dir):
+    max_seq_count = None
+    seq_sum = 0
+    file_count = 0
+
+    go_res_json_paths = get_file_paths(go_res_dir, ['.json', ])
+    for go_res_json_path in go_res_json_paths:
+        print('Info: start {0}'.format(go_res_json_path)) 
+
+        go_res_list = load_json(go_res_json_path)
         seq_sum += len(go_res_list)
         file_count += 1
         if max_seq_count is None or len(go_res_list) > max_seq_count:
@@ -168,21 +189,35 @@ def build_dataset(img_dir, go_res_dir, label_dir, top_text_list, skip_list, save
         y_true = list()
         for i in range(160):
             if i >= valid_lens:
-                X.append([0., 0., 0., 0., 0., 0., 0., 0., 0.])
+                X.append([0. for _ in range(14)])
                 y_true.append([0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
+
             elif i in top_text_idx_set:
-                (x0, y0, x1, y1, x2, y2, x3, y3), _ = go_res_list[i]
-                X.append([1., x0/w, y0/h, x1/w, y1/h, x2/w, y2/h, x3/w, y3/h])
+                (x0, y0, x1, y1, x2, y2, x3, y3), text = go_res_list[i]
+                feature_vec = [1.]
+                feature_vec.extend(simple_word2vec(text))
+                feature_vec.extend([x0/w, y0/h, x1/w, y1/h, x2/w, y2/h, x3/w, y3/h])
+                X.append(feature_vec)
+
                 y_true.append([0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
+
             elif i in label_idx_dict:
-                (x0, y0, x1, y1, x2, y2, x3, y3), _ = go_res_list[i]
-                X.append([0., x0/w, y0/h, x1/w, y1/h, x2/w, y2/h, x3/w, y3/h])
+                (x0, y0, x1, y1, x2, y2, x3, y3), text = go_res_list[i]
+                feature_vec = [0.]
+                feature_vec.extend(simple_word2vec(text))
+                feature_vec.extend([x0/w, y0/h, x1/w, y1/h, x2/w, y2/h, x3/w, y3/h])
+                X.append(feature_vec)
+
                 base_label_list = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
                 base_label_list[label_idx_dict[i]] = 1
                 y_true.append(base_label_list)
             else:
-                (x0, y0, x1, y1, x2, y2, x3, y3), _ = go_res_list[i]
-                X.append([0., x0/w, y0/h, x1/w, y1/h, x2/w, y2/h, x3/w, y3/h]) 
+                (x0, y0, x1, y1, x2, y2, x3, y3), text = go_res_list[i]
+                feature_vec = [0.]
+                feature_vec.extend(simple_word2vec(text))
+                feature_vec.extend([x0/w, y0/h, x1/w, y1/h, x2/w, y2/h, x3/w, y3/h])
+                X.append(feature_vec)
+
                 y_true.append([0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
 
         all_data = [X, y_true, valid_lens]
@@ -222,11 +257,15 @@ if __name__ == '__main__':
     valid_dataset_dir = os.path.join(dataset_save_dir, 'valid')
     valid_anno_file_path = os.path.join(dataset_save_dir, 'valid.csv')
 
-    # max_seq_lens, seq_lens_mean, max_seq_file_name = clean_go_res(go_dir)
+    # max_seq_lens, seq_lens_mean, max_seq_file_name = bbox_statistics(go_dir)
     # print(max_seq_lens) # 152
-    # print(max_seq_file_name) # CH-B101805176_page_2_img_0.json
+    # print(max_seq_file_name) # train/CH-B101805176_page_2_img_0.json
     # print(seq_lens_mean) # 92
 
+    # max_char_lens, target_file_name = char_length_statistics(go_dir)
+    # print(max_char_lens) # 72
+    # print(target_file_name) # train/CH-B103053828-4.json
+
     # top_text_list = text_statistics(go_dir)
     # for t in top_text_list:
     #     print(t)
@@ -288,4 +327,6 @@ if __name__ == '__main__':
     build_dataset(valid_image_path, valid_go_path, valid_label_path, filter_from_top_text_list, skip_list_valid, valid_dataset_dir)
     build_anno_file(valid_dataset_dir, valid_anno_file_path)
 
+    # print(simple_word2vec(' fd2jk接口 额24；叁‘，。测ADF壹试！¥？ '))
+
     

+import re
+# from gensim.models import word2vec
+
+def simple_word2vec(text):
+    clean_text = text.strip()
+    text_len = len(clean_text)
+
+    digit_num = 0
+    en_num = 0
+    cn_num = 0
+    space_num = 0
+    other_num = 0
+    for char in clean_text:
+        if char.isdigit():
+            digit_num += 1
+        elif re.match(r'[A-Za-z]', char):
+            en_num += 1
+        elif char.isspace():
+            space_num += 1
+        elif re.match(r'[\u4e00-\u9fa5]', char):
+            cn_num += 1
+        else:
+            other_num += 1
+    
+    vec = [text_len/100,
+           cn_num/text_len,
+           en_num/text_len,
+           digit_num/text_len,
+           # space_num/text_len,
+           other_num/text_len,
+           ]
+
+    # print(text)
+    # print(clean_text)
+    # print('-------------')
+    # print(en_num)
+    # print(cn_num)
+    # print(digit_num)
+    # print(space_num)
+    # print(other_num)
+    # print('-------------')
+
+    return vec
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