Update vi_backbones.py

vi_backbones.py

@@ -1,6 +1,5 @@
 import os
 import re
-# import hashlib
 import requests
 import datasets
 from bs4 import BeautifulSoup
@@ -17,12 +16,9 @@ class vi_backbones(datasets.GeneratorBasedBuilder):
             features=datasets.Features(
                 {
                     "ver": datasets.Value("string"),
-                    "name": datasets.Value("string"),
                     "type": datasets.Value("string"),
                     "input_size": datasets.Value("int16"),
-                    # "output_size": datasets.Value("int64"),
                     "url": datasets.Value("string"),
-                    # "md5": datasets.Value("string"),
                 }
             ),
             supervised_keys=("ver", "type"),
@@ -30,27 +26,6 @@ class vi_backbones(datasets.GeneratorBasedBuilder):
             license="mit"
         )
 
-    # def _get_file_md5(self, url):
-    #     """
-    #     Calculate the MD5 hash value of a file using its URL
-
-    #     :param url: the URL address of the file
-    #     :return: the MD5 hash value in string format
-    #     """
-    #     try:
-    #         response = requests.get(url, stream=True)
-    #         if response.status_code == 200:
-    #             md5obj = hashlib.md5()
-    #             for chunk in response.iter_content(chunk_size=1024*1024):
-    #                 md5obj.update(chunk)
-    #             return md5obj.hexdigest()
-    #         else:
-    #             raise ValueError(
-    #                 f"Error downloading file from {url}. Status code: {response.status_code}")
-    #     except Exception as e:
-    #         raise ValueError(
-    #             f"Error calculating MD5 of file at {url}: {str(e)}")
-
     def _parse_url(self, url):
         response = requests.get(url)
         html = response.text
@@ -58,31 +33,25 @@ class vi_backbones(datasets.GeneratorBasedBuilder):
 
     def _special_type(self, m_ver):
         m_type = re.search('[a-zA-Z]+', m_ver).group(0)
-        m_name = m_ver
 
         if m_type == 'wide' or m_type == 'resnext':
-            m_type = 'resnet'
+            return 'resnet'
 
         elif m_type == 'swin':
-            m_type = 'swin_transformer'
+            return 'swin_transformer'
 
         elif m_type == 'inception':
-            m_type = 'googlenet'
-
-        pattern = r'_v\d+_'
-        if re.search(pattern, m_name):
-            m_name = re.sub(pattern, '_', m_name)
+            return 'googlenet'
 
-        return m_type, m_name
+        return m_type
 
-    def _info_on_dataset(self, m_ver, m_name, m_type, in1k_span):
+    def _info_on_dataset(self, m_ver, m_type, in1k_span):
         url_span = in1k_span.find_next_sibling('span', {'class': 's2'})
         size_span = url_span.find_next_sibling('span', {'class': 'mi'})
         m_url = str(url_span.text[1:-1])
         input_size = int(size_span.text)
         m_dict = {
             'ver': m_ver,
-            'name': m_name,
             'type': m_type,
             'input_size': input_size,
             'url': m_url
@@ -99,7 +68,9 @@ class vi_backbones(datasets.GeneratorBasedBuilder):
             name = str(li.text)
             if name.__contains__('torchvision.models.') and len(name.split('.')) == 3:
 
-                if name.__contains__('_api') or name.__contains__('feature_extraction') or name.__contains__('maxvit'):
+                if name.__contains__('_api') or \
+                    name.__contains__('feature_extraction') or \
+                        name.__contains__('maxvit'):
                     continue
 
                 href = li.find('a').get('href')
@@ -110,7 +81,11 @@ class vi_backbones(datasets.GeneratorBasedBuilder):
                     div_id = str(div['id'])
                     if div_id.__contains__('_Weights'):
                         m_ver = div_id.split('_Weight')[0].lower()
-                        m_type, m_name = self._special_type(m_ver)
+
+                        if m_ver.__contains__('swin_v2_'):
+                            continue
+
+                        m_type = self._special_type(m_ver)
 
                         in1k_v1_span = div.find(
                             name='span',
@@ -123,7 +98,6 @@ class vi_backbones(datasets.GeneratorBasedBuilder):
 
                         m_dict, size_span = self._info_on_dataset(
                             m_ver,
-                            m_name,
                             m_type,
                             in1k_v1_span
                         )
@@ -138,7 +112,6 @@ class vi_backbones(datasets.GeneratorBasedBuilder):
                         if in1k_v2_span != None:
                             m_dict, _ = self._info_on_dataset(
                                 m_ver,
-                                m_name,
                                 m_type,
                                 in1k_v2_span
                             )
@@ -168,10 +141,7 @@ class vi_backbones(datasets.GeneratorBasedBuilder):
         for i, model in enumerate(subset):
             yield i, {
                 "ver": model['ver'],
-                "name": model['name'],
                 "type": model['type'],
                 "input_size": model['input_size'],
-                # "output_size": 1234,
                 "url": model['url'],
-                # "md5": self._get_file_md5(model['url']),
             }