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| import jieba | |
| from whoosh.qparser import QueryParser | |
| from PIL import Image | |
| from whoosh.index import open_dir | |
| from whoosh.analysis import Tokenizer, Token | |
| class ChineseTokenizer(Tokenizer): | |
| def __call__(self, value, positions=False, chars=False, | |
| keeporiginal=False, removestops=True, | |
| start_pos=0, start_char=0, mode='', **kwargs): | |
| t = Token(positions, chars, removestops=removestops, mode=mode, | |
| **kwargs) | |
| seglist = jieba.cut(value, cut_all=True) | |
| for w in seglist: | |
| t.original = t.text = w | |
| t.boost = 1.0 | |
| if positions: | |
| t.pos = start_pos + value.find(w) | |
| if chars: | |
| t.startchar = start_char + value.find(w) | |
| if chars and positions: | |
| t.endchar = start_char + value.find(w) + len(w) | |
| yield t | |
| def ChineseAnalyzer(): | |
| return ChineseTokenizer() | |
| def search(query, lang='CN', k=10): | |
| ix = open_dir('indexes') | |
| # Tokenize the query string and join tokens with OR operator | |
| if lang == 'CN': | |
| query_tokens = jieba.cut(query, cut_all=True) | |
| else: | |
| query_tokens = query.split() | |
| or_query = " OR ".join(query_tokens) | |
| parser = QueryParser("content", ix.schema) | |
| myquery = parser.parse(or_query) | |
| with ix.searcher() as searcher: | |
| results = searcher.search(myquery, limit=k) | |
| # Extract and return the file names and descriptions of the top-k hits | |
| results_list = [(hit['file_name'], hit['content'], hit.score) for hit in results] | |
| images = [] | |
| for result in results_list: | |
| print(result) | |
| image_name = result[0] | |
| base_name = image_name.split('_img')[0] | |
| image_full_path = 'images/' + base_name + '/' + image_name + '.png' # 这个代码就是构造图片路径的 | |
| img = Image.open(image_full_path) | |
| image_title = result[1].split('\n')[-1].split(':')[1] | |
| # img.show(title=image_title) | |
| images.append((img, image_title, result[2])) | |
| return images | |
| jieba.cut("") # 用于预加载中文分词词典，建议提前运行这段命令 | |
| # results = search("IF-428x接收端阈值") | |
| results = search("简化结构图") | |
| for result in results: | |
| print(result[1], result[2]) # result[0] 是图片的 PIL.Image 对象， result[1]是title，2是相似度打分 |