4-2-image-labeling

data/reviews.json

@@ -0,0 +1,7 @@
+[
+  {"id": 1, "text": "外卖小哥送得超快，餐盒还是热的，炸鸡酥脆多汁，酸辣粉也很正宗，分量足，五星好评！"},
+  {"id": 2, "text": "等了一个半小时才送到，汤全洒了，面坨成一坨，联系客服也不回，太让人失望了。"},
+  {"id": 3, "text": "奶茶是用料很扎实的现煮茶，珍珠Q弹有嚼劲，配送员态度也好，下次还会再点。"},
+  {"id": 4, "text": "配送速度一般，但披萨味道不错，芝士拉丝效果好，性价比高，值得推荐。"},
+  {"id": 5, "text": "点的麻辣烫食材不新鲜，有股怪味，吃完拉肚子，商家推卸责任，再也不点了。"}
+]

q2_1_crawler/move.html

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+[
+  {
+    "id": "1",
+    "title": "泰坦尼克号",
+    "director": "Frank Darabont",
+    "year": "2015",
+    "rating": "6.8",
+    "duration": "91",
+    "genre": "科幻",
+    "actors_count": "3"
+  },
+  {
+    "id": "2",
+    "title": "星际穿越",
+    "director": "陈凯歌",
+    "year": "2021",
+    "rating": "6.2",
+    "duration": "113",
+    "genre": "科幻",
+    "actors_count": "2"
+  },
+  {
+    "id": "3",
+    "title": "三傻大闹宝莱坞",
+    "director": "Robert Zemeckis",
+    "year": "2004",
+    "rating": "7.4",
+    "duration": "95",
+    "genre": "悬疑",
+    "actors_count": "4"
+  },
+  {
+    "id": "4",
+    "title": "阿甘正传",
+    "director": "James Cameron",
+    "year": "2013",
+    "rating": "6.9",
+    "duration": "93",
+    "genre": "爱情",
+    "actors_count": "4"
+  },
+  {
+    "id": "5",
+    "title": "放牛班的春天",
+    "director": "宫崎骏",
+    "year": "2005",
+    "rating": "7.1",
+    "duration": "127",
+    "genre": "悬疑",
+    "actors_count": "3"
+  },
+  {
+    "id": "6",
+    "title": "千与千寻",
+    "director": "Christopher Nolan",
+    "year": "2024",
+    "rating": "6.4",
+    "duration": "147",
+    "genre": "动画",
+    "actors_count": "3"
+  },
+  {
+    "id": "7",
+    "title": "忠犬八公的故事",
+    "director": "Lasse Hallström",
+    "year": "2002",
+    "rating": "6.2",
+    "duration": "166",
+    "genre": "剧情",
+    "actors_count": "4"
+  },
+  {
+    "id": "8",
+    "title": "霸王别姬",
+    "director": "Rajkumar Hirani",
+    "year": "2005",
+    "rating": "7.9",
+    "duration": "149",
+    "genre": "冒险",
+    "actors_count": "2"
+  },
+  {
+    "id": "9",
+    "title": "肖申克的救赎",
+    "director": "Christophe Barratier",
+    "year": "2008",
+    "rating": "9.3",
+    "duration": "91",
+    "genre": "冒险",
+    "actors_count": "2"
+  },
+  {
+    "id": "10",
+    "title": "盗梦空间",
+    "director": "Christopher Nolan",
+    "year": "2019",
+    "rating": "7.1",
+    "duration": "132",
+    "genre": "剧情",
+    "actors_count": "5"
+  }
+]

q2_1_crawler/movie.json

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+[
+  {
+    "id": "1",
+    "title": "泰坦尼克号",
+    "director": "Frank Darabont",
+    "year": "2015",
+    "rating": "6.8",
+    "duration": "91",
+    "genre": "科幻",
+    "actors_count": "3"
+  },
+  {
+    "id": "2",
+    "title": "星际穿越",
+    "director": "陈凯歌",
+    "year": "2021",
+    "rating": "6.2",
+    "duration": "113",
+    "genre": "科幻",
+    "actors_count": "2"
+  },
+  {
+    "id": "3",
+    "title": "三傻大闹宝莱坞",
+    "director": "Robert Zemeckis",
+    "year": "2004",
+    "rating": "7.4",
+    "duration": "95",
+    "genre": "悬疑",
+    "actors_count": "4"
+  },
+  {
+    "id": "4",
+    "title": "阿甘正传",
+    "director": "James Cameron",
+    "year": "2013",
+    "rating": "6.9",
+    "duration": "93",
+    "genre": "爱情",
+    "actors_count": "4"
+  },
+  {
+    "id": "5",
+    "title": "放牛班的春天",
+    "director": "宫崎骏",
+    "year": "2005",
+    "rating": "7.1",
+    "duration": "127",
+    "genre": "悬疑",
+    "actors_count": "3"
+  },
+  {
+    "id": "6",
+    "title": "千与千寻",
+    "director": "Christopher Nolan",
+    "year": "2024",
+    "rating": "6.4",
+    "duration": "147",
+    "genre": "动画",
+    "actors_count": "3"
+  },
+  {
+    "id": "7",
+    "title": "忠犬八公的故事",
+    "director": "Lasse Hallström",
+    "year": "2002",
+    "rating": "6.2",
+    "duration": "166",
+    "genre": "剧情",
+    "actors_count": "4"
+  },
+  {
+    "id": "8",
+    "title": "霸王别姬",
+    "director": "Rajkumar Hirani",
+    "year": "2005",
+    "rating": "7.9",
+    "duration": "149",
+    "genre": "冒险",
+    "actors_count": "2"
+  },
+  {
+    "id": "9",
+    "title": "肖申克的救赎",
+    "director": "Christophe Barratier",
+    "year": "2008",
+    "rating": "9.3",
+    "duration": "91",
+    "genre": "冒险",
+    "actors_count": "2"
+  },
+  {
+    "id": "10",
+    "title": "盗梦空间",
+    "director": "Christopher Nolan",
+    "year": "2019",
+    "rating": "7.1",
+    "duration": "132",
+    "genre": "剧情",
+    "actors_count": "5"
+  }
+]

q2_1_crawler/q2_1.py

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+import requests
+from bs4 import BeautifulSoup as bs
+import json
+
+url = 'https://exam.detr.top/exam-b/movies'
+headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/149.0.0.0 Safari/537.36 Edg/149.0.0.0',
+    'Referer':'https://exam.detr.top/exam-b/movies'}
+req = requests.get(url, headers=headers)
+req.encoding="utf-8"
+
+data=[]
+
+soup=bs(req.text,"html.parser")
+# print(soup)
+#id, title, director, year, rating, duration, genre, actors_count
+
+item=soup.select("table tbody tr" )
+movie_list=[]
+
+for tr in item:
+    tds=tr.find_all("td")
+    tds=list(tds)
+    # print(tds)
+    if len(tds)<8:
+        continue
+    movie={
+        "id":tds[0].get_text(strip=True),
+        "title":tds[1].get_text(strip=True),
+        "director":tds[2].get_text(strip=True),
+        "year":tds[3].get_text(strip=True),
+        "rating":tds[4].get_text(strip=True),
+        "duration":tds[5].get_text(strip=True),
+        "genre":tds[6].get_text(strip=True),
+        "actors_count":tds[7].get_text(strip=True)
+        }
+    movie_list.append(movie)
+print(movie_list)
+    
+
+with open('movie.json', 'w', encoding='utf-8') as f:
+    json.dump(movie_list, f, ensure_ascii=False, indent=2)
+
+with open("move.html","w",encoding='utf-8') as f:
+     json.dump(movie_list, f, ensure_ascii=False, indent=2)
+    
+
+
+
+
+# for i in range(len(items)):
+#     rank=i+1
+#     title=items[i].find("span",class_="title").get_text()
+#     actors=items[i].find("div",class_="bd").get_text().strip()
+#     try:
+#        actors=actors.split("主演：")[1].split("\n")[0]
+#     except:
+#        actors="无"
+#     quote=items[i].find("p",class_="quote").get_text().strip()
+
+#     data.append({
+#         "rank":rank,
+#         "title":title,
+#         "actors":actors,
+#         "quote":quote
+#     })

q2_1_crawler/q2_2.py

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+# ① 找出评分最高和最低的电影，打印电影名 + 评分。
+# ② 统计各类型的电影数量，用字典格式输出。
+# ③ 统计各导演的电影数量，用字典格式输出。
+# ④ 统计 2020 年（含）以后上映的电影数量。
+
+import json
+
+
+
+with open('movie.json', 'r', encoding='utf-8') as f:
+    data=json.load(f)
+    # print(data)
+   
+
+sort_movie=sorted(data,key=lambda x:x["rating"])
+min=sort_movie[0]
+max=sort_movie[-1]
+print("评分最低的电影",min["title"],min["rating"])
+print("评分最高的电影",max["title"],max["rating"])
+
+genre_shu={}
+for g in data:
+    ge=g["genre"]
+    if ge in genre_shu:
+        genre_shu[ge]+=1
+    else:
+        genre_shu[ge]=1
+print("各类型的电影数量",genre_shu)
+
+director_shu={}
+for d in data:
+    di=d["director"]
+    if di in director_shu:
+        director_shu[di]+=1
+    else:
+        director_shu[di]=1
+print("各导演的电影数量",director_shu)
+
+a=0
+for y in data:
+    if int(y["year"]) >= 2020:
+        a+=1
+print("2020 年（含）以后上映的电影数量",a)

q3/q3_3_质量自评.md

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+1.标注前准备：
+在图片标注中
+（1）边界框必须紧贴目标物轮廓
+（2）标签必须为 cat、dog、car（必须小写英文，不能写成"猫/狗/车"或"Cat/Dog/Car"）
+在文本标注中
+（1）标注必须包含每条评论的 id 和 text 字段
+（2）每个标注必须有一个 sentiment 字段，值为 "正面" 或 "负面"
+2.标注过程
+在图像的标注中，边界框内的留白较多，解决方法：最大限度地贴近目标轮廓
+在文本的标注中，可能会遇到情感模糊的问题，解决办法：抓住关键词进行标注。
+3.标注后检查
+在图像标注中，再次检查边界框与目标轮廓是否贴合，检查导出的 yolo 文件内容是否完整
+在文本标注中，对照关键词检查情感是否判断正确，检查导出的 json文件内容是否完整

q4/q4_1/q4_1.py

@@ -0,0 +1,33 @@
+import matplotlib.pyplot as plt
+import json
+
+
+with open('movie.json', 'r', encoding='utf-8') as f:
+    data=json.load(f)
+    # print(data)
+    
+genre_shu={}
+for g in data:
+    ge=g["genre"]
+    if ge in genre_shu:
+        genre_shu[ge]+=1
+    else:
+        genre_shu[ge]=1
+# print("各类型的电影数量",genre_shu)
+
+genre_lei=list(genre_shu.keys())
+genre_liang=list(genre_shu.values())
+
+print(genre_liang)
+
+plt.figure(figsize=(14, 12))
+plt.bar(genre_lei,  genre_liang,        # 类别, 数值
+        width=0.6)                   # 柱子宽度（0~1之间）
+
+# 标题和标签
+plt.title('类型电影数量分布', fontsize=14)
+plt.xlabel('类型名称', fontsize=12)
+plt.ylabel('电影数量', fontsize=12)
+
+plt.show()
+

q4/q4_2/q4_2.py

@@ -0,0 +1,24 @@
+import matplotlib.pyplot as plt
+import json
+
+rating=[]
+duration=[]
+
+with open('movie.json', 'r', encoding='utf-8') as f:
+    data=json.load(f)
+    # print(data)
+    for i in data:
+        rating.append(i["rating"])
+        duration.append(i["duration"])
+plt.figure(figsize=(12, 8))
+plt.scatter(duration, rating,
+            c='red',
+            s=80,                      # 点的大小
+            alpha=0.6,                 # 透明度
+            edgecolors='white')         # 点的边框
+plt.title('时长与评分关系散点图', fontsize=14)
+plt.xlabel('时长', fontsize=12)
+plt.ylabel('评分', fontsize=12)
+plt.grid(True, linestyle='--', alpha=0.5)
+plt.show()
+       

q4/q4_3a/q4_3a.py

@@ -0,0 +1,19 @@
+import matplotlib.pyplot as plt
+import json
+rating=[]
+
+with open('movie.json', 'r', encoding='utf-8') as f:
+    data=json.load(f)
+    # print(data)
+    for i in data:
+        rating.append(i["rating"])
+
+plt.figure(figsize=(12,8))
+plt.hist(rating,                     # 数据
+         bins=3,                    # 分成几个柱子
+         color='#3498DB',            # 颜色
+         edgecolor='white')          # 柱子边框颜色
+plt.title('评分分布', fontsize=14)
+plt.xlabel('评分', fontsize=13)
+plt.grid(True, linestyle='--', alpha=0.5, axis='y')
+plt.show()

q4/q4_3b/q4_3b.py

@@ -0,0 +1,19 @@
+import matplotlib.pyplot as plt
+import json
+duration=[]
+
+with open('movie.json', 'r', encoding='utf-8') as f:
+    data=json.load(f)
+    # print(data)
+    for i in data:
+       duration.append(i["duration"])
+
+plt.figure(figsize=(12,8))
+plt.hist( duration,                     # 数据
+         bins=3,                    # 分成几个柱子
+         color='#3498DB',            # 颜色
+         edgecolor='white')          # 柱子边框颜色
+plt.title('时长分布', fontsize=14)
+plt.xlabel('时长（分钟）', fontsize=13)
+plt.grid(True, linestyle='--', alpha=0.5, axis='y')
+plt.show()