diff --git a/backend/model.py b/backend/model.py
deleted file mode 100644
index 3bb59cf..0000000
--- a/backend/model.py
+++ /dev/null
@@ -1,55 +0,0 @@
-import os
-import requests
-from bs4 import BeautifulSoup
-from urllib.parse import urljoin
-import cv2
-from io import BytesIO
-import numpy as np
-
-def download_images(search_query, num_images, output_dir):
-    url = f'https://www.bing.com/images/search?q={search_query}&form=HDRSC2'
-    headers = {
-        'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/64.0.3282.140 Safari/537.36 Edge/17.17134'
-    }
-
-    response = requests.get(url, headers=headers)
-    soup = BeautifulSoup(response.text, 'html.parser')
-    image_tags = soup.find_all('img', {'class': 'mimg'})
-
-    if not os.path.exists(output_dir):
-        os.makedirs(output_dir)
-
-    i = 0
-    face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
-
-    for img_tag in image_tags:
-
-        img_url = img_tag.get('src') or img_tag.get('data-src')
-
-        # Ignore data URL
-        if img_url.startswith('data:image'):
-            continue
-
-        img_data = requests.get(img_url).content
-        img = np.asarray(bytearray(img_data), dtype="uint8")
-        img = cv2.imdecode(img, cv2.IMREAD_COLOR)
-        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
-        faces = face_cascade.detectMultiScale(gray, scaleFactor=1.05, minNeighbors=5, minSize=(40, 40))
-
-        if len(faces) == 1:
-            with open(os.path.join(output_dir, f'{search_query}_{i}.jpg'), 'wb') as f:
-                f.write(img_data)
-            print(f'Downloaded {i + 1}/{num_images} images')
-
-            i += 1
-            if i >= num_images:
-                break
-
-if __name__ == '__main__':
-    politician_names = ["伊藤博文"]
-    num_images = 10
-    base_output_dir = './politicians'
-
-    for name in politician_names:
-        output_dir = os.path.join(base_output_dir, name)
-        download_images(name, num_images, output_dir)