Upload app.py

app.py

@@ -1,28 +1,20 @@
-import transformers
 import streamlit as st
 import io
 from PIL import Image
 import numpy as np
 import cv2
+# from transformers import AutoImageProcessor, AutoModelForImageClassification
+from PIL import Image
 import requests
-import torch
-
+import numpy as np
 from matplotlib import pyplot as plt
 from transformers import pipeline
+
 from torchvision import transforms
-install --only-upgrade tesseract-ocr
-install tesseract-ocr
-install pytesseract
-install tesseract-ocr
-install libtesseract-dev
-install -y tesseract-ocr
-install -y libtesseract-dev
-install -y tesseract-ocr-rus
-import pytesseract
-from bs4 import BeautifulSoup
+import torch
 
 st.set_page_config(
-    page_title="Memory Studies",
+    page_title="MemoryStudies",
     page_icon="😎",
     layout="wide"
 )
@@ -31,7 +23,7 @@ st.markdown("### Распознай текст мемориальной доск
 st.write("Загрузите изображение мемориальной доски в формате png, jpeg, jpg")
 
 
-file = st.file_uploader("Загрузите своё фото:", type=['png','jpeg','jpg'])
+file = st.file_uploader("Загрузите своё фото мемориальной доски:", type=['png','jpeg','jpg'])
 if file:
     image_data = file.getvalue()
     # Показ загруженного изображения на Web-странице средствами Streamlit
@@ -43,29 +35,11 @@ if file:
     # preprocessor = AutoImageProcessor.from_pretrained("google/mobilenet_v2_1.0_224")
     # model = AutoModelForImageClassification.from_pretrained("google/mobilenet_v2_1.0_224")
 
-    detector = pipeline(task="image-classification", model="google/vit-base-patch16-224")
+    detector = pipeline(task="image-classification")
 
     st.markdown(detector(image))
-if file:
-    text = pytesseract.image_to_string(Image.open(io.BytesIO(image_data)), lang='rus')
-
-
-query = '+'.join(text.split())
-search_query = f'https://html.duckduckgo.com/html/?q={query}'
-user_agent = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/124.0.0.0 Safari/537.36'
-
-# Отправляем запрос на страницу поиска
-response = requests.get(search_query, headers={'User-Agent': user_agent}, cookies={'kl': 'ru-ru'})
-
-html_text = response.content.decode('utf-8')
-
-html = BeautifulSoup(response.text, 'html.parser')
 
-# Находим первый результат поиска
-first_result = html.find('a', class_='result__url')
 
-if first_result:
-    st.markdown(first_result.get('href'))
 
 
 #