bare minimum

README.md

@@ -5,9 +5,11 @@ colorFrom: blue
 colorTo: red
 sdk: streamlit
 app_file: language_models_project/app.py
+python_version: 3.10.4
 pinned: false
 ---
 
+
 # image2textapp
 demo of 🤗 spaces deployment of a streamlit python app
 

language_models_project/app.py

@@ -1,8 +1,6 @@
 #from main import classify
-import easyocr as ocr  #OCR
+#import easyocr as ocr  #OCR
 import streamlit as st  #Web App
-from PIL import Image #Image Processing
-import numpy as np #Image Processing 
 
 
 #title
@@ -13,37 +11,4 @@ st.markdown("## Optical Character Recognition - Using `easyocr`, `streamlit` -
 
 st.markdown("Link to the app - [image-to-text-app on 🤗 Spaces](https://huggingface.co/spaces/Amrrs/image-to-text-app)")
 
-#image uploader
-image = st.file_uploader(label = "Upload your image here",type=['png','jpg','jpeg'])
-
-
-@st.cache
-def load_model(): 
-    reader = ocr.Reader(['en'],model_storage_directory='.')
-    return reader 
-
-reader = load_model() #load model
-
-if image is not None:
-
-    input_image = Image.open(image) #read image
-    st.image(input_image) #display image
-
-    with st.spinner("🤖 AI is at Work! "):
-        
-
-        result = reader.readtext(np.array(input_image))
-
-        result_text = [] #empty list for results
-
-
-        for text in result:
-            result_text.append(text[1])
-
-        st.write(result_text)
-    #st.success("Here you go!")
-    st.balloons()
-else:
-    st.write("Upload an Image")
-
 st.caption("Made with ❤️ by @1littlecoder. Credits to 🤗 Spaces for Hosting this ")