import easyocr as ocr #OCR import streamlit as st #Web App from PIL import Image #Image Processing import numpy as np #Image Processing #title st.title("Easy OCR - Extract Text from Images") #subtitle st.markdown("## Optical Character Recognition - Using `easyocr`, `streamlit` - hosted on 🤗 Spaces") 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_resource 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("This space for testing Huggingface deployment by SYH")