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Browse files- app.py +47 -0
- requirements.txt +5 -0
app.py
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import easyocr as ocr #OCR
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import streamlit as st #Web App
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from PIL import Image #Image Processing
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import numpy as np #Image Processing
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#title
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st.title("Easy OCR - Extract Text from Images")
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#subtitle
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st.markdown("## Optical Character Recognition - Using `easyocr`, `streamlit` - hosted on π€ Spaces")
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st.markdown("Link to the app - [image-to-text-app on π€ Spaces](https://huggingface.co/spaces/Amrrs/image-to-text-app)")
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#image uploader
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image = st.file_uploader(label = "Upload your image here",type=['png','jpg','jpeg'])
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@st.cache
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def load_model():
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reader = ocr.Reader(['en'],model_storage_directory='.')
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return reader
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reader = load_model() #load model
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if image is not None:
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input_image = Image.open(image) #read image
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st.image(input_image) #display image
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with st.spinner("π€ AI is at Work! "):
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result = reader.readtext(np.array(input_image))
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result_text = [] #empty list for results
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for text in result:
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result_text.append(text[1])
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st.write(result_text)
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#st.success("Here you go!")
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st.balloons()
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else:
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st.write("Upload an Image")
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st.caption("Made with β€οΈ by @1littlecoder. Credits to π€ Spaces for Hosting this ")
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requirements.txt
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streamlit
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opencv-python-headless
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numpy
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easyocr
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Pillow
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