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Update app.py
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app.py
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@@ -4,44 +4,31 @@ 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("
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#subtitle
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st.markdown("## Optical Character Recognition - Using `easyocr`, `streamlit` - hosted on 🤗 Spaces")
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st.markdown("Link to the app - [image-to-text-app on 🤗 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.
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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()
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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)
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with st.spinner("🤖 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 ❤️ by @1littlecoder. Credits to 🤗 Spaces for Hosting this ")
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import numpy as np #Image Processing
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#title
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st.title("Image to Text Toy Application")
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#subtitle
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st.markdown("Link to the app - [image-to-text-app on 🤗 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_data
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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()
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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)
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with st.spinner("AI is at Work!"):
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result = reader.readtext(np.array(input_image))
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result_text = []
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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.balloons()
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else:
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st.write("Upload an Image")
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