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import PIL
from PIL import ImageDraw
from PIL import Image
import streamlit as st
import os
def load_image(image_file):
img = PIL.Image.open(image_file)
return img
def init_session_states():
if 'disp' not in st.session_state:
st.session_state['disp'] = st.empty()
st.session_state['disp'].text("Setting up environment with latest build of easyocr. This will take about a minute ")
if 'init' not in st.session_state:
st.session_state['init'] = 1
os.system('pip install git+git://github.com/jaidedai/easyocr.git')
os.system('pip install git+https://github.com/huggingface/transformers.git --upgrade')
init_session_states()
import easyocr
from transformers import TrOCRProcessor, VisionEncoderDecoderModel
def text_recognition(image):
processor = TrOCRProcessor.from_pretrained("microsoft/trocr-base-handwritten")
model = VisionEncoderDecoderModel.from_pretrained("microsoft/trocr-base-handwritten")
#processor = TrOCRProcessor.from_pretrained("microsoft/trocr-large-handwritten")
#model = VisionEncoderDecoderModel.from_pretrained("microsoft/trocr-large-handwritten")
pixel_values = processor(image, return_tensors="pt").pixel_values
generated_ids = model.generate(pixel_values)
generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
st.write(generated_text)
def main():
st.session_state['disp'].text("Env setup up Complete")
uploaded_file = st.file_uploader("Choose image file to detect text",type=['jpeg','jpg'])
if uploaded_file is not None:
file_details = {"FileName":uploaded_file.name,"FileType":uploaded_file.type,"FileSize":uploaded_file.size}
st.write(file_details)
image = load_image(uploaded_file)
st.image(image,width=500)
st.write("Detecting text bounding box and Take 1 recognition...")
reader = easyocr.Reader(['en'],gpu=True)
bound = reader.readtext(image)
st.write("Bounding box Detection complete")
st.write(str(bound))
st.write("Recognizing text - Take 2....")
text_recognition(image)
if __name__ == "__main__":
main()
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