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pelinbalci
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8f25cfa
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Parent(s):
66cafe3
Create app.py
Browse files
app.py
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import pandas as pd
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import numpy as np
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import PIL
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from PIL import Image
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import streamlit as st
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import torch
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import easyocr
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from matplotlib import pyplot as plt
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# main title
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st.title("Get text from image with EasyOCR")
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# subtitle
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st.markdown("## EasyOCRR with Streamlit")
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# upload image file
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image = st.file_uploader(label = "Upload your image", type=['png', 'jpg', 'jpeg'])
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#read the csv file and display the dataframe
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if file is not None:
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image = Image.open(file) # read image with PIL library
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st.image(image) #display
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# it will only detect the English and Turkish part of the image as text
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reader = easyocr.Reader(['tr','en'], gpu=False)
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result = reader.readtext(np.array(image)) # turn image to numpy array
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# collect the results in dictionary:
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textdic_easyocr = {}
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for idx in range(len(result)):
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pred_coor = result[idx][0]
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pred_text = result[idx][1]
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pred_confidence = result[idx][2]
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textdic_easyocr[pred_text] = {}
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textdic_easyocr[pred_text]['pred_confidence'] = pred_confidence
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df = pd.DataFrame.from_dict(textdic_easyocr).T
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st.table(df)
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ax1.plot(agg_df.year, agg_df.rating)
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st.pyplot(fig1)
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for res in result:
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top_left = tuple(res[0][0]) # top left coordinates as tuple
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bottom_right = tuple(res[0][2]) # bottom right coordinates as tuple
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# draw rectangle on image, 2 is thickness
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cv2.rectangle(image, top_left, bottom_right, (0, 255, 0), 2)
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# write recognized text on image (top_left) minus 10 pixel on y
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cv2.putText(image, res[1], (top_left[0], top_left[1]-10), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)
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fig1, ax1 = plt.subplots()
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plt.imshow(image)
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plt.show()
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else:
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st.write("Upload your image")
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