create first app

app.py

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+import pandas as pd
+import numpy as np
+import streamlit as st
+import easyocr
+import PIL
+from PIL import Image, ImageDraw
+from matplotlib import pyplot as plt
+
+#Main Title
+st.title("Get text from Image with EASYOCR")
+
+#Subtitle
+st.markdown('## Easy OCR with streamlit')
+
+#Upload image file
+file = st.file_uploader(label = "Upload your image", type=['png', 'jpg', 'jpeg'])
+
+image = Image.open(file)
+st.image(image) #display
+
+reader = easyocr.Reader(['en'], gpu=False)
+result = reader.readtext(np.array(image))
+
+textdic_easyocr = {} 
+for idx in range(len(result)): 
+  pred_coor = result[idx][0] 
+  pred_text = result[idx][1] 
+  pred_confidence = result[idx][2] 
+  textdic_easyocr[pred_text] = {} 
+  textdic_easyocr[pred_text]['pred_confidence'] = pred_confidence
+
+ # create a dataframe which shows the predicted text and prediction confidence
+  df = pd.DataFrame.from_dict(textdic_easyocr).T
+  st.table(df)
+
+
+def rectangle(image, result):
+    # https://www.blog.pythonlibrary.org/2021/02/23/drawing-shapes-on-images-with-python-and-pillow/
+    """ draw rectangles on image based on predicted coordinates"""
+    draw = ImageDraw.Draw(image)
+    for res in result:
+        top_left = tuple(res[0][0]) # top left coordinates as tuple
+        bottom_right = tuple(res[0][2]) # bottom right coordinates as tuple
+        draw.rectangle((top_left, bottom_right), outline="blue", width=2)
+    #display image on streamlit
+    st.image(image)