Create app.py

app.py

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