Update app.py

app.py

@@ -4,34 +4,6 @@ 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("## EasyOCRR with Streamlit")
-
-# upload image file
-file = st.file_uploader(label = "Upload your image", type=['png', 'jpg', 'jpeg'])
-
-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(['my','en'], gpu=False) 
-result = reader.readtext(np.array(image))  # turn image to numpy array
-
-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/
@@ -44,3 +16,57 @@ def rectangle(image, result):
     #display image on streamlit
     st.image(image)
 
+
+# main title
+st.title("Get text from image with EasyOCR")
+
+# subtitle
+st.markdown("## EasyOCR with Streamlit")
+
+# upload image file
+file = st.file_uploader(label = "Upload Here", 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(['en','my'], gpu=False) 
+    result = reader.readtext(np.array(image))  # turn image to numpy array
+
+    # Add a placeholder
+    # latest_iteration = st.empty()
+    # bar = st.progress(0)
+    
+    # for i in range(100):
+      # Update the progress bar with each iteration.
+      # latest_iteration.text(f'Iteration {i+1}')
+      # bar.progress(i + 1)
+      # time.sleep(0.1)
+
+    # print all predicted text:
+    for idx in range(len(result)):
+        pred_text = result[idx][1]
+        st.write(pred_text)
+    
+    # collect the results in the 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
+
+    # create a data frame which shows the predicted text and prediction confidence
+    df = pd.DataFrame.from_dict(textdic_easyocr).T
+    st.table(df)
+
+    # get boxes on the image 
+    rectangle(image, result)
+
+    st.spinner(text="In progress...")
+    
+else:
+    st.write("Upload your image")