Update app.py

app.py

@@ -18,13 +18,13 @@ def rectangle(image, result):
 
 
 # main title
-st.title("Get text from image with EasyOCR")
+st.title("Recognize text and locations from flowchart")
 
 # subtitle
-st.markdown("## EasyOCR with Streamlit")
+st.markdown("## FlowchartOCR")
 
 # upload image file
-file = st.file_uploader(label = "Upload Here", type=['png', 'jpg', 'jpeg'])
+file = st.file_uploader(label = "Upload Image", type=['png', 'jpg', 'jpeg'])
 
 #read the csv file and display the dataframe
 if file is not None:
@@ -32,23 +32,9 @@ if file is not None:
     st.image(image) #display
 
     # it will only detect the English and Turkish part of the image as text
-    reader = easyocr.Reader(['en','ja'], gpu=False) 
+    reader = easyocr.Reader(['en'], 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 = {}
@@ -56,8 +42,9 @@ if file is not None:
         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
+        if(pred_confidence>0.6):
+            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