Update app.py

app.py

@@ -2,7 +2,6 @@ import pandas as pd
 import PIL
 from PIL import Image
 from PIL import ImageDraw
-from PIL import ImageFont
 import gradio as gr
 import torch
 import easyocr
@@ -20,7 +19,7 @@ def midpoint(x1, y1, x2, y2):
     x_mid = int((x1 + x2)/2)
     y_mid = int((y1 + y2)/2)
     return (x_mid, y_mid)
-    
+
 def draw_mask(img, bounds):
     mask = np.zeros(img.shape[:2], dtype="uint8")
     for bound in bounds:
@@ -37,7 +36,8 @@ def draw_mask(img, bounds):
         thickness = int(math.sqrt((x2 - x1)**2 + (y2 - y1)**2))
         
         cv.line(mask, (x_mid0, y_mid0), (x_mid1, y_mi1), 255, thickness)
-    img = cv.inpaint(img, mask, 3, cv.INPAINT_TELEA)            
+    img = cv.inpaint(img, mask, 3, cv.INPAINT_TELEA)
+                 
     return(img)
        
 def inference(img, lang):
@@ -53,15 +53,16 @@ def inference(img, lang):
     bounds = reader.readtext(img.name)
     im = PIL.Image.open(img.name)
     img_array = np.array(im)
-    img = draw_mask(img_array, bounds)
-    img = Image.fromarray(img, 'RGB')
+    im = draw_mask(img_array, bounds)
+    im = Image.fromarray(im, 'RGB')
     lang = ""
-    img.save('result.jpg')
+    im.save('result.jpg')
+    
     return ['result.jpg', pd.DataFrame(bounds). iloc[: , 1:2]]
 
 title = 'Manga Image Cleaner'
 description = 'Image inpainting and text detection demo with the use of EasyOCR and CV2. To use it, simply upload your image and choose a language from the dropdown menu, or click one of the examples to test the program.'
-article = "<p style='text-align: center'><a href='https://www.jaided.ai/easyocr/'>Ready-to-use image inpainting with supported languages such as: Chinese, English, Japanese, and Korean</a> | <a href='https://github.com/JaidedAI/EasyOCR'>Github OCR Repo</a> | <a href='https://towardsdatascience.com/remove-text-from-images-using-cv2-and-keras-ocr-24e7612ae4f4'>CV2 Reference</a></p>"
+article = "<p style='text-align: center'> <a>Ready-to-use image inpainting with supported languages such as: Chinese, English, Japanese, and Korean</a> | <a href='https://github.com/JaidedAI/EasyOCR'>Github OCR Repo</a> | <a href='https://towardsdatascience.com/remove-text-from-images-using-cv2-and-keras-ocr-24e7612ae4f4'>CV2 Reference</a></p>"
 css = ".output_image, .input_image {height: 40rem !important; width: 100% !important;}"
 examples = [['chinese.jpg',"chinese"], ['english.jpg',"english"], ['japanese.jpg',"japanese"], ['korean.jpg',"korean"]]
 choices = [
@@ -74,7 +75,7 @@ gr.Interface(
     inference,
     [gr.inputs.Image(type='file', label='Input'),gr.inputs.Dropdown(choices, type="value", default="korean", label='language')],
     [gr.outputs.Image(type='file', label='Output'), 
-    gr.outputs.Image(type='file', label='Output'), 
+    #gr.outputs.Image(type='file', label='Output'), 
     gr.outputs.Dataframe()],
     title=title,
     description=description,