Update app.py

app.py

@@ -203,6 +203,9 @@ def blur_im(img,bounds,target_lang,trans_lang,ocr_sens,font_fac,t_color):
             elif t_color=="White":
                 im[y:y+h, x:x+w] = cv2.erode(im[y:y+h, x:x+w], kernel, iterations=3)
                 pass
+            else:
+                pass
+            
             im[y:y+h, x:x+w] = cv2.GaussianBlur(im[y:y+h, x:x+w],(51,51),0)
         else:
             pass
@@ -234,7 +237,7 @@ def draw_boxes(image, bounds, ocr_sens,width=1):
         draw.line([*p0, *p1, *p2, *p3, *p0], fill=color, width=width)
     return image
 
-def detect(img, target_lang,trans_lang,ocr_sens,font_fac,target_lang2=None):
+def detect(img, target_lang,trans_lang,ocr_sens,font_fac,t_color):
     if target_lang2 != None and target_lang2 != "":
         lang=f"{lang_id[target_lang]}"
         lang2=f"{lang_id[target_lang2]}"
@@ -252,7 +255,7 @@ def detect(img, target_lang,trans_lang,ocr_sens,font_fac,target_lang2=None):
     bounds = reader.readtext(img1)
     im = PIL.Image.open(path)
     im_out=draw_boxes(im, bounds,ocr_sens)
-    blr_out=blur_im(path,bounds,target_lang,trans_lang,ocr_sens,font_fac)
+    blr_out=blur_im(path,bounds,target_lang,trans_lang,ocr_sens,font_fac,t_color)
     return im_out,blr_out,pd.DataFrame(bounds),pd.DataFrame(bounds).iloc[:,1:]
     
 with gr.Blocks() as robot:
@@ -285,7 +288,7 @@ with gr.Blocks() as robot:
                         ocr_sens=gr.Slider(0.1, 1, step=0.05,value=0.25,label="Detect Min Confidence")
                         font_fac=gr.Slider(0.1, 1, step =0.1,value=0.4,label="Font Scale")
                         ocr_space=gr.Slider(1,10, step=1,value=5,label="Future Function")     
-                        text_color=gr.Radio(["Black", "White"])
+                        text_color=gr.Radio(label="Font Color",choices=["Black", "White"], value="Black")
 
             go_btn=gr.Button("Go")
     with gr.Row():