Update app.py

app.py

@@ -24,7 +24,8 @@ def inference(img, v1  = "121" , v2 = "9" ):
   #out = cv2.adaptiveThreshold(gray,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY,333,3)
   out = cv2.GaussianBlur( gray ,(5,5),0)
   #  v1 121 , v2 1
-  out = cv2.adaptiveThreshold( out ,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, int( float(v1) ) , int( float(v2) ) )
+  #out = cv2.adaptiveThreshold( out ,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, int( float(v1) ) , int( float(v2) ) )
+  out = cv2.adaptiveThreshold( out ,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 121, 9 )
   #out = cv2.dilate(out,(5,5))
   #out = blur = cv.GaussianBlur(img,(5,5),0)
   #out =  cv2.threshold(out,0,255,cv2.THRESH_BINARY+cv2.THRESH_OTSU)
@@ -60,7 +61,7 @@ value=3,
 # For Spaces usage, head to https://huggingface.co/docs/hub/spaces
 iface = gradio.Interface(
   fn=inference,
-  inputs=[['image',num_inference_steps_slider_component_v1,num_inference_steps_slider_component_v2]],
+  inputs=['image',num_inference_steps_slider_component_v1,num_inference_steps_slider_component_v2],
   outputs='image',
   title='Noise Removal', 
   description='Remove Noise with OpenCV and Adaptial Gaussian!',