fix: brisque

app.py

@@ -15,7 +15,7 @@ eval_net.trans.gated2 = True
 
 def process_image(input_img,score,model_path,gamma=1.0,alpha_s=1.0,alpha_i=1.0):
     if model_path is None:
-        return input_img,"Please choose a model weights.","Please choose a model weights."
+        return input_img,"Please choose a model weights."
     torch.set_grad_enabled(False)
     eval_net.load_state_dict(torch.load(os.path.join(directory,model_path), map_location=lambda storage, loc: storage))
     eval_net.eval()
@@ -36,13 +36,11 @@ def process_image(input_img,score,model_path,gamma=1.0,alpha_s=1.0,alpha_i=1.0):
     output = output[:, :, :h, :w]
     enhanced_img = transforms.ToPILImage()(output.squeeze(0))
     if score == 'Yes':
-        im1 = enhanced_img
-        # score_brisque = brisque.score(im1) 
-        im1 = np.array(im1)
+        im1 = np.array(enhanced_img)
         score_niqe = calculate_niqe(im1)
-        return enhanced_img,score_niqe,0
+        return enhanced_img,score_niqe
     else:
-        return enhanced_img,0,0
+        return enhanced_img,0
 
 def find_pth_files(directory):
     pth_files = []
@@ -74,8 +72,7 @@ interface = gr.Interface(
     ],
     outputs=[
         gr.Image(label="Result", type="pil"),
-        gr.Textbox(label="NIQE"),
-        gr.Textbox(label="BRISQUE")
+        gr.Textbox(label="NIQE")
     ],
     title="HVI-CIDNet (Low-Light Image Enhancement)",
     description="The demo of paper \"You Only Need One Color Space: An Efficient Network for Low-light Image Enhancement\"",