fix: weights

app.py

@@ -13,7 +13,9 @@ eval_net = CIDNet()
 eval_net.trans.gated = True
 eval_net.trans.gated2 = True
 
-def process_image(input_img,score,model_path,gamma,alpha_s=1.0,alpha_i=1.0):
+def process_image(input_img,score,model_path,gamma=1.0,alpha_s=1.0,alpha_i=1.0):
+    if len(model_path) == 0:
+        return input_img,"Please choose a model weights.","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()
@@ -65,7 +67,7 @@ interface = gr.Interface(
     inputs=[
         gr.Image(label="Low-light Image", type="pil"),
         gr.Radio(choices=['Yes','No'],label="Image Score"),
-        gr.Radio(choices=pth_files2,label="Model Path",info="Choose your model. The best model is \"generalization.pth\"."),
+        gr.Radio(choices=pth_files2,label="Model Weights",info="Choose your model. The best models are \"SICE.pth\" and \"generalization.pth\"."),
         gr.Slider(0.1,10,label="gamma curve",step=0.01,value=1.0, info="Best range is [0.5,2.5]."),
         gr.Slider(0,2,label="Alpha-s",step=0.01,value=1.0, info="Higher is more saturated."),
         gr.Slider(0.1,2,label="Alpha-i",step=0.01,value=1.0, info="Higher is more lighted.")