initate cfg and model outside inf

app.py

@@ -13,23 +13,25 @@ def download_file(http_address, file_name):
     r = requests.get(http_address, allow_redirects=True)
     open(file_name, 'wb').write(r.content)
 
-
-cfgs = ['configs/modnet/modnet_mobilenetv2.yml', 'configs/modnet/modnet_resnet50_vd.yml', 'configs/modnet/modnet_hrnet_w18.yml']
+cfg_paths = ['configs/modnet/modnet_mobilenetv2.yml', 'configs/modnet/modnet_resnet50_vd.yml', 'configs/modnet/modnet_hrnet_w18.yml']
+cfgs = [Config(cfg) for cfg in cfg_paths]
 
 download_file('https://paddleseg.bj.bcebos.com/matting/models/modnet-mobilenetv2.pdparams', 'modnet-mobilenetv2.pdparams')
 download_file('https://paddleseg.bj.bcebos.com/matting/models/modnet-resnet50_vd.pdparams', 'modnet-resnet50_vd.pdparams')
 download_file('https://paddleseg.bj.bcebos.com/matting/models/modnet-hrnet_w18.pdparams', 'modnet-hrnet_w18.pdparams')
 models_paths = ['modnet-mobilenetv2.pdparams', 'modnet-resnet50_vd.pdparams', 'modnet-hrnet_w18.pdparams']
+models = [cfg.model for cfg in cfgs]
 
 
 def inference(image, chosen_model):
     paddle.set_device('cpu')
-    cfg = Config(cfgs[chosen_model])
 
+    cfg = cfgs[chosen_model]
     val_dataset = cfg.val_dataset
-    model = cfg.model
     img_transforms = val_dataset.transforms
 
+    model = models[chosen_model]
+
     alpha_pred = predict(model,
                          model_path=models_paths[chosen_model],
                          transforms=img_transforms,
@@ -41,7 +43,6 @@ def inference(image, chosen_model):
 inputs = [gr.inputs.Image(label='Input Image'),
           gr.inputs.Radio(['MobileNetV2', 'ResNet50_vd', 'HRNet_W18'], label='Model', type='index')]
 
-
 gr.Interface(
     inference, 
     inputs,