Add pre download and setup of models first and DRLN and EDSR models.

app.py

@@ -12,12 +12,7 @@ article = "<p style='text-align: center'><a href='https://github.com/eugenesiow/
           "| <a href='https://github.com/eugenesiow/super-image#scale-x2'>Models</a></p>"
 
 
-def inference(img, scale_str, model_name):
-    _id = randint(1, 1000)
-    output_dir = Path('./tmp/')
-    output_dir.mkdir(parents=True, exist_ok=True)
-    output_file = output_dir / ('output_image' + str(_id) + '.jpg')
-    scale = int(scale_str.replace('x', ''))
+def get_model(model_name, scale):
     if model_name == 'EDSR':
         model = EdsrModel.from_pretrained('eugenesiow/edsr', scale=scale)
     elif model_name == 'MSRN':
@@ -40,6 +35,16 @@ def inference(img, scale_str, model_name):
         model = RcanModel.from_pretrained('eugenesiow/rcan', scale=scale)
     else:
         model = EdsrModel.from_pretrained('eugenesiow/edsr-base', scale=scale)
+    return model
+
+
+def inference(img, scale_str, model_name):
+    _id = randint(1, 1000)
+    output_dir = Path('./tmp/')
+    output_dir.mkdir(parents=True, exist_ok=True)
+    output_file = output_dir / ('output_image' + str(_id) + '.jpg')
+    scale = int(scale_str.replace('x', ''))
+    model = get_model(model_name, scale)
     inputs = ImageLoader.load_image(img)
     preds = model(inputs)
     output_file_str = str(output_file.resolve())
@@ -51,8 +56,11 @@ torch.hub.download_url_to_file('http://people.rennes.inria.fr/Aline.Roumy/result
                                'baby.bmp')
 torch.hub.download_url_to_file('http://people.rennes.inria.fr/Aline.Roumy/results/images_SR_BMVC12/input_groundtruth/woman_mini_d3_gaussian.bmp',
                                'woman.bmp')
-# models = ['EDSR-base', 'EDSR', 'MSRN', 'MDSR', 'AWSRN-BAM', 'A2N', 'CARN', 'PAN', 'HAN', 'DRLN', 'RCAN']
-models = ['EDSR-base', 'MSRN', 'MDSR', 'AWSRN-BAM', 'A2N', 'CARN', 'PAN']
+models = ['EDSR-base', 'DRLN', 'EDSR', 'MSRN', 'MDSR', 'AWSRN-BAM', 'A2N', 'CARN', 'PAN']
+scales = [2, 3, 4]
+for model_name in models:
+    for scale in scales:
+        get_model(model_name, scale)
 
 gr.Interface(
     inference,
@@ -68,7 +76,7 @@ gr.Interface(
     article=article,
     examples=[
         ['baby.bmp', 'x2', 'EDSR-base'],
-        ['woman.bmp', 'x3', 'MSRN']
+        ['woman.bmp', 'x3', 'DRLN']
     ],
     enable_queue=True
-    ).launch(debug=True)
+    ).launch(debug=False)