Removed super resolution model load

app.py

@@ -8,13 +8,6 @@ from models.network_swinir import SwinIR as net
 # model load
 param_key_g = 'params_ema'
 device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
-super_res_model = net(upscale=4, in_chans=3, img_size=64, window_size=8,
-                    img_range=1., depths=[6, 6, 6, 6, 6, 6, 6, 6, 6], embed_dim=240,
-                    num_heads=[8, 8, 8, 8, 8, 8, 8, 8, 8],
-                    mlp_ratio=2, upsampler='nearest+conv', resi_connection='3conv')
-super_res_pretrained_model = torch.load("model_zoo/003_realSR_BSRGAN_DFOWMFC_s64w8_SwinIR-L_x4_PSNR.pth")
-super_res_model.load_state_dict(super_res_pretrained_model[param_key_g] if param_key_g in super_res_pretrained_model.keys() else super_res_pretrained_model, strict=True)
-super_res_model.eval()
 
 fisheye_correction_model = net(upscale=4, in_chans=3, img_size=64, window_size=8,
                     img_range=1., depths=[6, 6, 6, 6, 6, 6, 6, 6, 6], embed_dim=240,
@@ -24,7 +17,7 @@ fisheye_correction_pretrained_model = torch.load("model_zoo/003_realSR_BSRGAN_DF
 fisheye_correction_model.load_state_dict(fisheye_correction_pretrained_model[param_key_g] if param_key_g in fisheye_correction_pretrained_model.keys() else fisheye_correction_pretrained_model, strict=True)
 fisheye_correction_model.eval()
 
-def predict(radio_btn, input_img):
+def predict(input_img):
     out = None
     
     # preprocess input
@@ -36,10 +29,7 @@ def predict(radio_btn, input_img):
 
         # inference
         window_size = 8
-        if(radio_btn == 'Super resolution'):
-            model = super_res_model.to(device)
-        else:
-            model = fisheye_correction_model.to(device)
+        model = fisheye_correction_model.to(device)
 
         with torch.no_grad():
             # pad input image to be a multiple of window_size
@@ -88,7 +78,7 @@ def test(model, img_lq):
 gr.Interface(
     fn=predict,
     inputs=[
-        gr.Radio(choices=["Super resolution", "Distortion correction"], value="Super resolution", label="Select task:"), gr.inputs.Image()
+        gr.inputs.Image()
     ],
     outputs=[
         gr.inputs.Image()
@@ -96,7 +86,6 @@ gr.Interface(
     title="SwinIR moon distortion",
     description="Description of the app",
     examples=[
-        ["Super resolution", "render0001.png"], ["Super resolution", "render1546.png"], ["Super resolution", "render1682.png"], 
-        ["Distortion correction", "render0001_DC.png"], ["Distortion correction", "render1546_DC.png"], ["Distortion correction", "render1682_DC.png"]
+        "render0001_DC.png", "render1546_DC.png", "render1682_DC.png"
     ]
 ).launch()