Update app.py

app.py

@@ -16,21 +16,21 @@ def inference(img, model):
     os.system('mkdir test')
     img.save("test/1.png", "PNG")
     if model == 'Denoising (gaussian)':
-        os.system('python main_test_SRMNet.py --input_dir test --weights experiments/pretrained_models/Denoise_gaussian.pth')
+        os.system('python main_test_SRMNet.py --input_dir test --task Deblurring_motionblur')
     elif model == 'Denoising (real-world)':
-        os.system('python main_test_SRMNet.py --input_dir test --weights experiments/pretrained_models/Denoise_realworld.pth')
+        os.system('python main_test_SRMNet.py --input_dir test --task Dehaze_realworld')
     elif model == 'Deblurring (motion-blur)':
-        os.system('python main_test_SRMNet.py --input_dir test --weights experiments/pretrained_models/Deblurring_motionblur.pth')
+        os.system('python main_test_SRMNet.py --input_dir test --task Denoise_gaussian')
     elif model == 'Dehazing (dense haze)':
-        os.system('python main_test_SRMNet.py --input_dir test --weights experiments/pretrained_models/Dehaze_realworld.pth')
+        os.system('python main_test_SRMNet.py --input_dir test --task Denoise_realworld')
     elif model == 'Deraining (rainstreak)':
-        os.system('python main_test_SRMNet.py --input_dir test --weights experiments/pretrained_models/Deraining_rainstreak.pth')
+        os.system('python main_test_SRMNet.py --input_dir test --task Deraining_raindrop')
     elif model == 'Deraining (raindrop)':
-        os.system('python main_test_SRMNet.py --input_dir test --weights experiments/pretrained_models/Deraining_raindrop.pth')
+        os.system('python main_test_SRMNet.py --input_dir test --task Deraining_rainstreak')
     elif model == 'Low-light Enhancement':
-        os.system('python main_test_SRMNet.py --input_dir test --weights experiments/pretrained_models/LLEnhancement.pth')
+        os.system('python main_test_SRMNet.py --input_dir test --task LLEnhancement')
     elif model == 'Retouching':
-        os.system('python main_test_SRMNet.py --input_dir test --weights experiments/pretrained_models/Retouching.pth')
+        os.system('python main_test_SRMNet.py --input_dir test --task Retouching')
         
     return 'result/1.png'
 
@@ -39,7 +39,16 @@ title = "[NCHU thesis] Image Restoration by Selective Residual Block on Improved
 description = ""
 article = "<p style='text-align: center'><a href='https://' target='_blank'>Image Restoration by Selective Residual Block on Improved Hierarchical Encoder-Decoder Networks</a> | <a href='https://github.com/FanChiMao/SRMNet-thesis' target='_blank'>Github Repo</a></p> <center><img src='https://visitor-badge.glitch.me/badge?page_id=52Hz_SRMNet_thesis' alt='visitor badge'></center>"
 
-examples = [['low-light.png', 'LOL'], ['low-light_2.png', 'MIT-5K']]
+examples = [
+['figures/noise_1.png', 'Denoising (gaussian)'], 
+['figures/noise_2.png', 'Denoising (real-world)'],
+['figures/blur.png', 'Deblurring (motion-blur)'],
+['figures/haze.png', 'Dehazing (dense haze)'],
+['figures/rainstreak.png', 'Deraining (rainstreak)'],
+['figures/raindrop.png', 'Deraining (raindrop)'],
+['figures/LL.png', 'Low-light Enhancement'],
+['figures/nchu.png', 'Retouching'],
+]
 gr.Interface(
     inference,
     [gr.inputs.Image(type="pil", label="Input"), gr.inputs.Dropdown(choices=[