Eugene Siow commited on
Commit
41506bf
1 Parent(s): 89d3a8e

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

Browse files
Files changed (1) hide show
  1. app.py +18 -10
app.py CHANGED
@@ -12,12 +12,7 @@ article = "<p style='text-align: center'><a href='https://github.com/eugenesiow/
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  "| <a href='https://github.com/eugenesiow/super-image#scale-x2'>Models</a></p>"
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- def inference(img, scale_str, model_name):
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- _id = randint(1, 1000)
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- output_dir = Path('./tmp/')
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- output_dir.mkdir(parents=True, exist_ok=True)
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- output_file = output_dir / ('output_image' + str(_id) + '.jpg')
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- scale = int(scale_str.replace('x', ''))
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  if model_name == 'EDSR':
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  model = EdsrModel.from_pretrained('eugenesiow/edsr', scale=scale)
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  elif model_name == 'MSRN':
@@ -40,6 +35,16 @@ def inference(img, scale_str, model_name):
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  model = RcanModel.from_pretrained('eugenesiow/rcan', scale=scale)
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  else:
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  model = EdsrModel.from_pretrained('eugenesiow/edsr-base', scale=scale)
 
 
 
 
 
 
 
 
 
 
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  inputs = ImageLoader.load_image(img)
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  preds = model(inputs)
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  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
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  'baby.bmp')
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  torch.hub.download_url_to_file('http://people.rennes.inria.fr/Aline.Roumy/results/images_SR_BMVC12/input_groundtruth/woman_mini_d3_gaussian.bmp',
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  'woman.bmp')
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- # models = ['EDSR-base', 'EDSR', 'MSRN', 'MDSR', 'AWSRN-BAM', 'A2N', 'CARN', 'PAN', 'HAN', 'DRLN', 'RCAN']
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- models = ['EDSR-base', 'MSRN', 'MDSR', 'AWSRN-BAM', 'A2N', 'CARN', 'PAN']
 
 
 
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  gr.Interface(
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  inference,
@@ -68,7 +76,7 @@ gr.Interface(
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  article=article,
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  examples=[
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  ['baby.bmp', 'x2', 'EDSR-base'],
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- ['woman.bmp', 'x3', 'MSRN']
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  ],
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  enable_queue=True
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- ).launch(debug=True)
 
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  "| <a href='https://github.com/eugenesiow/super-image#scale-x2'>Models</a></p>"
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+ def get_model(model_name, scale):
 
 
 
 
 
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  if model_name == 'EDSR':
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  model = EdsrModel.from_pretrained('eugenesiow/edsr', scale=scale)
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  elif model_name == 'MSRN':
 
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  model = RcanModel.from_pretrained('eugenesiow/rcan', scale=scale)
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  else:
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  model = EdsrModel.from_pretrained('eugenesiow/edsr-base', scale=scale)
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+ return model
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+
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+
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+ def inference(img, scale_str, model_name):
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+ _id = randint(1, 1000)
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+ output_dir = Path('./tmp/')
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+ output_dir.mkdir(parents=True, exist_ok=True)
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+ output_file = output_dir / ('output_image' + str(_id) + '.jpg')
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+ scale = int(scale_str.replace('x', ''))
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+ model = get_model(model_name, scale)
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  inputs = ImageLoader.load_image(img)
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  preds = model(inputs)
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  output_file_str = str(output_file.resolve())
 
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  'baby.bmp')
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  torch.hub.download_url_to_file('http://people.rennes.inria.fr/Aline.Roumy/results/images_SR_BMVC12/input_groundtruth/woman_mini_d3_gaussian.bmp',
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  'woman.bmp')
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+ models = ['EDSR-base', 'DRLN', 'EDSR', 'MSRN', 'MDSR', 'AWSRN-BAM', 'A2N', 'CARN', 'PAN']
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+ scales = [2, 3, 4]
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+ for model_name in models:
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+ for scale in scales:
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+ get_model(model_name, scale)
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  gr.Interface(
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  inference,
 
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  article=article,
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  examples=[
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  ['baby.bmp', 'x2', 'EDSR-base'],
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+ ['woman.bmp', 'x3', 'DRLN']
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  ],
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  enable_queue=True
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+ ).launch(debug=False)