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younesbelkada commited on Apr 6, 2022

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3e3cc54

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1 Parent(s): 5c7822d

change cuda + description

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models/model_settings.py +1 -1
utils/constants.py +3 -6

models/model_settings.py CHANGED Viewed

@@ -97,6 +97,6 @@ STYLEGAN_TRUNCATION_LAYERS = 8  # 0 means no truncation
 STYLEGAN_RANDOMIZE_NOISE = False
 # Settings for model running.
-USE_CUDA = True
 MAX_IMAGES_ON_DEVICE = 8

 STYLEGAN_RANDOMIZE_NOISE = False
 # Settings for model running.
+USE_CUDA = False
 MAX_IMAGES_ON_DEVICE = 8

utils/constants.py CHANGED Viewed

@@ -9,7 +9,7 @@ VALID_CHOICES = [
     "Smiling",
     "Gray_Hair",
 ]
-ENABLE_GPU = True
 MODEL_NAME = "stylegan_ffhq"
 OUTPUT_LIST = [
     gr.outputs.Image(type="pil", label="Generated Images"),
@@ -26,13 +26,13 @@ OUTPUT_LIST = [
 # &#x2B55; This method is biased on the data it has been trained for attribute recognition. E.g. if you decide to modify the "Bald" attribute on Female faces, the method will turn it into Male faces. Future work may focus more on this direction to try to have unbiased results of the modifications.
 # </center>
 # </p>
 # """
 description = """
 <p>
-<center>
 This is an interactive demo of an extension of the <a href="https://genforce.github.io/interfacegan/">CVPR2020 InterfaceGAN paper</a>, by adding other attributes such as Hat, Bald, etc. to the generated images. Here is a step-by-step guide to use this interface:
 <ul>
   <li>🌾 Select the Random seed you want to use to generate the images</li>
@@ -40,10 +40,7 @@ This is an interactive demo of an extension of the <a href="https://genforce.git
   <li>🛠 Select the coefficient of modification (higher value means stronger modification)</li>
   <li>🔥 Submit!</li>
 </ul>
-Check the <a href="https://github.com/genforce/interfacegan">original repo</a> as well as the <a href="https://github.com/younesbelkada/interfacegan">extended version of the work</a>.
 &#x2B55; This method is biased on the data it has been trained for attribute recognition. E.g. if you decide to modify the "Bald" attribute on Female faces, the method will turn it into Male faces. Future work may focus more on this direction to try to have unbiased results of the modifications.
-</center>
 </p>
 """
 css = """

     "Smiling",
     "Gray_Hair",
 ]
+ENABLE_GPU = False
 MODEL_NAME = "stylegan_ffhq"
 OUTPUT_LIST = [
     gr.outputs.Image(type="pil", label="Generated Images"),
 # &#x2B55; This method is biased on the data it has been trained for attribute recognition. E.g. if you decide to modify the "Bald" attribute on Female faces, the method will turn it into Male faces. Future work may focus more on this direction to try to have unbiased results of the modifications.
+#Check the <a href="https://github.com/genforce/interfacegan">original repo</a> as well as the <a href="https://github.com/younesbelkada/interfacegan">extended version of the work</a>.
+#
 # </center>
 # </p>
 # """
 description = """
 <p>
 This is an interactive demo of an extension of the <a href="https://genforce.github.io/interfacegan/">CVPR2020 InterfaceGAN paper</a>, by adding other attributes such as Hat, Bald, etc. to the generated images. Here is a step-by-step guide to use this interface:
 <ul>
   <li>🌾 Select the Random seed you want to use to generate the images</li>
   <li>🛠 Select the coefficient of modification (higher value means stronger modification)</li>
   <li>🔥 Submit!</li>
 </ul>
 &#x2B55; This method is biased on the data it has been trained for attribute recognition. E.g. if you decide to modify the "Bald" attribute on Female faces, the method will turn it into Male faces. Future work may focus more on this direction to try to have unbiased results of the modifications.
 </p>
 """
 css = """