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pbaylies / stylegan-encoder

StyleGAN Encoder - converts real images to latent space
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StopIteration exception in encode_images.py #48

Open armheb opened 4 years ago

armheb commented 4 years ago

I'm using the StyleGAN_Encoder_Tutorial notebook in google colab but whe running the: !python encode_images.py aligned_images/ generated_images/ latent_representations/ \ --vgg_url=https://rolux.org/media/stylegan/vgg16_zhang_perceptual.pkl \ --batch_size=2 cell, I get the following error: Using TensorFlow backend. Setting up TensorFlow plugin "fused_bias_act.cu": Preprocessing... Loading... Done. Setting up TensorFlow plugin "upfirdn_2d.cu": Preprocessing... Loading... Done. Traceback (most recent call last): File "encode_images.py", line 243, in main() File "encode_images.py", line 118, in main generator = Generator(Gs_network, args.batch_size, randomize_noise=args.randomize_noise) File "/content/stylegan2/encoder/generator_model.py", line 62, in init self.dlatent_variable = next(v for v in tf.global_variables() if 'learnable_dlatents' in v.name) StopIteration

Zenobia7 commented 3 years ago

I'm using the StyleGAN_Encoder_Tutorial notebook in google colab but whe running the: !python encode_images.py aligned_images/ generated_images/ latent_representations/ \ --vgg_url=https://rolux.org/media/stylegan/vgg16_zhang_perceptual.pkl \ --batch_size=2 cell, I get the following error: Using TensorFlow backend. Setting up TensorFlow plugin "fused_bias_act.cu": Preprocessing... Loading... Done. Setting up TensorFlow plugin "upfirdn_2d.cu": Preprocessing... Loading... Done. Traceback (most recent call last): File "encode_images.py", line 243, in main() File "encode_images.py", line 118, in main generator = Generator(Gs_network, args.batch_size, randomize_noise=args.randomize_noise) File "/content/stylegan2/encoder/generator_model.py", line 62, in init self.dlatent_variable = next(v for v in tf.global_variables() if 'learnable_dlatents' in v.name) StopIteration

Hello, have you solved the problem? I also encountered this problem and would like to ask how did you solve it in the end?