35 lines
1.4 KiB
Python
35 lines
1.4 KiB
Python
from configs.config_base import config
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config['gpu'] = '1'
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config['lr'] = 0.0001
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config['name'] = 'ae_body_10_3'
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config['notes'] = 'convnext + convnext, add dense with tanh at the end of reverse convnext,\
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flattened bottleneck with 128 latent_dim\ remove global orientation\
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fixed gender issue with deoriented bodies, again, aaand again\
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trained on 100 garments\
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remove multiplications with garment uv mask\
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larger bottleneck, low res output upscaled\
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larger batch size, 32 instead of 4\
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'
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config['dataset_in_memory'] = False
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config['batch_size'] = 32
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config['signature_dynamic'] = { 'id': (),
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'pose_shape': (72 + 11,),
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'uv_body_posed': (3, 512, 256,),
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'mesh_body_posed': (14475, 3,),
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}
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config['signature_static'] = {
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'mesh_mask': (14475,),
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}
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config['cond_ae']['upscale_output'] = True
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config['cond_ae']['bottleneck_size'] = 512
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config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
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config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae']['bottleneck_size']]
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config['cond_ae']['decoder_input'] = (4, 2, config['cond_ae']['bottleneck_size'])
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config['cond_ae']['decoder_depths'] = [3, 3, 9, 3]
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config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 128, 64, 16] |