ValueError: You need to provide a valid (batch_size)x3x4 projection matrix #41
Description
After the solved installation problem with the use of a docker image based on CUDA 10 and some changes on the cpp code of the neural renderer the code start, but when I try to use the entrypoint_predict I receive the next error:
python3.8 entrypoint_predict.py --options ./experiments/default/resnet.yml --checkpoint ./datasets/data/pretrained/resnet50-19c8e357.pth --folder ./datasets/imgs --name test1
=> creating logs/test1
=> creating checkpoints/test1/default_resnet_0505062026
=> creating summary/test1/default_resnet_0505062026
{'checkpoint': './datasets/data/pretrained/resnet50-19c8e357.pth',
'checkpoint_dir': 'checkpoints/test1/default_resnet_0505062026',
'dataset': {'camera_c': array([111.5, 111.5]),
'camera_f': array([248., 248.]),
'mesh_pos': array([ 0. , 0. , -0.8]),
'name': 'shapenet_demo',
'normalization': True,
'num_classes': 13,
'predict': {'folder': './datasets/imgs'},
'shapenet': {'num_points': 9000,
'resize_with_constant_border': False},
'subset_eval': 'test_tf',
'subset_train': 'train_tf'},
'log_dir': 'logs/test1',
'log_level': 'info',
'loss': {'weights': {'chamfer': array([1., 1., 1.]),
'chamfer_opposite': 0.55,
'constant': 1.0,
'edge': 0.1,
'laplace': 0.5,
'move': 0.033,
'normal': 0.00016,
'reconst': 0.0}},
'model': {'align_with_tensorflow': False,
'backbone': 'resnet50',
'coord_dim': 3,
'gconv_activation': True,
'hidden_dim': 192,
'last_hidden_dim': 192,
'name': 'pixel2mesh',
'z_threshold': 0},
'name': 'test1',
'num_gpus': 8,
'num_workers': 16,
'optim': {'adam_beta1': 0.9,
'lr': 0.0001,
'lr_factor': 0.3,
'lr_step': array([30, 70, 90]),
'name': 'adam',
'sgd_momentum': 0.9,
'wd': 1e-06},
'pin_memory': True,
'summary_dir': 'summary/test1/default_resnet_0505062026',
'test': {'batch_size': 8,
'dataset': array([], dtype=float64),
'shuffle': False,
'summary_steps': 50,
'weighted_mean': False},
'train': {'batch_size': 8,
'checkpoint_steps': 10000,
'num_epochs': 110,
'shuffle': True,
'summary_steps': 50,
'test_epochs': 1,
'use_augmentation': True},
'version': 'default_resnet_0505062026'}
=> creating summary writer
Using GPUs: [0, 1, 2, 3, 4, 5, 6, 7]
Loading datasets: shapenet_demo
Running model initialization...
Traceback (most recent call last):
File "entrypoint_predict.py", line 39, in <module>
main()
File "entrypoint_predict.py", line 34, in main
predictor = Predictor(options, logger, writer)
File "/home/vrai/Pixel2Mesh/functions/predictor.py", line 20, in __init__
super().__init__(options, logger, writer, training=False, shared_model=shared_model)
File "/home/vrai/Pixel2Mesh/functions/base.py", line 55, in __init__
self.init_fn(shared_model=shared_model)
File "/home/vrai/Pixel2Mesh/functions/predictor.py", line 42, in init_fn
self.renderer = MeshRenderer(self.options.dataset.camera_f, self.options.dataset.camera_c,
File "/home/vrai/Pixel2Mesh/utils/vis/renderer.py", line 36, in __init__
self.renderer = nr.Renderer(camera_mode='projection',
File "/usr/local/lib/python3.8/dist-packages/neural_renderer-1.1.3-py3.8-linux-x86_64.egg/neural_renderer/renderer.py", line 34, in __init__
raise ValueError('You need to provide a valid (batch_size)x3x4 projection matrix')
ValueError: You need to provide a valid (batch_size)x3x4 projection matrix
I use the default configuration in the default folder and I also tested with the configuration in the baseline folder, after the changes to the baseline from 8 GPUs to 1 (I know that it is not enough but for testing, I use my personal PC)