invaders = torchvision.datasets.ImageFolder(
root=config.datapath('spaceinvaders/images/raw'),
transform=TVT.Compose([TVT.ToTensor()]))
from mentalitystorm.transforms import ColorMask
shots = ColorMask(lower=[128, 128, 128], upper=[255, 255, 255])
cartpole = torchvision.datasets.ImageFolder(
root=config.datapath('cartpole/images/raw'),
transform=TVT.Compose([TVT.ToTensor()]))
co_ord_conv_invaders = GymImageDataset(
directory=config.datapath(r'SpaceInvaders-v4\images\raw_v1\all'),
input_transform=TVT.Compose([TVT.ToTensor(),
transforms.CoordConv()]),
target_transform=TVT.Compose([TVT.ToTensor()]))
co_ord_conv_shots = GymImageDataset(
directory=config.datapath(r'SpaceInvaders-v4\images\raw_v1\all'),
input_transform=TVT.Compose(
[shots, TVT.ToTensor(),
transforms.CoordConv()]),
target_transform=TVT.Compose([shots, TVT.ToTensor()]))
regular_invaders = GymImageDataset(
directory=config.datapath(r'SpaceInvaders-v4\images\raw_v1\all'),
input_transform=TVT.Compose([TVT.ToTensor()]),
target_transform=TVT.Compose([TVT.ToTensor()]))
co_ord_conv_data_package = DataPackage(co_ord_conv_invaders,
input_viewer = ImageViewer('input', (320, 480))
output_viewer = ImageViewer('output', (320, 480))
latent_viewer = ImageViewer('latent', (320, 480))
latent_instr = LatentInstrument()
invader = tf.ColorMask(lower=[120, 125, 30],
upper=[140, 140, 130],
append=False)
cut_invader = tf.SetRange(0, 30, 0, 210, [0])
co_ord_conv_shots = GymImageDataset(
directory=config.datapath(r'SpaceInvaders-v4\images\raw_v1\all'),
input_transform=TVT.Compose(
[invader, cut_invader,
TVT.ToTensor(),
tf.CoordConv()]),
target_transform=TVT.Compose([invader, cut_invader,
TVT.ToTensor()]))
co_ord_conv_data_package = DataPackage(co_ord_conv_shots, StandardSelect())
run_fac = SimpleRunFac()
compressor = Params(Compressor, (210, 160),
1,
input_channels=3,
output_channels=1)
opt = Params(Adam, lr=1e-3)
run_fac.run_list.append(
Run(compressor,
opt,
def view_decode(model, input, output):
image = model.decode(output)
decode_viewer.update(image)
decode2_viewer.update(image)
shots = tf.ColorMask(lower=[128, 128, 128], upper=[255, 255, 255], append=True)
player = tf.ColorMask(lower=[30, 100, 40], upper=[70, 180, 70], append=True)
cut_player = tf.SetRange(0, 60, 0, 210, [4])
invader = tf.ColorMask(lower=[120, 125, 30], upper=[140, 140, 130], append=True)
cut_invader = tf.SetRange(0, 30, 0, 210, [5])
barrier = tf.ColorMask(lower=[120, 74, 30], upper=[190, 100, 70], append=True)
select = tf.SelectChannels([3, 4, 5, 6])
segmentor = TVT.Compose([shots, player, cut_player, invader, cut_invader,
barrier, select, TVT.ToTensor(), tf.CoordConv()])
co_ord_conv_shots = GymImageDataset(directory=config.datapath(r'SpaceInvaders-v4\images\raw_v1\all'),
input_transform=segmentor,
target_transform=segmentor)
co_ord_conv_data_package = DataPackage(co_ord_conv_shots, StandardSelect())
channel_coder = Params(MultiChannelAE)
opt = Params(Adam, lr=1e-3)
run_fac = SimpleRunFac(increment_run=False)
run_fac.run_list.append(Run(channel_coder, None, None, co_ord_conv_data_package,
run_name='shots_v1', trainer=SimpleInference()))
#run_fac = SimpleRunFac.resume(r'C:\data\runs\549', co_ord_conv_data_package)
invaders = torchvision.datasets.ImageFolder(
root=config.datapath('spaceinvaders/images/raw'),
transform=TVT.Compose([TVT.ToTensor()])
)
from mentalitystorm.transforms import ColorMask
shots = ColorMask(lower=[128, 128, 128], upper=[255, 255, 255])
cartpole = torchvision.datasets.ImageFolder(
root=config.datapath('cartpole/images/raw'),
transform=TVT.Compose([TVT.ToTensor()])
)
co_ord_conv_invaders = GymImageDataset(directory=config.datapath(r'SpaceInvaders-v4\images\raw_v1\all'),
input_transform=TVT.Compose([TVT.ToTensor(), transforms.CoordConv()]),
target_transform=TVT.Compose([TVT.ToTensor()]))
co_ord_conv_invaders_w_target = GymImageDataset(directory=config.datapath(r'SpaceInvaders-v4\images\raw_v1\all'),
input_transform=TVT.Compose(
[TVT.ToTensor(), transforms.CoordConv()]),
target_transform=TVT.Compose(
[TVT.ToTensor(), transforms.CoordConv()]))
regular_invaders = GymImageDataset(directory=config.datapath(r'SpaceInvaders-v4\images\raw_v1\all'),
input_transform=TVT.Compose([TVT.ToTensor()]),
target_transform=TVT.Compose([TVT.ToTensor()]))
co_ord_conv_data_package_w_target = DataPackage(co_ord_conv_invaders_w_target, StandardSelect())
co_ord_conv_data_package = DataPackage(co_ord_conv_invaders, StandardSelect())
control_data_package = DataPackage(regular_invaders, AutoEncodeSelect())
from mentalitystorm.basemodels import MultiChannelAE, DummyAE
from mentalitystorm.train import SimpleInference
if __name__ == '__main__':
input_viewer = ImageViewer('input', (320, 480))
output_viewer = ImageViewer('output', (320, 480))
latent_viewer = ImageViewer('latent', (320, 480))
latent_instr = LatentInstrument()
shots = tf.ColorMask(lower=[128, 128, 128], upper=[255, 255, 255], append=True)
player = tf.ColorMask(lower=[30, 100, 40], upper=[70, 180, 70], append=True)
cut = tf.SetRange(0, 60, 0, 210, [4])
select = tf.SelectChannels([3, 4])
segmentor = TVT.Compose([shots, player, cut, select, TVT.ToTensor(), tf.CoordConv()])
co_ord_conv_shots = GymImageDataset(directory=config.datapath(r'SpaceInvaders-v4\images\raw_v1\all'),
input_transform=segmentor,
target_transform=segmentor)
co_ord_conv_data_package = DataPackage(co_ord_conv_shots, StandardSelect())
channel_coder = Params(MultiChannelAE)
opt = Params(Adam, lr=1e-3)
run_fac = SimpleRunFac()
run_fac.run_list.append(Run(channel_coder, None, None, co_ord_conv_data_package,
run_name='shots_v1', trainer=SimpleInference()))
#run_fac = SimpleRunFac.resume(r'C:\data\runs\549', co_ord_conv_data_package)
