if __name__ == "__main__":
device = torch.device('cuda:%d' % (0))
load_model_err = 0
from models import Generator as Generator_freeform
frames_dist_folder = 'project_video_frames' # a folder to save generated images
ckpt_path = './time_1024_1/models/180000.pth' # path to the checkpoint
video_name = 'videl_keyframe_15' # name of the generated video
model_type = 'freeform'
net = Generator_freeform(ngf=64, nz=100)
net.load_state_dict(torch.load(ckpt_path)['g'])
net.to(device)
net.eval()
try:
rmtree(frames_dist_folder)
except:
pass
os.makedirs(frames_dist_folder, exist_ok=True)
fps = 30
minutes = 1
im_size = 1024
ease_fn = ease_fn_dict['SineEaseInOut']
make_video_from_latents(net, user_selected_noises,
frames_dist_folder='tmp_video_frames',
video_name='stylegan2_video_1',
fps=30,
video_length=16,
ease_fn=ease_fn_dict['SineEaseInOut'],
model_type=model_type,
im_size=1024)
'''
model_type = 'freeform'
net = Generator_freeform(ngf=64, nz=100)
#net.load_state_dict(torch.load('./abface_1/models/20000.pth')['g'])
#net.load_state_dict(torch.load('./proj_5356.pth')['g'])
net.load_state_dict(torch.load('./time_1024_1/models/180000.pth')['g'])
net.to(device)
net.eval()
#frames_dist_folder = 'project_5122_frames'
frames_dist_folder = 'project_time_frames'
try:
rmtree(frames_dist_folder)
except:
pass
os.makedirs(frames_dist_folder, exist_ok=True)
fps = 30
minutes = 1
im_size = 1024
video_name = 'time_magz_4_kf_15'
