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'