{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Set CUDA:2 as current device.\n"
]
}
],
"source": [
"import sys\n",
"import os\n",
"import torch\n",
"\n",
"sys.path.append(os.path.abspath(sys.path[0] + '/../'))\n",
"torch.cuda.set_device(2)\n",
"print(\"Set CUDA:%d as current device.\" % torch.cuda.current_device())\n",
"torch.autograd.set_grad_enabled(False)\n",
"\n",
"from data.spherical_view_syn import *\n",
"from configs.spherical_view_syn import SphericalViewSynConfig\n",
"from utils import netio\n",
"from utils import img\n",
"from utils import misc\n",
"from utils import device\n",
"from utils import view\n",
"from components.gen_final import GenFinal\n",
"\n",
"\n",
"def load_net(path):\n",
" config = SphericalViewSynConfig()\n",
" config.from_id(path[:-4])\n",
" config.SAMPLE_PARAMS['perturb_sample'] = False\n",
" #config.print()\n",
" net = config.create_net().to(device.default())\n",
" netio.load(path, net)\n",
" return net\n",
"\n",
"\n",
"def find_file(prefix):\n",
" for path in os.listdir():\n",
" if path.startswith(prefix + '@'):\n",
" return path\n",
" return None\n",
"\n",
"\n",
"def load_views(data_desc_file) -> view.Trans:\n",
" with open(data_desc_file, 'r', encoding='utf-8') as file:\n",
" data_desc = json.loads(file.read())\n",
" view_centers = torch.tensor(\n",
" data_desc['view_centers'], device=device.default()).view(-1, 3)\n",
" view_rots = torch.tensor(\n",
" data_desc['view_rots'], device=device.default()).view(-1, 3, 3)\n",
" return view.Trans(view_centers, view_rots)\n",
"\n",
"scenes = {\n",
" 'gas': '__0_user_study/us_gas_all_in_one',\n",
" 'mc': '__0_user_study/us_mc_all_in_one',\n",
" 'bedroom': 'bedroom_all_in_one',\n",
" 'gallery': 'gallery_all_in_one',\n",
" 'lobby': 'lobby_all_in_one'\n",
"}\n",
"\n",
"fov_list = [20, 45, 110]\n",
"res_list = [(128, 128), (256, 256), (256, 230)]\n",
"res_full = (1600, 1440)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Change working directory to /home/dengnc/deep_view_syn/data/__0_user_study/us_mc_all_in_one\n",
"Load net from fovea@nmsl-rgb_e10_fc128x4_d1-50_s32.pth ...\n",
"Load net from periph@nnmsl-rgb_e10_fc64x4_d1-50_s16.pth ...\n",
"Dataset loaded.\n",
"views: [110]\n"
]
}
],
"source": [
"scene = 'mc'\n",
"os.chdir(sys.path[0] + '/../data/' + scenes[scene])\n",
"print('Change working directory to ', os.getcwd())\n",
"\n",
"fovea_net = load_net(find_file('fovea'))\n",
"periph_net = load_net(find_file('periph'))\n",
"\n",
"# Load Dataset\n",
"views = load_views('nerf_views.json')\n",
"print('Dataset loaded.')\n",
"print('views:', views.size())\n",
"gen = GenFinal(fov_list, res_list, res_full, fovea_net, periph_net,\n",
" device=device.default())"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"for view_idx in range(20):\n",
" center = (0, 0)\n",
" test_view = views.get(view_idx)\n",
" images = gen.gen(center, test_view,\n",
" mono_trans=view.Trans(test_view.trans_point(\n",
" torch.tensor([-0.03, 0, 0], device=device.default())\n",
" ), test_view.r))\n",
" #left_images = gen(center, view.Trans(\n",
" # test_view.trans_point(\n",
" # torch.tensor([-0.03, 0, 0], device=device.default())\n",
" # ), test_view.r), mono_trans=test_view, ret_raw=True)\n",
" #right_images = gen(center, view.Trans(\n",
" # test_view.trans_point(\n",
" # torch.tensor([0.03, 0, 0], device=device.default())\n",
" # ), test_view.r), mono_trans=test_view, ret_raw=True)\n",
" #plot_figures(images, center)\n",
"\n",
" outputdir = '/home/dengnc/deep_view_syn/data/__1_eval/output_mono_periph/ref_as_right_eye/%s/' % scene\n",
" misc.create_dir(outputdir)\n",
" #for key in images:\n",
" key = 'blended'\n",
" img.save(images[key], outputdir + 'view%04d_%s.png' % (view_idx, key))\n"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"ename": "TypeError",
"evalue": "gen() takes 3 positional arguments but 4 were given",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-5-245bea67ea44>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mcenter\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0mtest_view\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mviews\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m \u001b[0mimages\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgen\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcenter\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtest_view\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 8\u001b[0m \u001b[0;31m#plot_figures(images, center)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mTypeError\u001b[0m: gen() takes 3 positional arguments but 4 were given"
]
}
],
"source": [
"import numpy as np\n",
"gaze_idx = 0\n",
"for y in np.linspace(-200, 200, 11):\n",
" for x in np.linspace(-200, 200, 11):\n",
" center = (int(x), int(y))\n",
" test_view = views.get(0)\n",
" images = gen.gen(center, test_view, True)\n",
" #plot_figures(images, center)\n",
"\n",
" misc.create_dir('output/eval_gaze')\n",
" out_path = 'output/eval_gaze/gaze%03d_%d,%d.png' % (gaze_idx, x, y)\n",
" img.save(images['blended'], out_path)\n",
" print('Output ' + out_path)\n",
" gaze_idx += 1"
]
}
],
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"language_info": {
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