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show_gui.py
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show_gui.py
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import torch
from opt import get_opts
import numpy as np
from einops import rearrange
import dearpygui.dearpygui as dpg
from scipy.spatial.transform import Rotation as R
import time
from datasets import dataset_dict
from datasets.ray_utils import get_ray_directions, get_rays
from models.networks import NGP
from models.rendering import render
from train import depth2img
from utils import load_ckpt
import warnings; warnings.filterwarnings("ignore")
class OrbitCamera:
def __init__(self, K, img_wh, r):
self.K = K
self.W, self.H = img_wh
self.radius = r
self.center = np.zeros(3)
self.rot = np.eye(3)
@property
def pose(self):
# first move camera to radius
res = np.eye(4)
res[2, 3] -= self.radius
# rotate
rot = np.eye(4)
rot[:3, :3] = self.rot
res = rot @ res
# translate
res[:3, 3] -= self.center
return res
def orbit(self, dx, dy):
rotvec_x = self.rot[:, 1] * np.radians(0.05 * dx)
rotvec_y = self.rot[:, 0] * np.radians(-0.05 * dy)
self.rot = R.from_rotvec(rotvec_y).as_matrix() @ \
R.from_rotvec(rotvec_x).as_matrix() @ \
self.rot
def scale(self, delta):
self.radius *= 1.1 ** (-delta)
def pan(self, dx, dy, dz=0):
self.center += 1e-4 * self.rot @ np.array([dx, dy, dz])
class NGPGUI:
def __init__(self, hparams, K, img_wh, radius=2.5):
self.hparams = hparams
rgb_act = 'None' if self.hparams.use_exposure else 'Sigmoid'
self.model = NGP(scale=hparams.scale, rgb_act=rgb_act).cuda()
load_ckpt(self.model, hparams.ckpt_path)
self.cam = OrbitCamera(K, img_wh, r=radius)
self.W, self.H = img_wh
self.render_buffer = np.ones((self.W, self.H, 3), dtype=np.float32)
# placeholders
self.dt = 0
self.mean_samples = 0
self.img_mode = 0
self.register_dpg()
def render_cam(self, cam):
t = time.time()
directions = get_ray_directions(cam.H, cam.W, cam.K, device='cuda')
rays_o, rays_d = get_rays(directions, torch.cuda.FloatTensor(cam.pose))
# TODO: set these attributes by gui
if self.hparams.dataset_name in ['colmap', 'nerfpp']:
exp_step_factor = 1/256
else: exp_step_factor = 0
results = render(self.model, rays_o, rays_d,
**{'test_time': True,
'to_cpu': True, 'to_numpy': True,
'T_threshold': 1e-2,
'exposure': torch.cuda.FloatTensor([dpg.get_value('_exposure')]),
'max_samples': 100,
'exp_step_factor': exp_step_factor})
rgb = rearrange(results["rgb"], "(h w) c -> h w c", h=self.H)
depth = rearrange(results["depth"], "(h w) -> h w", h=self.H)
torch.cuda.synchronize()
self.dt = time.time()-t
self.mean_samples = results['total_samples']/len(rays_o)
if self.img_mode == 0:
return rgb
elif self.img_mode == 1:
return depth2img(depth).astype(np.float32)/255.0
def register_dpg(self):
dpg.create_context()
dpg.create_viewport(title="ngp_pl", width=self.W, height=self.H, resizable=False)
## register texture ##
with dpg.texture_registry(show=False):
dpg.add_raw_texture(
self.W,
self.H,
self.render_buffer,
format=dpg.mvFormat_Float_rgb,
tag="_texture")
## register window ##
with dpg.window(tag="_primary_window", width=self.W, height=self.H):
dpg.add_image("_texture")
dpg.set_primary_window("_primary_window", True)
def callback_depth(sender, app_data):
self.img_mode = 1-self.img_mode
## control window ##
with dpg.window(label="Control", tag="_control_window", width=200, height=150):
dpg.add_slider_float(label="exposure", default_value=0.2,
min_value=1/60, max_value=32, tag="_exposure")
dpg.add_button(label="show depth", tag="_button_depth",
callback=callback_depth)
dpg.add_separator()
dpg.add_text('no data', tag="_log_time")
dpg.add_text('no data', tag="_samples_per_ray")
## register camera handler ##
def callback_camera_drag_rotate(sender, app_data):
if not dpg.is_item_focused("_primary_window"):
return
self.cam.orbit(app_data[1], app_data[2])
def callback_camera_wheel_scale(sender, app_data):
if not dpg.is_item_focused("_primary_window"):
return
self.cam.scale(app_data)
def callback_camera_drag_pan(sender, app_data):
if not dpg.is_item_focused("_primary_window"):
return
self.cam.pan(app_data[1], app_data[2])
with dpg.handler_registry():
dpg.add_mouse_drag_handler(
button=dpg.mvMouseButton_Left, callback=callback_camera_drag_rotate
)
dpg.add_mouse_wheel_handler(callback=callback_camera_wheel_scale)
dpg.add_mouse_drag_handler(
button=dpg.mvMouseButton_Middle, callback=callback_camera_drag_pan
)
## Avoid scroll bar in the window ##
with dpg.theme() as theme_no_padding:
with dpg.theme_component(dpg.mvAll):
dpg.add_theme_style(
dpg.mvStyleVar_WindowPadding, 0, 0, category=dpg.mvThemeCat_Core
)
dpg.add_theme_style(
dpg.mvStyleVar_FramePadding, 0, 0, category=dpg.mvThemeCat_Core
)
dpg.add_theme_style(
dpg.mvStyleVar_CellPadding, 0, 0, category=dpg.mvThemeCat_Core
)
dpg.bind_item_theme("_primary_window", theme_no_padding)
## Launch the gui ##
dpg.setup_dearpygui()
dpg.set_viewport_small_icon("assets/icon.png")
dpg.set_viewport_large_icon("assets/icon.png")
dpg.show_viewport()
def render(self):
while dpg.is_dearpygui_running():
dpg.set_value("_texture", self.render_cam(self.cam))
dpg.set_value("_log_time", f'Render time: {1000*self.dt:.2f} ms')
dpg.set_value("_samples_per_ray", f'Samples/ray: {self.mean_samples:.2f}')
dpg.render_dearpygui_frame()
if __name__ == "__main__":
hparams = get_opts()
kwargs = {'root_dir': hparams.root_dir,
'downsample': hparams.downsample,
'read_meta': False}
dataset = dataset_dict[hparams.dataset_name](**kwargs)
NGPGUI(hparams, dataset.K, dataset.img_wh).render()
dpg.destroy_context()