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visualizer.py
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# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and related documentation without an express
# license agreement from NVIDIA CORPORATION is strictly prohibited.
import click
import os
import multiprocessing
import numpy as np
import imgui
import dnnlib
from gui_utils import imgui_window
from gui_utils import imgui_utils
from gui_utils import gl_utils
from gui_utils import text_utils
from viz import renderer
from viz import pickle_widget
from viz import latent_widget
from viz import stylemix_widget
from viz import trunc_noise_widget
from viz import performance_widget
from viz import capture_widget
from viz import layer_widget
from viz import equivariance_widget
from viz import pose_widget
from viz import zoom_widget
from viz import conditioning_pose_widget
from viz import render_type_widget
from viz import render_depth_sample_widget
from viz import deformation_widget
import scipy.io
from pathlib import Path
#----------------------------------------------------------------------------
class Visualizer(imgui_window.ImguiWindow):
def __init__(self, capture_dir=None, projector_overwrite=None):
super().__init__(title='Cat Machine', window_width=1920, window_height=1080)
self.projector_overwrite = projector_overwrite
# Internals.
self._last_error_print = None
self._async_renderer = AsyncRenderer()
self._defer_rendering = 0
self._tex_img = None
self._tex_obj = None
# Widget interface.
self.args = dnnlib.EasyDict()
self.result = dnnlib.EasyDict()
self.pane_w = 0
self.label_w = 0
self.button_w = 0
# Widgets.
self.pickle_widget = pickle_widget.PickleWidget(self)
self.latent_widget = latent_widget.LatentWidget(self)
self.stylemix_widget = stylemix_widget.StyleMixingWidget(self)
self.trunc_noise_widget = trunc_noise_widget.TruncationNoiseWidget(self)
self.perf_widget = performance_widget.PerformanceWidget(self)
self.capture_widget = capture_widget.CaptureWidget(self)
self.layer_widget = layer_widget.LayerWidget(self)
self.eq_widget = equivariance_widget.EquivarianceWidget(self)
self.pose_widget = pose_widget.PoseWidget(self)
self.zoom_widget = zoom_widget.ZoomWidget(self)
self.conditioning_pose_widget = conditioning_pose_widget.ConditioningPoseWidget(self)
self.render_type_widget = render_type_widget.RenderTypeWidget(self)
self.render_depth_sample_widget = render_depth_sample_widget.RenderDepthSampleWidget(self)
# Widgets for varying face/body pose parameters
self.deformation_widget = deformation_widget.DeformationWidget(self, include=['pose', 'betas', 'orient'])
if capture_dir is not None:
self.capture_widget.path = capture_dir
# Initialize window.
self.set_position(0, 0)
self._adjust_font_size()
self.skip_frame() # Layout may change after first frame.
def close(self):
super().close()
if self._async_renderer is not None:
self._async_renderer.close()
self._async_renderer = None
def add_recent_pickle(self, pkl, ignore_errors=False):
self.pickle_widget.add_recent(pkl, ignore_errors=ignore_errors)
def load_pickle(self, pkl, ignore_errors=False):
self.pickle_widget.load(pkl, ignore_errors=ignore_errors)
def print_error(self, error):
error = str(error)
if error != self._last_error_print:
print('\n' + error + '\n')
self._last_error_print = error
def defer_rendering(self, num_frames=1):
self._defer_rendering = max(self._defer_rendering, num_frames)
def clear_result(self):
self._async_renderer.clear_result()
def set_async(self, is_async):
if is_async != self._async_renderer.is_async:
self._async_renderer.set_async(is_async)
self.clear_result()
if 'image' in self.result:
self.result.message = 'Switching rendering process...'
self.defer_rendering()
def _adjust_font_size(self):
old = self.font_size
self.set_font_size(min(self.content_width / 120, self.content_height / 60))
if self.font_size != old:
self.skip_frame() # Layout changed.
def draw_frame(self, i_f=None, p_info=None, side_by_side_pkl=None, write_out_image=None, read_in_canonpose=None,
write_output_frames=None):
self.begin_frame()
self.args = dnnlib.EasyDict()
self.pane_w = self.font_size * 50
self.button_w = self.font_size * 5
self.label_w = round(self.font_size * 5.5)
# Detect mouse dragging in the result area.
dragging, dx, dy = imgui_utils.drag_hidden_window('##result_area', x=self.pane_w, y=0, width=self.content_width-self.pane_w, height=self.content_height)
if dragging:
self.pose_widget.drag(dx, dy)
# Begin control pane.
imgui.set_next_window_position(0, 0)
imgui.set_next_window_size(self.pane_w, self.content_height)
imgui.begin('##control_pane', closable=False, flags=(imgui.WINDOW_NO_TITLE_BAR | imgui.WINDOW_NO_RESIZE | imgui.WINDOW_NO_MOVE))
# Widgets.
expanded, _visible = imgui_utils.collapsing_header('Network & latent', default=True)
self.pickle_widget(expanded)
self.pose_widget(expanded)
self.zoom_widget(expanded)
self.conditioning_pose_widget(expanded)
self.render_type_widget(expanded)
self.render_depth_sample_widget(expanded)
self.latent_widget(expanded)
self.stylemix_widget(expanded)
self.trunc_noise_widget(expanded)
expanded, _visible = imgui_utils.collapsing_header('Performance & capture', default=True)
self.perf_widget(expanded)
self.capture_widget(expanded)
expanded, _visible = imgui_utils.collapsing_header('Layers & channels', default=True)
self.layer_widget(expanded)
with imgui_utils.grayed_out(not self.result.get('has_input_transform', False)):
expanded, _visible = imgui_utils.collapsing_header('Equivariance', default=True)
self.eq_widget(expanded)
expanded, _visible = imgui_utils.collapsing_header('Deformation', default=True)
self.deformation_widget(expanded)
#
#
#
# Render.
if self.is_skipping_frames():
pass
elif self._defer_rendering > 0:
self._defer_rendering -= 1
elif self.args.pkl is not None:
self._async_renderer.set_args(**self.args, i_f=i_f, p_info=p_info,
projector_overwrite=self.projector_overwrite,
side_by_side_pkl=side_by_side_pkl, write_out_image=write_out_image,
read_in_canonpose=read_in_canonpose, write_output_frames=write_output_frames)
result = self._async_renderer.get_result()
if result is not None:
self.result = result
# Display.
max_w = self.content_width - self.pane_w
max_h = self.content_height
pos = np.array([self.pane_w + max_w / 2, max_h / 2])
if 'image' in self.result:
if self._tex_img is not self.result.image:
self._tex_img = self.result.image
if self._tex_obj is None or not self._tex_obj.is_compatible(image=self._tex_img):
self._tex_obj = gl_utils.Texture(image=self._tex_img, bilinear=False, mipmap=False)
else:
self._tex_obj.update(self._tex_img)
zoom = min(max_w / self._tex_obj.width, max_h / self._tex_obj.height)
# print(zoom)
zoom = np.floor(zoom) if zoom >= 1 else zoom
# zoom = 1
self._tex_obj.draw(pos=pos, zoom=zoom, align=0.5, rint=True)
if 'error' in self.result:
self.print_error(self.result.error)
if 'message' not in self.result:
self.result.message = str(self.result.error)
if 'message' in self.result:
tex = text_utils.get_texture(self.result.message, size=self.font_size, max_width=max_w, max_height=max_h, outline=2)
tex.draw(pos=pos, align=0.5, rint=True, color=1)
# End frame.
self._adjust_font_size()
imgui.end()
self.end_frame()
#----------------------------------------------------------------------------
class AsyncRenderer:
def __init__(self):
self._closed = False
self._is_async = False
self._cur_args = None
self._cur_result = None
self._cur_stamp = 0
self._renderer_obj = None
self._args_queue = None
self._result_queue = None
self._process = None
def close(self):
self._closed = True
self._renderer_obj = None
if self._process is not None:
self._process.terminate()
self._process = None
self._args_queue = None
self._result_queue = None
@property
def is_async(self):
return self._is_async
def set_async(self, is_async):
self._is_async = is_async
def set_args(self, **args):
assert not self._closed
if args != self._cur_args:
if self._is_async:
self._set_args_async(**args)
else:
self._set_args_sync(**args)
self._cur_args = args
def _set_args_async(self, **args):
if self._process is None:
self._args_queue = multiprocessing.Queue()
self._result_queue = multiprocessing.Queue()
try:
multiprocessing.set_start_method('spawn')
except RuntimeError:
pass
self._process = multiprocessing.Process(target=self._process_fn, args=(self._args_queue, self._result_queue), daemon=True)
self._process.start()
self._args_queue.put([args, self._cur_stamp])
def _set_args_sync(self, **args):
if self._renderer_obj is None:
self._renderer_obj = renderer.Renderer()
self._cur_result = self._renderer_obj.render(**args)
def get_result(self):
assert not self._closed
if self._result_queue is not None:
while self._result_queue.qsize() > 0:
result, stamp = self._result_queue.get()
if stamp == self._cur_stamp:
self._cur_result = result
return self._cur_result
def clear_result(self):
assert not self._closed
self._cur_args = None
self._cur_result = None
self._cur_stamp += 1
@staticmethod
def _process_fn(args_queue, result_queue):
renderer_obj = renderer.Renderer()
cur_args = None
cur_stamp = None
while True:
args, stamp = args_queue.get()
while args_queue.qsize() > 0:
args, stamp = args_queue.get()
if args != cur_args or stamp != cur_stamp:
result = renderer_obj.render(**args)
if 'error' in result:
result.error = renderer.CapturedException(result.error)
result_queue.put([result, stamp])
cur_args = args
cur_stamp = stamp
#----------------------------------------------------------------------------
@click.command()
@click.argument('pkls', metavar='PATH', nargs=-1)
@click.option('--capture-dir', help='Where to save screenshot captures', metavar='PATH', default=None)
@click.option('--browse-dir', help='Specify model path for the \'Browse...\' button', metavar='PATH')
@click.option('--overwrite_bodypose_params', metavar='PATH', default=None)
@click.option('--projector_overwrite', metavar='STR', default=None)
@click.option('--side_by_side_pkl', metavar='STR', default=None)
@click.option('--write_out_image', required=False, default=None)
@click.option('--read_in_canonpose', required=False, default=None)
@click.option('--write_output_frames', required=False, default=None)
def main(
pkls,
capture_dir,
browse_dir,
overwrite_bodypose_params,
projector_overwrite,
side_by_side_pkl,
write_out_image,
read_in_canonpose,
write_output_frames,
):
"""Interactive model visualizer.
Optional PATH argument can be used specify which .pkl file to load.
"""
viz = Visualizer(capture_dir=capture_dir, projector_overwrite=projector_overwrite)
if browse_dir is not None:
viz.pickle_widget.search_dirs = [browse_dir]
# List pickles.
# pkls = ['/home/ericchan/Downloads/network-snapshot-002200.pkl']
if len(pkls) > 0:
for pkl in pkls:
viz.add_recent_pickle(pkl)
viz.load_pickle(pkls[0])
else:
pretrained = [
'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan3/versions/1/files/stylegan3-r-afhqv2-512x512.pkl',
'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan3/versions/1/files/stylegan3-r-ffhq-1024x1024.pkl',
'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan3/versions/1/files/stylegan3-r-ffhqu-1024x1024.pkl',
'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan3/versions/1/files/stylegan3-r-ffhqu-256x256.pkl',
'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan3/versions/1/files/stylegan3-r-metfaces-1024x1024.pkl',
'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan3/versions/1/files/stylegan3-r-metfacesu-1024x1024.pkl',
'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan3/versions/1/files/stylegan3-t-afhqv2-512x512.pkl',
'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan3/versions/1/files/stylegan3-t-ffhq-1024x1024.pkl',
'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan3/versions/1/files/stylegan3-t-ffhqu-1024x1024.pkl',
'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan3/versions/1/files/stylegan3-t-ffhqu-256x256.pkl',
'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan3/versions/1/files/stylegan3-t-metfaces-1024x1024.pkl',
'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan3/versions/1/files/stylegan3-t-metfacesu-1024x1024.pkl',
'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan2/versions/1/files/stylegan2-afhqcat-512x512.pkl',
'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan2/versions/1/files/stylegan2-afhqdog-512x512.pkl',
'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan2/versions/1/files/stylegan2-afhqv2-512x512.pkl',
'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan2/versions/1/files/stylegan2-afhqwild-512x512.pkl',
'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan2/versions/1/files/stylegan2-brecahad-512x512.pkl',
'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan2/versions/1/files/stylegan2-celebahq-256x256.pkl',
'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan2/versions/1/files/stylegan2-cifar10-32x32.pkl',
'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan2/versions/1/files/stylegan2-ffhq-1024x1024.pkl',
'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan2/versions/1/files/stylegan2-ffhq-256x256.pkl',
'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan2/versions/1/files/stylegan2-ffhq-512x512.pkl',
'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan2/versions/1/files/stylegan2-ffhqu-1024x1024.pkl',
'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan2/versions/1/files/stylegan2-ffhqu-256x256.pkl',
'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan2/versions/1/files/stylegan2-lsundog-256x256.pkl',
'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan2/versions/1/files/stylegan2-metfaces-1024x1024.pkl',
'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan2/versions/1/files/stylegan2-metfacesu-1024x1024.pkl'
]
# Populate recent pickles list with pretrained model URLs.
for url in pretrained:
viz.add_recent_pickle(url)
if overwrite_bodypose_params is not None:
if Path(overwrite_bodypose_params).suffix == ".npy":
info = np.load(overwrite_bodypose_params)
elif Path(overwrite_bodypose_params).suffix == ".mat":
info = scipy.io.loadmat(overwrite_bodypose_params)['pose'].transpose()
else:
info = None
else:
info = None
print(f'Total frames: {info.shape[0]}')
i = 0
# Run.
while not viz.should_close():
print(f'Frame: {i}')
# if i == info.shape[0]-1:
# LATENT INTERP LINE 2
# viz.latent_widget.latent.x = 0.
viz.draw_frame(i, info, side_by_side_pkl, write_out_image, read_in_canonpose, write_output_frames)
if info is not None:
i = (i + 1) % info.shape[0]
viz.close()
#----------------------------------------------------------------------------
if __name__ == "__main__":
main()
#----------------------------------------------------------------------------