583f2bdd13
BOMs barf on UTF-8 decoding within PyTorch:
File "D:\Soft\Miniconda3\lib\site-packages\torch\utils_cpp_extension_versioner.py", line 16, in hash_source_files
hash_value = update_hash(hash_value, file.read())
UnicodeDecodeError: 'gbk' codec can't decode byte 0xbf in position 2: illegal multibyte sequence
Should fix #10, #14
334 lines
14 KiB
Python
334 lines
14 KiB
Python
# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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#
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# NVIDIA CORPORATION and its licensors retain all intellectual property
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# and proprietary rights in and to this software, related documentation
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# and any modifications thereto. Any use, reproduction, disclosure or
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# distribution of this software and related documentation without an express
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# license agreement from NVIDIA CORPORATION is strictly prohibited.
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import click
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import os
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import multiprocessing
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import numpy as np
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import imgui
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import dnnlib
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from gui_utils import imgui_window
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from gui_utils import imgui_utils
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from gui_utils import gl_utils
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from gui_utils import text_utils
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from viz import renderer
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from viz import pickle_widget
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from viz import latent_widget
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from viz import stylemix_widget
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from viz import trunc_noise_widget
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from viz import performance_widget
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from viz import capture_widget
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from viz import layer_widget
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from viz import equivariance_widget
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#----------------------------------------------------------------------------
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class Visualizer(imgui_window.ImguiWindow):
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def __init__(self, capture_dir=None):
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super().__init__(title='GAN Visualizer', window_width=3840, window_height=2160)
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# Internals.
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self._last_error_print = None
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self._async_renderer = AsyncRenderer()
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self._defer_rendering = 0
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self._tex_img = None
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self._tex_obj = None
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# Widget interface.
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self.args = dnnlib.EasyDict()
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self.result = dnnlib.EasyDict()
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self.pane_w = 0
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self.label_w = 0
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self.button_w = 0
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# Widgets.
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self.pickle_widget = pickle_widget.PickleWidget(self)
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self.latent_widget = latent_widget.LatentWidget(self)
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self.stylemix_widget = stylemix_widget.StyleMixingWidget(self)
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self.trunc_noise_widget = trunc_noise_widget.TruncationNoiseWidget(self)
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self.perf_widget = performance_widget.PerformanceWidget(self)
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self.capture_widget = capture_widget.CaptureWidget(self)
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self.layer_widget = layer_widget.LayerWidget(self)
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self.eq_widget = equivariance_widget.EquivarianceWidget(self)
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if capture_dir is not None:
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self.capture_widget.path = capture_dir
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# Initialize window.
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self.set_position(0, 0)
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self._adjust_font_size()
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self.skip_frame() # Layout may change after first frame.
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def close(self):
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super().close()
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if self._async_renderer is not None:
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self._async_renderer.close()
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self._async_renderer = None
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def add_recent_pickle(self, pkl, ignore_errors=False):
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self.pickle_widget.add_recent(pkl, ignore_errors=ignore_errors)
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def load_pickle(self, pkl, ignore_errors=False):
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self.pickle_widget.load(pkl, ignore_errors=ignore_errors)
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def print_error(self, error):
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error = str(error)
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if error != self._last_error_print:
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print('\n' + error + '\n')
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self._last_error_print = error
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def defer_rendering(self, num_frames=1):
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self._defer_rendering = max(self._defer_rendering, num_frames)
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def clear_result(self):
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self._async_renderer.clear_result()
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def set_async(self, is_async):
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if is_async != self._async_renderer.is_async:
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self._async_renderer.set_async(is_async)
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self.clear_result()
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if 'image' in self.result:
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self.result.message = 'Switching rendering process...'
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self.defer_rendering()
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def _adjust_font_size(self):
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old = self.font_size
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self.set_font_size(min(self.content_width / 120, self.content_height / 60))
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if self.font_size != old:
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self.skip_frame() # Layout changed.
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def draw_frame(self):
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self.begin_frame()
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self.args = dnnlib.EasyDict()
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self.pane_w = self.font_size * 45
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self.button_w = self.font_size * 5
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self.label_w = round(self.font_size * 4.5)
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# Detect mouse dragging in the result area.
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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)
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if dragging:
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self.latent_widget.drag(dx, dy)
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# Begin control pane.
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imgui.set_next_window_position(0, 0)
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imgui.set_next_window_size(self.pane_w, self.content_height)
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imgui.begin('##control_pane', closable=False, flags=(imgui.WINDOW_NO_TITLE_BAR | imgui.WINDOW_NO_RESIZE | imgui.WINDOW_NO_MOVE))
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# Widgets.
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expanded, _visible = imgui_utils.collapsing_header('Network & latent', default=True)
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self.pickle_widget(expanded)
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self.latent_widget(expanded)
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self.stylemix_widget(expanded)
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self.trunc_noise_widget(expanded)
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expanded, _visible = imgui_utils.collapsing_header('Performance & capture', default=True)
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self.perf_widget(expanded)
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self.capture_widget(expanded)
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expanded, _visible = imgui_utils.collapsing_header('Layers & channels', default=True)
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self.layer_widget(expanded)
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with imgui_utils.grayed_out(not self.result.get('has_input_transform', False)):
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expanded, _visible = imgui_utils.collapsing_header('Equivariance', default=True)
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self.eq_widget(expanded)
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# Render.
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if self.is_skipping_frames():
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pass
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elif self._defer_rendering > 0:
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self._defer_rendering -= 1
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elif self.args.pkl is not None:
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self._async_renderer.set_args(**self.args)
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result = self._async_renderer.get_result()
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if result is not None:
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self.result = result
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# Display.
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max_w = self.content_width - self.pane_w
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max_h = self.content_height
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pos = np.array([self.pane_w + max_w / 2, max_h / 2])
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if 'image' in self.result:
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if self._tex_img is not self.result.image:
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self._tex_img = self.result.image
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if self._tex_obj is None or not self._tex_obj.is_compatible(image=self._tex_img):
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self._tex_obj = gl_utils.Texture(image=self._tex_img, bilinear=False, mipmap=False)
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else:
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self._tex_obj.update(self._tex_img)
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zoom = min(max_w / self._tex_obj.width, max_h / self._tex_obj.height)
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zoom = np.floor(zoom) if zoom >= 1 else zoom
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self._tex_obj.draw(pos=pos, zoom=zoom, align=0.5, rint=True)
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if 'error' in self.result:
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self.print_error(self.result.error)
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if 'message' not in self.result:
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self.result.message = str(self.result.error)
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if 'message' in self.result:
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tex = text_utils.get_texture(self.result.message, size=self.font_size, max_width=max_w, max_height=max_h, outline=2)
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tex.draw(pos=pos, align=0.5, rint=True, color=1)
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# End frame.
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self._adjust_font_size()
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imgui.end()
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self.end_frame()
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#----------------------------------------------------------------------------
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class AsyncRenderer:
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def __init__(self):
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self._closed = False
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self._is_async = False
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self._cur_args = None
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self._cur_result = None
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self._cur_stamp = 0
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self._renderer_obj = None
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self._args_queue = None
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self._result_queue = None
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self._process = None
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def close(self):
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self._closed = True
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self._renderer_obj = None
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if self._process is not None:
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self._process.terminate()
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self._process = None
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self._args_queue = None
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self._result_queue = None
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@property
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def is_async(self):
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return self._is_async
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def set_async(self, is_async):
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self._is_async = is_async
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def set_args(self, **args):
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assert not self._closed
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if args != self._cur_args:
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if self._is_async:
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self._set_args_async(**args)
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else:
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self._set_args_sync(**args)
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self._cur_args = args
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def _set_args_async(self, **args):
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if self._process is None:
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self._args_queue = multiprocessing.Queue()
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self._result_queue = multiprocessing.Queue()
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try:
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multiprocessing.set_start_method('spawn')
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except RuntimeError:
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pass
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self._process = multiprocessing.Process(target=self._process_fn, args=(self._args_queue, self._result_queue), daemon=True)
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self._process.start()
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self._args_queue.put([args, self._cur_stamp])
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def _set_args_sync(self, **args):
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if self._renderer_obj is None:
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self._renderer_obj = renderer.Renderer()
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self._cur_result = self._renderer_obj.render(**args)
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def get_result(self):
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assert not self._closed
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if self._result_queue is not None:
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while self._result_queue.qsize() > 0:
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result, stamp = self._result_queue.get()
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if stamp == self._cur_stamp:
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self._cur_result = result
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return self._cur_result
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def clear_result(self):
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assert not self._closed
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self._cur_args = None
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self._cur_result = None
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self._cur_stamp += 1
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@staticmethod
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def _process_fn(args_queue, result_queue):
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renderer_obj = renderer.Renderer()
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cur_args = None
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cur_stamp = None
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while True:
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args, stamp = args_queue.get()
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while args_queue.qsize() > 0:
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args, stamp = args_queue.get()
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if args != cur_args or stamp != cur_stamp:
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result = renderer_obj.render(**args)
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if 'error' in result:
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result.error = renderer.CapturedException(result.error)
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result_queue.put([result, stamp])
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cur_args = args
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cur_stamp = stamp
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#----------------------------------------------------------------------------
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@click.command()
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@click.argument('pkls', metavar='PATH', nargs=-1)
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@click.option('--capture-dir', help='Where to save screenshot captures', metavar='PATH', default=None)
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@click.option('--browse-dir', help='Specify model path for the \'Browse...\' button', metavar='PATH')
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def main(
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pkls,
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capture_dir,
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browse_dir
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):
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"""Interactive model visualizer.
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Optional PATH argument can be used specify which .pkl file to load.
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"""
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viz = Visualizer(capture_dir=capture_dir)
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if browse_dir is not None:
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viz.pickle_widget.search_dirs = [browse_dir]
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# List pickles.
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if len(pkls) > 0:
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for pkl in pkls:
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viz.add_recent_pickle(pkl)
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viz.load_pickle(pkls[0])
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else:
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pretrained = [
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'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan3/versions/1/files/stylegan3-r-afhqv2-512x512.pkl',
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'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan3/versions/1/files/stylegan3-r-ffhq-1024x1024.pkl',
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'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan3/versions/1/files/stylegan3-r-ffhqu-1024x1024.pkl',
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'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan3/versions/1/files/stylegan3-r-ffhqu-256x256.pkl',
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'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan3/versions/1/files/stylegan3-r-metfaces-1024x1024.pkl',
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'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan3/versions/1/files/stylegan3-r-metfacesu-1024x1024.pkl',
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'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan3/versions/1/files/stylegan3-t-afhqv2-512x512.pkl',
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'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan3/versions/1/files/stylegan3-t-ffhq-1024x1024.pkl',
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'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan3/versions/1/files/stylegan3-t-ffhqu-1024x1024.pkl',
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'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan3/versions/1/files/stylegan3-t-ffhqu-256x256.pkl',
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'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan3/versions/1/files/stylegan3-t-metfaces-1024x1024.pkl',
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'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan3/versions/1/files/stylegan3-t-metfacesu-1024x1024.pkl',
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'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan2/versions/1/files/stylegan2-afhqcat-512x512.pkl',
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'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan2/versions/1/files/stylegan2-afhqdog-512x512.pkl',
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'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan2/versions/1/files/stylegan2-afhqv2-512x512.pkl',
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'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan2/versions/1/files/stylegan2-afhqwild-512x512.pkl',
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'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan2/versions/1/files/stylegan2-brecahad-512x512.pkl',
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'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan2/versions/1/files/stylegan2-celebahq-256x256.pkl',
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'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan2/versions/1/files/stylegan2-cifar10-32x32.pkl',
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'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan2/versions/1/files/stylegan2-ffhq-1024x1024.pkl',
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'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan2/versions/1/files/stylegan2-ffhq-256x256.pkl',
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'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan2/versions/1/files/stylegan2-ffhq-512x512.pkl',
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'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan2/versions/1/files/stylegan2-ffhqu-1024x1024.pkl',
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'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan2/versions/1/files/stylegan2-ffhqu-256x256.pkl',
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'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan2/versions/1/files/stylegan2-lsundog-256x256.pkl',
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'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan2/versions/1/files/stylegan2-metfaces-1024x1024.pkl',
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'https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan2/versions/1/files/stylegan2-metfacesu-1024x1024.pkl'
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]
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# Populate recent pickles list with pretrained model URLs.
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for url in pretrained:
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viz.add_recent_pickle(url)
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# Run.
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while not viz.should_close():
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viz.draw_frame()
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viz.close()
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#----------------------------------------------------------------------------
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if __name__ == "__main__":
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main()
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#----------------------------------------------------------------------------
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