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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 torch |
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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 drag_widget |
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from viz import capture_widget |
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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='DragGAN', window_width=3840, window_height=2160) |
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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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self._mask_obj = None |
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self._image_area = None |
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self._status = dnnlib.EasyDict() |
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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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self.image_w = 0 |
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self.image_h = 0 |
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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.drag_widget = drag_widget.DragWidget(self) |
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self.capture_widget = capture_widget.CaptureWidget(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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self.set_position(0, 0) |
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self._adjust_font_size() |
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self.skip_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() |
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def check_update_mask(self, **args): |
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update_mask = False |
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if 'pkl' in self._status: |
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if self._status.pkl != args['pkl']: |
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update_mask = True |
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self._status.pkl = args['pkl'] |
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if 'w0_seed' in self._status: |
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if self._status.w0_seed != args['w0_seed']: |
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update_mask = True |
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self._status.w0_seed = args['w0_seed'] |
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return update_mask |
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def capture_image_frame(self): |
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self.capture_next_frame() |
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captured_frame = self.pop_captured_frame() |
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captured_image = None |
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if captured_frame is not None: |
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x1, y1, w, h = self._image_area |
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captured_image = captured_frame[y1:y1+h, x1:x1+w, :] |
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return captured_image |
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def get_drag_info(self): |
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seed = self.latent_widget.seed |
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points = self.drag_widget.points |
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targets = self.drag_widget.targets |
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mask = self.drag_widget.mask |
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w = self._async_renderer._renderer_obj.w |
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return seed, points, targets, mask, w |
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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 * 18 |
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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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if self._image_area is not None: |
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if not hasattr(self.drag_widget, 'width'): |
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self.drag_widget.init_mask(self.image_w, self.image_h) |
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clicked, down, img_x, img_y = imgui_utils.click_hidden_window( |
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'##image_area', self._image_area[0], self._image_area[1], self._image_area[2], self._image_area[3], self.image_w, self.image_h) |
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self.drag_widget.action(clicked, down, img_x, img_y) |
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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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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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expanded, _visible = imgui_utils.collapsing_header('Drag', default=True) |
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self.drag_widget(expanded) |
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expanded, _visible = imgui_utils.collapsing_header('Capture', default=True) |
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self.capture_widget(expanded) |
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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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if 'stop' in self.result and self.result.stop: |
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self.drag_widget.stop_drag() |
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if 'points' in self.result: |
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self.drag_widget.set_points(self.result.points) |
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if 'init_net' in self.result: |
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if self.result.init_net: |
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self.drag_widget.reset_point() |
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if self.check_update_mask(**self.args): |
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h, w, _ = self.result.image.shape |
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self.drag_widget.init_mask(w, h) |
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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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self.image_h, self.image_w = self._tex_obj.height, self._tex_obj.width |
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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 self.drag_widget.show_mask and hasattr(self.drag_widget, 'mask'): |
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mask = ((1-self.drag_widget.mask.unsqueeze(-1)) * 255).to(torch.uint8) |
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if self._mask_obj is None or not self._mask_obj.is_compatible(image=self._tex_img): |
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self._mask_obj = gl_utils.Texture(image=mask, bilinear=False, mipmap=False) |
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else: |
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self._mask_obj.update(mask) |
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self._mask_obj.draw(pos=pos, zoom=zoom, align=0.5, rint=True, alpha=0.15) |
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if self.drag_widget.mode in ['flexible', 'fixed']: |
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posx, posy = imgui.get_mouse_pos() |
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if posx >= self.pane_w: |
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pos_c = np.array([posx, posy]) |
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gl_utils.draw_circle(center=pos_c, radius=self.drag_widget.r_mask * zoom, alpha=0.5) |
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rescale = self._tex_obj.width / 512 * zoom |
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for point in self.drag_widget.targets: |
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pos_x = self.pane_w + max_w / 2 + (point[1] - self.image_w//2) * zoom |
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pos_y = max_h / 2 + (point[0] - self.image_h//2) * zoom |
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gl_utils.draw_circle(center=np.array([pos_x, pos_y]), color=[0,0,1], radius=9 * rescale) |
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for point in self.drag_widget.points: |
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pos_x = self.pane_w + max_w / 2 + (point[1] - self.image_w//2) * zoom |
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pos_y = max_h / 2 + (point[0] - self.image_h//2) * zoom |
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gl_utils.draw_circle(center=np.array([pos_x, pos_y]), color=[1,0,0], radius=9 * rescale) |
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for point, target in zip(self.drag_widget.points, self.drag_widget.targets): |
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t_x = self.pane_w + max_w / 2 + (target[1] - self.image_w//2) * zoom |
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t_y = max_h / 2 + (target[0] - self.image_h//2) * zoom |
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p_x = self.pane_w + max_w / 2 + (point[1] - self.image_w//2) * zoom |
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p_y = max_h / 2 + (point[0] - self.image_h//2) * zoom |
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gl_utils.draw_arrow(p_x, p_y, t_x, t_y, l=8 * rescale, width = 3 * rescale) |
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imshow_w = int(self._tex_obj.width * zoom) |
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imshow_h = int(self._tex_obj.height * zoom) |
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self._image_area = [int(self.pane_w + max_w / 2 - imshow_w / 2), int(max_h / 2 - imshow_h / 2), imshow_w, imshow_h] |
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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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self._adjust_font_size() |
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imgui.end() |
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self.end_frame() |
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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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args2 = args.copy() |
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args_mask = args2.pop('mask') |
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if self._cur_args: |
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_cur_args = self._cur_args.copy() |
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cur_args_mask = _cur_args.pop('mask') |
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else: |
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_cur_args = self._cur_args |
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if args2 != _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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@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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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/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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for url in pretrained: |
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viz.add_recent_pickle(url) |
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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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if __name__ == "__main__": |
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main() |
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