Modulable printer for video streaming (#4)
* Add modulable printer * remove errors * add modularity in printer * Fixed Small bugs * Fixed small bugs * Add modulable printer * remove errors * "Rebasing" * Fixed Small bugs * Fixed small bugs * Added save option
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george-adaimi
GitHub
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2b23bb9c9e
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0207a54a2c
@ -80,9 +80,10 @@ def factory_outputs(args, images_outputs, output_path, pifpaf_outputs, monoloco_
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epistemic = True
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if dic_out['boxes']: # Only print in case of detections
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printer = Printer(images_outputs[1], output_path, dic_out, kk, output_types=args.output_types,
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printer = Printer(images_outputs[1], output_path, kk, output_types=args.output_types,
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show=args.show, z_max=args.z_max, epistemic=epistemic)
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printer.print()
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figures, axes = printer.factory_axes()
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printer.draw(figures, axes, dic_out)
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if 'json' in args.output_types:
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with open(os.path.join(output_path + '.monoloco.json'), 'w') as ff:
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@ -24,23 +24,27 @@ class Printer:
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TEXTCOLOR = 'darkorange'
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COLOR_KPS = 'yellow'
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def __init__(self, image, output_path, dic_ann, kk, output_types, show=False,
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draw_kps=False, text=True, legend=True, epistemic=False, z_max=30, fig_width=10):
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def __init__(self, image, output_path, kk, output_types, show=False,
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text=True, legend=True, epistemic=False, z_max=30, fig_width=10):
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self.im = image
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self.kk = kk
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self.output_types = output_types
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self.show = show
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self.draw_kps = draw_kps
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self.text = text
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self.epistemic = epistemic
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self.legend = legend
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self.z_max = z_max # To include ellipses in the image
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self.y_scale = 1
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self.ww = self.im.size[0]
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self.hh = self.im.size[1]
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self.fig_width = fig_width
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# Define the output dir
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self.path_out = output_path
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self.cmap = cm.get_cmap('jet')
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def _process_input(self, dic_ann):
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# Include the vectors inside the interval given by z_max
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self.stds_ale = dic_ann['stds_ale']
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self.stds_ale_epi = dic_ann['stds_epi']
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@ -51,59 +55,55 @@ class Printer:
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self.zz_pred = [xx[2] if xx[2] < self.z_max - self.stds_ale_epi[idx] else 0
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for idx, xx in enumerate(dic_ann['xyz_pred'])]
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self.dds_real = dic_ann['dds_real']
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self.uv_centers = dic_ann['uv_centers']
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self.uv_shoulders = dic_ann['uv_shoulders']
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self.uv_kps = dic_ann['uv_kps']
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self.uv_camera = (int(self.im.size[0] / 2), self.im.size[1])
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self.ww = self.im.size[0]
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self.hh = self.im.size[1]
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self.radius = 14 / 1600 * self.ww
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self.ext = ".png"
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def print(self):
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"""
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Show frontal, birds-eye-view or combined visualization
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With or without ground truth
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Either front and/or bird visualization or combined one
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"""
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# Parameters
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# Resize image for aesthetic proportions in combined visualization
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def factory_axes(self):
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axes = []
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figures = []
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self.mpl_im0 = None
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# Resize image for aesthetic proportions in combined visualization
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if 'combined' in self.output_types:
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y_scale = self.ww / (self.hh * 1.8) # Defined proportion
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self.im = self.im.resize((self.ww, round(self.hh * y_scale)))
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self.y_scale = self.ww / (self.hh * 1.8) # Defined proportion
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self.im = self.im.resize((self.ww, round(self.hh * self.y_scale)))
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self.ww = self.im.size[0]
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self.hh = self.im.size[1]
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fig_width = self.fig_width + 0.6 * self.fig_width
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fig_height = self.fig_width * self.hh / self.ww
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# Distinguish between KITTI images and general images
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if y_scale > 1.7:
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if self.y_scale > 1.7:
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fig_ar_1 = 1.7
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else:
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fig_ar_1 = 1.3
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width_ratio = 1.9
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ext = '.combined.png'
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self.ext = '.combined.png'
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fig, (ax1, ax0) = plt.subplots(1, 2, sharey=False, gridspec_kw={'width_ratios': [1, width_ratio]},
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figsize=(fig_width, fig_height))
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ax1.set_aspect(fig_ar_1)
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fig.set_tight_layout(True)
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fig.subplots_adjust(left=0.02, right=0.98, bottom=0, top=1, hspace=0, wspace=0.02)
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figures.append(fig)
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assert 'front' not in self.output_types and 'bird' not in self.output_types, \
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"--combined arguments is not supported with other visualizations"
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# Initialize front
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elif 'front' in self.output_types:
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y_scale = 1
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width = self.fig_width
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height = self.fig_width * self.hh / self.ww
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self.ext = ".front.png"
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plt.figure(0)
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fig0, ax0 = plt.subplots(1, 1, figsize=(width, height))
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fig0.set_tight_layout(True)
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figures.append(fig0)
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# Create front
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if any(xx in self.output_types for xx in ['front', 'combined']):
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@ -111,27 +111,9 @@ class Printer:
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ax0.set_axis_off()
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ax0.set_xlim(0, self.ww)
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ax0.set_ylim(self.hh, 0)
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ax0.imshow(self.im)
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self.mpl_im0 = ax0.imshow(self.im)
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z_min = 0
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bar_ticks = self.z_max // 5 + 1
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cmap = cm.get_cmap('jet')
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num = 0
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for idx, uv in enumerate(self.uv_shoulders):
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if self.draw_kps:
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ax0 = self.show_kps(ax0, self.uv_kps[idx], y_scale, self.RADIUS_KPS, self.COLOR_KPS)
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elif min(self.zz_pred[idx], self.zz_gt[idx]) > 0:
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color = cmap((self.zz_pred[idx] % self.z_max) / self.z_max)
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circle = Circle((uv[0], uv[1] * y_scale), radius=self.radius, color=color, fill=True)
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ax0.add_patch(circle)
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if self.text:
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ax0.text(uv[0]+self.radius, uv[1] * y_scale - self.radius, str(num),
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fontsize=self.FONTSIZE, color=self.TEXTCOLOR, weight='bold')
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num += 1
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ax0.get_xaxis().set_visible(False)
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ax0.get_yaxis().set_visible(False)
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@ -139,31 +121,59 @@ class Printer:
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cax = divider.append_axes('right', size='3%', pad=0.05)
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norm = matplotlib.colors.Normalize(vmin=z_min, vmax=self.z_max)
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sm = plt.cm.ScalarMappable(cmap=cmap, norm=norm)
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sm = plt.cm.ScalarMappable(cmap=self.cmap, norm=norm)
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sm.set_array([])
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plt.colorbar(sm, ticks=np.linspace(z_min, self.z_max, bar_ticks),
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boundaries=np.arange(z_min - 0.05, self.z_max + 0.1, .1), cax=cax, label='Z [m]')
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# Save Front
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if 'front' in self.output_types:
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if self.show:
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plt.show()
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else:
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plt.savefig(self.path_out + '.front.png', bbox_inches='tight')
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axes.append(ax0)
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if len(axes) == 0:
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axes.append(None)
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# Initialize Bird
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if 'bird' in self.output_types:
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plt.close()
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self.ext = ".bird.png" #TODO multiple savings external
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plt.figure(1)
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ext = '.bird.png'
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fig1, ax1 = plt.subplots(1, 1)
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fig1.set_tight_layout(True)
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# Create bird or combine it with front)
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figures.append(fig1)
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if any(xx in self.output_types for xx in ['bird', 'combined']):
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uv_max = [0., float(self.hh)]
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xyz_max = pixel_to_camera(uv_max, self.kk, self.z_max)
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x_max = abs(xyz_max[0]) # shortcut to avoid oval circles in case of different kk
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# To avoid repetitions in the legend
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if self.legend:
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handles, labels = ax1.get_legend_handles_labels()
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by_label = OrderedDict(zip(labels, handles))
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ax1.legend(by_label.values(), by_label.keys())
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# Adding field of view
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ax1.plot([0, x_max], [0, self.z_max], 'k--')
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ax1.plot([0, -x_max], [0, self.z_max], 'k--')
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ax1.set_ylim(0, self.z_max+1)
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ax1.set_xlabel("X [m]")
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ax1.set_ylabel("Z [m]")
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axes.append(ax1)
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return figures, axes
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def draw(self, figures, axes, dic_ann, image, save=False):
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self._process_input(dic_ann)
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num = 0
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if any(xx in self.output_types for xx in ['front', 'combined']):
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self.mpl_im0.set_data(image)
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for idx, uv in enumerate(self.uv_shoulders):
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if min(self.zz_pred[idx], self.zz_gt[idx]) > 0:
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color = self.cmap((self.zz_pred[idx] % self.z_max) / self.z_max)
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circle = Circle((uv[0], uv[1] * self.y_scale), radius=self.radius, color=color, fill=True)
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axes[0].add_patch(circle)
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if self.text:
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axes[0].text(uv[0]+self.radius, uv[1] * self.y_scale - self.radius, str(num),
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fontsize=self.FONTSIZE, color=self.TEXTCOLOR, weight='bold')
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num += 1
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if any(xx in self.output_types for xx in ['bird', 'combined']):
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for idx, _ in enumerate(self.xx_gt):
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if self.zz_gt[idx] > 0:
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target = get_task_error(self.dds_real[idx])
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@ -171,8 +181,8 @@ class Printer:
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angle = get_angle(self.xx_gt[idx], self.zz_gt[idx])
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ellipse_real = Ellipse((self.xx_gt[idx], self.zz_gt[idx]), width=target * 2, height=1,
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angle=angle, color='lightgreen', fill=True, label="Task error")
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ax1.add_patch(ellipse_real)
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ax1.plot(self.xx_gt[idx], self.zz_gt[idx], 'kx', label="Ground truth", markersize=3)
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axes[1].add_patch(ellipse_real)
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axes[1].plot(self.xx_gt[idx], self.zz_gt[idx], 'kx', label="Ground truth", markersize=3)
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# Print prediction and the real ground truth. Color of prediction depends if ground truth exists
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num = 0
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@ -187,72 +197,23 @@ class Printer:
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height=1, angle=angle, color='r', fill=False, label="Uncertainty",
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linewidth=1, linestyle='--')
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ax1.add_patch(ellipse_ale)
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axes[1].add_patch(ellipse_ale)
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if self.epistemic:
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ax1.add_patch(ellipse_var)
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axes[1].add_patch(ellipse_var)
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ax1.plot(self.xx_pred[idx], self.zz_pred[idx], 'ro', label="Predicted", markersize=3)
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axes[1].plot(self.xx_pred[idx], self.zz_pred[idx], 'ro', label="Predicted", markersize=3)
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# Plot the number
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if not self.draw_kps:
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(_, x_pos), (_, z_pos) = get_confidence(self.xx_pred[idx], self.zz_pred[idx], self.stds_ale_epi[idx])
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(_, x_pos), (_, z_pos) = get_confidence(self.xx_pred[idx], self.zz_pred[idx], self.stds_ale_epi[idx])
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if self.text:
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ax1.text(x_pos, z_pos, str(num), fontsize=self.FONTSIZE_BV, color='darkorange')
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num += 1
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# To avoid repetitions in the legend
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if self.legend:
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handles, labels = ax1.get_legend_handles_labels()
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by_label = OrderedDict(zip(labels, handles))
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ax1.legend(by_label.values(), by_label.keys())
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# Adding field of view
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ax1.plot([0, x_max], [0, self.z_max], 'k--')
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ax1.plot([0, -x_max], [0, self.z_max], 'k--')
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ax1.set_ylim(0, self.z_max+1)
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ax1.set_xlabel("X [m]")
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ax1.set_ylabel("Z [m]")
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# TO remove axis numbers
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# plt.setp([ax1.get_yticklabels() for aa in fig.axes[:-1]], visible=False)
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# plt.setp([ax1.get_xticklabels() for aa in fig.axes[:-1]], visible=False)
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if self.show:
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plt.show()
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else:
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plt.savefig(self.path_out + ext, bbox_inches='tight')
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if self.draw_kps:
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im = cv2.imread(self.path_out + ext)
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im = self.increase_brightness(im, value=30)
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im_new = im[0 : self.hh, 0:round(self.ww / 1.7)]
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cv2.imwrite(self.path_out, im_new)
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plt.close('all')
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def show_kps(self, ax0, uv_kp_single, y_scale, radius, color):
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for idx, uu in enumerate(uv_kp_single[0]):
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vv = uv_kp_single[1][idx]
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circle = Circle((uu, vv * y_scale), radius=radius, color=color, fill=True)
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ax0.add_patch(circle)
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return ax0
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@staticmethod
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def increase_brightness(img, value=30):
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hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
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h, s, v = cv2.split(hsv)
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lim = 255 - value
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v[v > lim] = 255
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v[v <= lim] += value
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final_hsv = cv2.merge((h, s, v))
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img = cv2.cvtColor(final_hsv, cv2.COLOR_HSV2BGR)
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return img
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if self.text:
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axes[1].text(x_pos, z_pos, str(num), fontsize=self.FONTSIZE_BV, color='darkorange')
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num += 1
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for fig in figures:
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fig.canvas.draw()
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if save:
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plt.savefig(self.path_out + self.ext, bbox_inches='tight')
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def get_confidence(xx, zz, std):
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"""Obtain the points to plot the confidence of each annotation"""
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