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from PIL import Image
import matplotlib.pyplot as plt
# Log images
def log_input_image(x, opts):
return tensor2im(x)
def tensor2im(var):
# var shape: (3, H, W)
var = var.cpu().detach().transpose(0, 2).transpose(0, 1).numpy()
var = ((var + 1) / 2)
var[var < 0] = 0
var[var > 1] = 1
var = var * 255
return Image.fromarray(var.astype('uint8'))
def vis_faces(log_hooks):
display_count = len(log_hooks)
fig = plt.figure(figsize=(8, 4 * display_count))
gs = fig.add_gridspec(display_count, 3)
for i in range(display_count):
hooks_dict = log_hooks[i]
fig.add_subplot(gs[i, 0])
if 'diff_input' in hooks_dict:
vis_faces_with_id(hooks_dict, fig, gs, i)
else:
vis_faces_no_id(hooks_dict, fig, gs, i)
plt.tight_layout()
return fig
def vis_faces_with_id(hooks_dict, fig, gs, i):
plt.imshow(hooks_dict['input_face'])
plt.title('Input\nOut Sim={:.2f}'.format(float(hooks_dict['diff_input'])))
fig.add_subplot(gs[i, 1])
plt.imshow(hooks_dict['target_face'])
plt.title('Target\nIn={:.2f}, Out={:.2f}'.format(float(hooks_dict['diff_views']),
float(hooks_dict['diff_target'])))
fig.add_subplot(gs[i, 2])
plt.imshow(hooks_dict['output_face'])
plt.title('Output\n Target Sim={:.2f}'.format(float(hooks_dict['diff_target'])))
def vis_faces_no_id(hooks_dict, fig, gs, i):
plt.imshow(hooks_dict['input_face'], cmap="gray")
plt.title('Input')
fig.add_subplot(gs[i, 1])
plt.imshow(hooks_dict['target_face'])
plt.title('Target')
fig.add_subplot(gs[i, 2])
plt.imshow(hooks_dict['output_face'])
plt.title('Output')
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