| from __future__ import print_function, unicode_literals |
| import matplotlib.pyplot as plt |
| import argparse |
|
|
| from utils.fh_utils import * |
|
|
|
|
| def show_training_samples(base_path, version, num2show=None, render_mano=False): |
| if render_mano: |
| from utils.model import HandModel, recover_root, get_focal_pp, split_theta |
|
|
| if num2show == -1: |
| num2show = db_size('training') |
|
|
| |
| db_data_anno = load_db_annotation(base_path, 'training') |
|
|
| |
| for idx in range(db_size('training')): |
| if idx >= num2show: |
| break |
|
|
| |
| img = read_img(idx, base_path, 'training', version) |
| msk = read_msk(idx, base_path) |
|
|
| |
| K, mano, xyz = db_data_anno[idx] |
| K, mano, xyz = [np.array(x) for x in [K, mano, xyz]] |
| uv = projectPoints(xyz, K) |
|
|
| |
| msk_rendered = None |
| if render_mano: |
| |
| poses, shapes, uv_root, scale = split_theta(mano) |
| focal, pp = get_focal_pp(K) |
| xyz_root = recover_root(uv_root, scale, focal, pp) |
|
|
| |
| renderer = HandModel(use_mean_pca=False, use_mean_pose=True) |
| renderer.pose_by_root(xyz_root[0], poses[0], shapes[0]) |
| msk_rendered = renderer.render(K, img_shape=img.shape[:2]) |
|
|
| |
| fig = plt.figure() |
| ax1 = fig.add_subplot(121) |
| ax2 = fig.add_subplot(122) |
| ax1.imshow(img) |
| ax2.imshow(msk if msk_rendered is None else msk_rendered) |
| plot_hand(ax1, uv, order='uv') |
| plot_hand(ax2, uv, order='uv') |
| ax1.axis('off') |
| ax2.axis('off') |
| plt.show() |
|
|
|
|
| def show_eval_samples(base_path, num2show=None): |
| if num2show == -1: |
| num2show = db_size('evaluation') |
|
|
| for idx in range(db_size('evaluation')): |
| if idx >= num2show: |
| break |
|
|
| |
| img = read_img(idx, base_path, 'evaluation') |
|
|
| |
| fig = plt.figure() |
| ax1 = fig.add_subplot(111) |
| ax1.imshow(img) |
| ax1.axis('off') |
| plt.show() |
|
|
|
|
| if __name__ == '__main__': |
| parser = argparse.ArgumentParser(description='Show some samples from the dataset.') |
| parser.add_argument('base_path', type=str, |
| help='Path to where the FreiHAND dataset is located.') |
| parser.add_argument('--show_eval', action='store_true', |
| help='Shows samples from the evaluation split if flag is set, shows training split otherwise.') |
| parser.add_argument('--mano', action='store_true', |
| help='Enables rendering of the hand if mano is available. See README for details.') |
| parser.add_argument('--num2show', type=int, default=-1, |
| help='Number of samples to show. ''-1'' defaults to show all.') |
| parser.add_argument('--sample_version', type=str, default=sample_version.gs, |
| help='Which sample version to use when showing the training set.' |
| ' Valid choices are %s' % sample_version.valid_options()) |
| args = parser.parse_args() |
|
|
| |
| msg = 'Invalid choice: ''%s''. Must be in %s' % (args.sample_version, sample_version.valid_options()) |
| assert args.sample_version in sample_version.valid_options(), msg |
|
|
| if args.show_eval: |
| """ Show some evaluation samples. """ |
| show_eval_samples(args.base_path, |
| num2show=args.num2show) |
|
|
| else: |
| """ Show some training samples. """ |
| show_training_samples( |
| args.base_path, |
| args.sample_version, |
| num2show=args.num2show, |
| render_mano=args.mano |
| ) |
|
|
|
|
