# Set up data fetch camera_fps = [tf.placeholder(tf.string) for i in range(prm.batch_size)] pts_xyz_fps = [tf.placeholder(tf.string) for i in range(prm.batch_size)] pts_rgb_fps = [tf.placeholder(tf.string) for i in range(prm.batch_size)] pts_sift_fps = [tf.placeholder(tf.string) for i in range(prm.batch_size)] gt_depth_fps = [tf.placeholder(tf.string) for i in range(prm.batch_size)] getfeed = lambda fps: \ dict([(ph,'data/'+fps[i,3]) for i,ph in enumerate(camera_fps)]+\ [(ph,'data/'+fps[i,0]) for i,ph in enumerate(pts_xyz_fps)]+\ [(ph,'data/'+fps[i,2]) for i,ph in enumerate(pts_sift_fps)]+\ [(ph,'data/'+fps[i,1]) for i,ph in enumerate(pts_rgb_fps)]+\ [(ph,'data/'+fps[i,5]) for i,ph in enumerate(gt_depth_fps)]) gt_depth = ld.load_img_bch(gt_depth_fps, prm.crop_size, prm.scale_size, isval=False, binary=True) proj_depth, proj_sift, proj_rgb = ld.load_proj_bch(camera_fps, pts_xyz_fps, pts_sift_fps, pts_rgb_fps, prm.crop_size, prm.scale_size, isval=False) pd_b = [] ps_b = [] pr_b = [] is_visible = [] is_valid = []
# Set up data fetch camera_fps = [tf.placeholder(tf.string) for i in range(prm.batch_size)] pts_xyz_fps = [tf.placeholder(tf.string) for i in range(prm.batch_size)] pts_rgb_fps = [tf.placeholder(tf.string) for i in range(prm.batch_size)] pts_sift_fps = [tf.placeholder(tf.string) for i in range(prm.batch_size)] gt_rgb_fps = [tf.placeholder(tf.string) for i in range(prm.batch_size)] getfeed = lambda fps: \ dict([(ph,'data/'+fps[i,3]) for i,ph in enumerate(camera_fps)]+\ [(ph,'data/'+fps[i,0]) for i,ph in enumerate(pts_xyz_fps)]+\ [(ph,'data/'+fps[i,2]) for i,ph in enumerate(pts_sift_fps)]+\ [(ph,'data/'+fps[i,1]) for i,ph in enumerate(pts_rgb_fps)]+\ [(ph,'data/'+fps[i,4]) for i,ph in enumerate(gt_rgb_fps)]) gt_rgb = ld.load_img_bch(gt_rgb_fps, prm.crop_size, prm.scale_size, isval=False, binary=False) proj_depth, proj_sift, proj_rgb = ld.load_proj_bch(camera_fps, pts_xyz_fps, pts_sift_fps, pts_rgb_fps, prm.crop_size, prm.scale_size, isval=False) pd_b = [] ps_b = [] pr_b = [] is_visible = [] is_valid = []