diff options
Diffstat (limited to 'Code/utils.py')
| -rw-r--r-- | Code/utils.py | 12 |
1 files changed, 6 insertions, 6 deletions
diff --git a/Code/utils.py b/Code/utils.py index c2bf856..042912e 100644 --- a/Code/utils.py +++ b/Code/utils.py @@ -1,6 +1,6 @@ import tensorflow as tf import numpy as np -from scipy.ndimage import imread +from scipy.misc import imread from glob import glob import os @@ -69,14 +69,14 @@ def get_full_clips(data_dir, num_clips, num_rec_out=1): A batch of frame sequences with values normalized in range [-1, 1]. """ clips = np.empty([num_clips, - c.TEST_HEIGHT, - c.TEST_WIDTH, + c.FULL_HEIGHT, + c.FULL_WIDTH, (3 * (c.HIST_LEN + num_rec_out))]) # get num_clips random episodes ep_dirs = np.random.choice(glob(data_dir + '*'), num_clips) - # get a random clip of length HIST_LEN + 1 from each episode + # get a random clip of length HIST_LEN + num_rec_out from each episode for clip_num, ep_dir in enumerate(ep_dirs): ep_frame_paths = glob(os.path.join(ep_dir, '*')) start_index = np.random.choice(len(ep_frame_paths) - (c.HIST_LEN + num_rec_out - 1)) @@ -105,8 +105,8 @@ def process_clip(): take_first = np.random.choice(2, p=[0.95, 0.05]) cropped_clip = np.empty([c.TRAIN_HEIGHT, c.TRAIN_WIDTH, 3 * (c.HIST_LEN + 1)]) for i in xrange(100): # cap at 100 trials in case the clip has no movement anywhere - crop_x = np.random.choice(c.TEST_WIDTH - c.TRAIN_WIDTH + 1) - crop_y = np.random.choice(c.TEST_HEIGHT - c.TRAIN_HEIGHT + 1) + crop_x = np.random.choice(c.FULL_WIDTH - c.TRAIN_WIDTH + 1) + crop_y = np.random.choice(c.FULL_HEIGHT - c.TRAIN_HEIGHT + 1) cropped_clip = clip[crop_y:crop_y + c.TRAIN_HEIGHT, crop_x:crop_x + c.TRAIN_WIDTH, :] if take_first or clip_l2_diff(cropped_clip) > c.MOVEMENT_THRESHOLD: |