diff options
| -rw-r--r-- | Code/avg_runner.py | 6 | ||||
| -rw-r--r-- | Code/constants.py | 16 | ||||
| -rw-r--r-- | Code/process_data.py | 5 | ||||
| -rw-r--r-- | Code/utils.py | 12 |
4 files changed, 26 insertions, 13 deletions
diff --git a/Code/avg_runner.py b/Code/avg_runner.py index 18bc592..9a27426 100644 --- a/Code/avg_runner.py +++ b/Code/avg_runner.py @@ -42,8 +42,8 @@ class AVGRunner: self.summary_writer, c.TRAIN_HEIGHT, c.TRAIN_WIDTH, - c.TEST_HEIGHT, - c.TEST_WIDTH, + c.FULL_HEIGHT, + c.FULL_WIDTH, c.SCALE_FMS_G, c.SCALE_KERNEL_SIZES_G) @@ -161,7 +161,7 @@ def main(): # set test frame dimensions assert os.path.exists(c.TEST_DIR) - c.TEST_HEIGHT, c.TEST_WIDTH = c.get_test_frame_dims() + c.FULL_HEIGHT, c.FULL_WIDTH = c.get_test_frame_dims() ## # Init and run the predictor diff --git a/Code/constants.py b/Code/constants.py index dfd3660..761448b 100644 --- a/Code/constants.py +++ b/Code/constants.py @@ -49,16 +49,23 @@ def get_test_frame_dims(): return shape[0], shape[1] +def get_train_frame_dims(): + img_path = glob(os.path.join(TRAIN_DIR, '*/*'))[0] + img = imread(img_path, mode='RGB') + shape = np.shape(img) + + return shape[0], shape[1] + def set_test_dir(directory): """ Edits all constants dependent on TEST_DIR. @param directory: The new test directory. """ - global TEST_DIR, TEST_HEIGHT, TEST_WIDTH + global TEST_DIR, FULL_HEIGHT, FULL_WIDTH TEST_DIR = directory - TEST_HEIGHT, TEST_WIDTH = get_test_frame_dims() + FULL_HEIGHT, FULL_WIDTH = get_test_frame_dims() # root directory for all data DATA_DIR = get_dir('../Data/') @@ -75,8 +82,9 @@ MOVEMENT_THRESHOLD = 100 # total number of processed clips in TRAIN_DIR_CLIPS NUM_CLIPS = len(glob(TRAIN_DIR_CLIPS + '*')) -# the height and width of the full frames to test on. Set in avg_runner.py main. -TEST_HEIGHT = TEST_WIDTH = 0 +# the height and width of the full frames to test on. Set in avg_runner.py or process_data.py main. +FULL_HEIGHT = 210 +FULL_WIDTH = 160 # the height and width of the patches to train on TRAIN_HEIGHT = TRAIN_WIDTH = 32 diff --git a/Code/process_data.py b/Code/process_data.py index 446de91..8375035 100644 --- a/Code/process_data.py +++ b/Code/process_data.py @@ -2,6 +2,7 @@ import numpy as np import getopt import sys from glob import glob +import os import constants as c from utils import process_clip @@ -64,6 +65,10 @@ def main(): usage() sys.exit(2) + # set train frame dimensions + assert os.path.exists(c.TRAIN_DIR) + c.FULL_HEIGHT, c.FULL_WIDTH = c.get_train_frame_dims() + ## # Process data for training ## 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: |