def ckpt_up_to_date(local_ckpt_prefix, bucket, folder):
fm = FileManager(bucket)
ckpt_names = fm.get_folder_list(folder)
most_recent_prefix = most_recent_ckpt_from_list(ckpt_names)
if not local_ckpt_prefix == most_recent_prefix:
return False
return True
def extract_training_data(s3_bucket_name, top_dir):
fm = FileManager(s3_bucket_name)
annotation_dir = os.path.join(top_dir, 'annotations')
frames_dir = os.path.join(top_dir, 'frames')
annotations_names = fm.get_folder_list(annotation_dir, extension_filter='json')
frame_names = [x for x in fm.get_folder_list(frames_dir) if len(x.split('.')) == 2]
frame_exts = set([x.split('.')[1] for x in frame_names])
frame_names = set(frame_names)
data = []
for filename in annotations_names:
# if not json file, skip
if not filename.split('.')[1] == 'json':
continue
# strange behavior with os.path.join
# depending on whether or not looking in s3 bucket
if s3_bucket_name is not None:
annotation_filename = annotation_dir + filename
else:
annotation_filename = os.path.join(annotation_dir, filename)
M = get_matrix_from_annotations(s3_bucket_name, annotation_filename)
if M is not None:
filename_noext = filename.split('.')[0]
for ext in frame_exts:
frame_name = filename_noext + '.' + ext
if frame_name in frame_names:
# same strange behavior
if s3_bucket_name is not None:
frame_path_from_bucket = top_dir + '/frames' + frame_name
else:
frame_path_from_bucket = os.path.join(top_dir, 'frames', frame_name)
data.append((frame_path_from_bucket, M))
return data
def download_ckpt_to_dir(bucket, folder, dest_dir):
'''
download most recent ckpt files (index, meta, data) from s3 bucket and directory.
dest: local folder to put files into
returns: path/to/ckpt_prefix
'''
fm = FileManager(bucket)
# need .data and .index files (don't necessarily need meta, but will download)
ckpt_names = fm.get_folder_list(folder)
most_recent_ckpt_prefix = most_recent_ckpt_from_list(ckpt_names)
print('Downloading ckpts from s3: {}'.format(most_recent_ckpt_prefix))
ckpt_file_names = [x for x in ckpt_names if most_recent_ckpt_prefix in x]
path_and_prefix = dest_dir + '/' + most_recent_ckpt_prefix
for key in ckpt_file_names:
dest_filepath = dest_dir + '/' + key
fm.download_file(folder, key, dest_filepath)
return path_and_prefix
from utils.display import Display
from utils.file_manager import FileManager
from utils.warp_tools import *
from utils.rink_specs import HockeyRink
import random
import cv2
fm = FileManager('bsivisiondata')
d = Display()
annotations = fm.get_folder_list('PHI-PIT_6m-8m/annotations',
extension_filter='json')
# random.shuffle(annotations)
for f in annotations:
print f
im_dict = fm.read_image_dict('PHI-PIT_6m-8m/annotations', f)
if not 'warp' in im_dict:
continue
imname = f.split('.')[0] + '.png'
im = fm.read_image_file('PHI-PIT_6m-8m/frames', imname)
im = cv2.cvtColor(im, cv2.COLOR_RGB2BGR)
H = np.array(im_dict['warp']['M'])
hr = HockeyRink()
scaled_H = scale_homography(H, 600, 300)
H1280 = scale_homography(H, 1280, 720)
'''
NEEDED TO BE RESIZING IMAGES BEFORE CALLING WARP!!!
'''