def process_all_videos(video_folder):
vids = os.listdir(video_folder)
date = Fn.extract_date_from_beginning(video_folder)
print date
for i, vid in enumerate(vids):
if not vid.endswith("MOV"):
continue
print ("Processing video {}".format(vid))
process_video(os.path.join(video_folder, vid), date)
if i >= 2:
return
def process_all_videos(video_folder):
vids = os.listdir(video_folder)
date = Fn.extract_date_from_beginning(video_folder)
print date
for i, vid in enumerate(vids):
if not vid.endswith("MOV"):
continue
print("Processing video {}".format(vid))
process_video(os.path.join(video_folder, vid), date)
if i >= 2:
return
def process_file(fn, date):
df, meta = read_meta_file(fn)
if len(df)<=1:
#print("Not a distance related ground truth file, skipping")
return
w = get_pitch_width(meta)
l = get_pitch_length(meta)
if w is None or l is None:
print("No width or length information, skipping {}".format(fn))
return
diag = math.sqrt(l*l + w*w)
distances=get_corner_to_dist_mapping(w,l,date)
dfprev = df.shift(1)
df["route"] = dfprev.corner + df.corner
df["dist_from_prev_to_curr"] = df.route.apply(lambda x: get_distance(x,distances))
df["dist_covered"] = df["dist_from_prev_to_curr"].cumsum()
df["secs_elapsed"] = df["secs_from_prev_to_curr"].cumsum()
df2 = df[["secs_elapsed","dist_covered"]]
ts = pd.Series(df.dist_covered.values, index=df.secs_elapsed)
ts.to_csv(Fn.change_ext(fn,"dground"))
def process_file(fn, date):
df, meta = read_meta_file(fn)
if len(df) <= 1:
#print("Not a distance related ground truth file, skipping")
return
w = get_pitch_width(meta)
l = get_pitch_length(meta)
if w is None or l is None:
print("No width or length information, skipping {}".format(fn))
return
diag = math.sqrt(l * l + w * w)
distances = get_corner_to_dist_mapping(w, l, date)
dfprev = df.shift(1)
df["route"] = dfprev.corner + df.corner
df["dist_from_prev_to_curr"] = df.route.apply(
lambda x: get_distance(x, distances))
df["dist_covered"] = df["dist_from_prev_to_curr"].cumsum()
df["secs_elapsed"] = df["secs_from_prev_to_curr"].cumsum()
df2 = df[["secs_elapsed", "dist_covered"]]
ts = pd.Series(df.dist_covered.values, index=df.secs_elapsed)
ts.to_csv(Fn.change_ext(fn, "dground"))
import os
import glob
import sys
from utils import Filenames as Fn
if __name__ == '__main__':
folder = sys.argv[1]
if len(sys.argv)>2:
force=True
else:
force=False
txts = glob.glob(os.path.join(folder,"*txt"))
metas = glob.glob(os.path.join(folder,"*meta"))
for txt in txts:
folder = os.path.dirname(txt)
basetxt= os.path.basename(txt)
for meta in metas:
if "Session"+basetxt in meta:
newtxtbase,_ = os.path.splitext(meta)
print basetxt
print "will rename ", txt," to ",newtxtbase
if force:
print "actually renaming"
Fn.change_filename(txt, newtxtbase)
import os
import glob
import sys
from utils import Filenames as Fn
if __name__ == '__main__':
folder = sys.argv[1]
if len(sys.argv) > 2:
force = True
else:
force = False
txts = glob.glob(os.path.join(folder, "*txt"))
metas = glob.glob(os.path.join(folder, "*meta"))
for txt in txts:
folder = os.path.dirname(txt)
basetxt = os.path.basename(txt)
for meta in metas:
if "Session" + basetxt in meta:
newtxtbase, _ = os.path.splitext(meta)
print basetxt
print "will rename ", txt, " to ", newtxtbase
if force:
print "actually renaming"
Fn.change_filename(txt, newtxtbase)
def process_all_ground_truth(folder,date):
all_meta_files = Fn.find_files_with_ext(folder,"meta")
for fn in all_meta_files:
#print(fn)
process_file(fn,date)
df, meta = read_meta_file(fn)
if len(df)<=1:
#print("Not a distance related ground truth file, skipping")
return
w = get_pitch_width(meta)
l = get_pitch_length(meta)
if w is None or l is None:
print("No width or length information, skipping {}".format(fn))
return
diag = math.sqrt(l*l + w*w)
distances=get_corner_to_dist_mapping(w,l,date)
dfprev = df.shift(1)
df["route"] = dfprev.corner + df.corner
df["dist_from_prev_to_curr"] = df.route.apply(lambda x: get_distance(x,distances))
df["dist_covered"] = df["dist_from_prev_to_curr"].cumsum()
df["secs_elapsed"] = df["secs_from_prev_to_curr"].cumsum()
df2 = df[["secs_elapsed","dist_covered"]]
ts = pd.Series(df.dist_covered.values, index=df.secs_elapsed)
ts.to_csv(Fn.change_ext(fn,"dground"))
def process_all_ground_truth(folder,date):
all_meta_files = Fn.find_files_with_ext(folder,"meta")
for fn in all_meta_files:
#print(fn)
process_file(fn,date)
if __name__ == '__main__':
folder = sys.argv[1]
date = Fn.extract_date_from_beginning(folder)
process_all_ground_truth(folder,date)
def process_all_ground_truth(folder, date):
all_meta_files = Fn.find_files_with_ext(folder, "meta")
for fn in all_meta_files:
#print(fn)
process_file(fn, date)
return
w = get_pitch_width(meta)
l = get_pitch_length(meta)
if w is None or l is None:
print("No width or length information, skipping {}".format(fn))
return
diag = math.sqrt(l * l + w * w)
distances = get_corner_to_dist_mapping(w, l, date)
dfprev = df.shift(1)
df["route"] = dfprev.corner + df.corner
df["dist_from_prev_to_curr"] = df.route.apply(
lambda x: get_distance(x, distances))
df["dist_covered"] = df["dist_from_prev_to_curr"].cumsum()
df["secs_elapsed"] = df["secs_from_prev_to_curr"].cumsum()
df2 = df[["secs_elapsed", "dist_covered"]]
ts = pd.Series(df.dist_covered.values, index=df.secs_elapsed)
ts.to_csv(Fn.change_ext(fn, "dground"))
def process_all_ground_truth(folder, date):
all_meta_files = Fn.find_files_with_ext(folder, "meta")
for fn in all_meta_files:
#print(fn)
process_file(fn, date)
if __name__ == '__main__':
folder = sys.argv[1]
date = Fn.extract_date_from_beginning(folder)
process_all_ground_truth(folder, date)
