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)