def integrate(fpath, poly):
fnames = os.listdir(fpath)
fnames = np.sort(fnames)
description = [('video_ts',np.float32), ('x', np.float32), ('y', np.float32)]
for i, fname in enumerate(fnames):
session_file = os.path.join(fpath,fname)
with open(session_file) as file:
sid = int(fname[:-4])
data = np.genfromtxt(file, dtype=description, delimiter=',', names=None)
se_ts = (data['video_ts'] - poly[i][1]) / poly[i][0]
se_ts = np.around(se_ts)
se_ts = se_ts.astype(np.int)
data = append_field(data, 'se_ts', se_ts)
data = append_field(data, 'session_id', sid)
if i == 0:
naksu_data = data
else:
naksu_data = rowstack((naksu_data, data))
#naksu_data = np.vstack((naksu_data, data))
return naksu_data
def integrate_manual(fpath):
sid_paths = os.listdir(fpath)
sid_paths = np.sort(sid_paths)
description = [('video_ts',np.float32), ('x', np.float32), ('y', np.float32),
('se_ts', np.int), ('session_id', np.int)]
naksu_data = np.array([], dtype=description)
for sid in sid_paths:
bend_paths = os.listdir(os.path.join(fpath,sid))
for b in bend_paths:
print sid, b
lap_paths = os.listdir(os.path.join(fpath, sid, b))
for l in lap_paths:
files = os.listdir(os.path.join(fpath, sid, b, l))
files = [os.path.join(fpath, sid, b, l, x) for x in files if x.lower().endswith('.mrk')]
for f in files:
with open(f) as file:
fdata = np.genfromtxt(file, dtype=[('point', np.int),
('x', np.float), ('y', np.float)])
if np.size(fdata) == 0: continue
fdata = fdata if np.size(fdata['x']) == 1 else fdata[0]
impath = f[:-4] + ".jpg"
img = Image.open(impath)
imstr = StringIO()
pos, size = (3, 24), (80, 24)
img = img.crop((pos[0], pos[1], pos[0]+size[0], pos[1]+size[1]))
img = ImageOps.invert(img)
img.save(imstr, format="PPM")
imstr = imstr.getvalue()
cmd = "gocr -C 0-9. -"
proc = subprocess.Popen(cmd, shell=True,
stdin=subprocess.PIPE,
stderr=subprocess.PIPE,
stdout=subprocess.PIPE)
timestamp = proc.communicate(imstr)[0]
timestamp = timestamp.strip()
timestamp = timestamp.strip('_')
try:
timestamp = float(timestamp)
except ValueError:
continue
d = np.array((0, fdata['x'], fdata['y'], timestamp, sid), dtype=description)
naksu_data = rowstack((naksu_data, d))
naksu_data.sort(order=['session_id', 'se_ts'])
return naksu_data
def get_merged_data():
# this is not needed unless TP location is an issue!
# cdata, h5file = get_cleaned_data(DATA_FILE)
cdata, h5file = get_uncleaned_data(DATA_FILE)
naksu_raw = h5file.root.ramppi11.naksu_data.read()
merged = []
for d in foreach(cdata, ["session_id", "lap"]):
naksu_x, naksu_y, lap_d = get_interp_naksu(d, naksu_raw)
naksu_d = np.rec.fromarrays((naksu_x, naksu_y), names="naksu_x,naksu_y")
merged.append(colstack(lap_d, naksu_d))
merged = rowstack(merged)
return merged