def get_results(series, gesture_id):
# todo setup a config for current_end ( from the trained model)
current_end = 0
window_len = CONFIG.get_size_dim(gesture_id)
window = np.full((1, window_len), np.nan)
results = list()
while current_end <= len(series) - 1:
window, current_end, current_start = Launcher.update_window(
series, window, current_end)
results.append(window)
return results
def detect(array, gesture_id):
peaks = list()
count = 0
start = 0
for i, v in enumerate(array):
if v < CONFIG.get_threshold(gesture_id):
print("peak found")
start = start + count
count += 1
if count == CONFIG.get_size_dim(gesture_id) - 1:
peaks.append(Gesture(start, count, array[start:count]))
count = 0
start = 0
return peaks
def detect_old(array, gesture_id):
starting_point = CONFIG.get_size_dim(gesture_id) - 1
for i, v in enumerate(array[starting_point:]):
if all(j < CONFIG.get_threshold(gesture_id) for j in v):
print("i maybe found a gesture from index " + i.__str__() +
"to index " + (i + 150).__str__())