diff options
| -rwxr-xr-x | random241sensor.py | 41 |
1 files changed, 35 insertions, 6 deletions
diff --git a/random241sensor.py b/random241sensor.py index 624cc29..e9525e4 100755 --- a/random241sensor.py +++ b/random241sensor.py @@ -3,16 +3,17 @@ import logging import cv import numpy as np -#import time +import time # Bool to define wether to capture the cam or not capture = True # Bool to define wether to show the capture stream or not showStream = True -white_threshold = 30.0 +white_threshold = 15.0 checked = np.zeros((1, 1), dtype=np.int) mat = np.zeros((1, 1)) clusters = [] +balances = [] def capture(camNumber, showStream): @@ -48,10 +49,11 @@ def bgr2gray(mat): # Find a white dot in the black input matrix -def find_dot(mat_input): +def harvest_entropy(mat_input): global mat global checked global clusters + global balances mat = mat_input.copy() if np.ndim(mat) >= 2: # Create array to hold the already checked pixels @@ -78,7 +80,13 @@ def find_dot(mat_input): #print balance_point # Empty the global clusters variable again del clusters[:] - return balance_point + balances.append([time.time(), balance_point]) + mean = mean_balances() + logging.info('%s, %s (balance mean)', mean[1], mean[0]) + floats = coordinate_to_float(balance_point[0], balance_point[1]) + logging.info('%s, %s (float)', floats[1], floats[0]) + #return balance_point + return floats else: logging.error('Input matrix has wrong dimension!') @@ -153,5 +161,26 @@ def cluster_to_balance_point(): return [x_balance, y_balance] -# TODO: Function to add up balances -# TODO: Function to calculate forced balance +# Displays the mean balance calculated from all balances +def mean_balances(): + global balances + mean_balance = [0.0, 0.0] + for balance in balances: + mean_balance[0] = mean_balance[0] + balance[1][0] + mean_balance[1] = mean_balance[1] + balance[1][1] + mean_balance[0] = mean_balance[0] / float(len(balances)) + mean_balance[1] = mean_balance[1] / float(len(balances)) + return mean_balance + + +# Calculates float value between 0.0 and 1.0 from coordinate +# TODO: insert on-the-fly mean_balance as parameter +def coordinate_to_float(x, y): + global mat + width = float(len(mat)) + height = float(len(mat[0])) +# balance_dim = [width / 2, height / 2] + floatx = x / width + floaty = y / height + return [floatx, floaty] +# TODO: Function to calculate floats from mean_balance on the fly |