First commit, still some TODOs

5 files changed, 361 insertions, 0 deletions

diff --git a/.ropeproject/config.py b/.ropeproject/config.py
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+++ b/.ropeproject/config.py
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+# The default ``config.py``
+
+
+def set_prefs(prefs):
+    """This function is called before opening the project"""
+
+    # Specify which files and folders to ignore in the project.
+    # Changes to ignored resources are not added to the history and
+    # VCSs.  Also they are not returned in `Project.get_files()`.
+    # Note that ``?`` and ``*`` match all characters but slashes.
+    # '*.pyc': matches 'test.pyc' and 'pkg/test.pyc'
+    # 'mod*.pyc': matches 'test/mod1.pyc' but not 'mod/1.pyc'
+    # '.svn': matches 'pkg/.svn' and all of its children
+    # 'build/*.o': matches 'build/lib.o' but not 'build/sub/lib.o'
+    # 'build//*.o': matches 'build/lib.o' and 'build/sub/lib.o'
+    prefs['ignored_resources'] = ['*.pyc', '*~', '.ropeproject',
+                                  '.hg', '.svn', '_svn', '.git']
+
+    # Specifies which files should be considered python files.  It is
+    # useful when you have scripts inside your project.  Only files
+    # ending with ``.py`` are considered to be python files by
+    # default.
+    #prefs['python_files'] = ['*.py']
+
+    # Custom source folders:  By default rope searches the project
+    # for finding source folders (folders that should be searched
+    # for finding modules).  You can add paths to that list.  Note
+    # that rope guesses project source folders correctly most of the
+    # time; use this if you have any problems.
+    # The folders should be relative to project root and use '/' for
+    # separating folders regardless of the platform rope is running on.
+    # 'src/my_source_folder' for instance.
+    #prefs.add('source_folders', 'src')
+
+    # You can extend python path for looking up modules
+    #prefs.add('python_path', '~/python/')
+
+    # Should rope save object information or not.
+    prefs['save_objectdb'] = True
+    prefs['compress_objectdb'] = False
+
+    # If `True`, rope analyzes each module when it is being saved.
+    prefs['automatic_soa'] = True
+    # The depth of calls to follow in static object analysis
+    prefs['soa_followed_calls'] = 0
+
+    # If `False` when running modules or unit tests "dynamic object
+    # analysis" is turned off.  This makes them much faster.
+    prefs['perform_doa'] = True
+
+    # Rope can check the validity of its object DB when running.
+    prefs['validate_objectdb'] = True
+
+    # How many undos to hold?
+    prefs['max_history_items'] = 32
+
+    # Shows whether to save history across sessions.
+    prefs['save_history'] = True
+    prefs['compress_history'] = False
+
+    # Set the number spaces used for indenting.  According to
+    # :PEP:`8`, it is best to use 4 spaces.  Since most of rope's
+    # unit-tests use 4 spaces it is more reliable, too.
+    prefs['indent_size'] = 4
+
+    # Builtin and c-extension modules that are allowed to be imported
+    # and inspected by rope.
+    prefs['extension_modules'] = []
+
+    # Add all standard c-extensions to extension_modules list.
+    prefs['import_dynload_stdmods'] = True
+
+    # If `True` modules with syntax errors are considered to be empty.
+    # The default value is `False`; When `False` syntax errors raise
+    # `rope.base.exceptions.ModuleSyntaxError` exception.
+    prefs['ignore_syntax_errors'] = False
+
+    # If `True`, rope ignores unresolvable imports.  Otherwise, they
+    # appear in the importing namespace.
+    prefs['ignore_bad_imports'] = False
+
+
+def project_opened(project):
+    """This function is called after opening the project"""
+    # Do whatever you like here!
diff --git a/random241.py b/random241.py
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index 0000000..1f74485
--- /dev/null
+++ b/random241.py
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+#!/usr/bin/python2
+
+import cv
+import time
+import numpy as np
+import logging
+import random241arg as arg
+import random241sensor as sensor
+import random241osc as osc
+
+showStream = False
+stop_key = 0
+capture = True
+camNumber = 1
+time_delta = 60 * 60 / 2
+logging.basicConfig(filename='random241.log',
+                    format='%(asctime)s %(message)s',
+                    filemode='w', level=logging.INFO)
+
+
+# Read parameters
+params = arg.read_params()
+# Define which cam to use, etc.
+#cam = sensor.capture(params['-c'], showStream)
+
+# Get frame and size information from camera
+cam = cv.CaptureFromCAM(camNumber)
+frame = cv.QueryFrame(cam)
+if frame is not None:
+    frame_size = cv.GetSize(frame)
+    logging.info('Grabbing random numbers from: %dx%dpx.',
+                 frame_size[0], frame_size[1])
+
+    # Get matrix with values from frame
+    mat = cv.GetMat(frame)
+    frame_values = np.asarray(mat)
+    # Create grayscale image
+    gray_values = sensor.bgr2gray(frame_values)
+
+    # Define the time to run the test
+    time_delta = time_delta + time.time()
+
+    # Setup OSC
+    osc.connect_to_server("dvzrv", 57120)
+
+    # Main loop for accessing the camera and calculating random numbers from it
+    #while True:
+    while time_delta > time.time():
+        img = cv.QueryFrame(cam)
+        # Get a numpy array with rgb values
+        #frame = sensor.frame_to_mat(stream)
+        randomness = sensor.find_dot(sensor.bgr2gray(sensor.frame_to_mat(img)))
+        if randomness is not None:
+            osc.send_osc_msg_to_server(randomness)
+        if showStream:
+            while stop_key != ord("q"):
+                cv.ShowImage("Americium 241", img)
+                key = cv.WaitKey(2)
+
+    #time.sleep(5)
+    #random241sensor.set_capture(False)
+else:
+    logging.error('Connect camera %d first!', camNumber)
diff --git a/random241arg.py b/random241arg.py
new file mode 100755
index 0000000..4bd00d8
--- /dev/null
+++ b/random241arg.py
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+#!/usr/bin/python2
+
+from sys import argv
+
+
+def read_params():
+    # Checks the given parameters
+    info = """Use the program as following:
+    random241.py [option] <param> ...
+    Options:
+        -c  number of cam to use (starts with first found camera 0 (default))
+        -r  remote address to send the output to (standard 192.168.0.7)
+    """
+    default = {'-c': "1", '-r': "192.168.0.7"}
+    parameters = default.copy()
+    if len(argv) != 3:
+        for i in xrange(1, len(argv) - 1, 2):
+            if argv[i] in parameters:
+                parameters[argv[i]] = argv[i + 1]
+            else:
+                print info
+                return 0
+        return parameters
+    else:
+        return default
diff --git a/random241osc.py b/random241osc.py
new file mode 100755
index 0000000..3d95f69
--- /dev/null
+++ b/random241osc.py
@@ -0,0 +1,31 @@
+#import OSC as osc
+import liblo as osc
+import logging
+
+# Declare an empty target
+target = None
+
+
+# Connect to the server
+def connect_to_server(hostname, port):
+    global target
+    if (hostname or port) is None:
+        target = osc.Adress('127.0.0.1', 57120, osc.TCP)
+    else:
+        try:
+            target = osc.Address(hostname, port, osc.TCP)
+        except osc.AddressError, err:
+            logging.error(err)
+
+
+# Send a osc_message to the server
+def send_osc_msg_to_server(randomness):
+    global target
+    # if the message is not empty and longer than 1
+    if randomness is not None and len(randomness) > 1:
+        msg = osc.Message("/random")
+        msg.add(randomness[0], randomness[1])
+        try:
+            osc.send(target, msg)
+        except:
+            logging.error('OSC: Sending of message failed.')
diff --git a/random241sensor.py b/random241sensor.py
new file mode 100755
index 0000000..624cc29
--- /dev/null
+++ b/random241sensor.py
@@ -0,0 +1,157 @@
+#!/usr/bin/python2
+
+import logging
+import cv
+import numpy as np
+#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
+checked = np.zeros((1, 1), dtype=np.int)
+mat = np.zeros((1, 1))
+clusters = []
+
+
+def capture(camNumber, showStream):
+    # Open stream for that camera
+    logging.info('Capture from camera #%d', camNumber)
+    cam = cv.CaptureFromCAM(int(camNumber))
+    # Stream to output window as long as it is active
+    return cam
+    while capture:
+        stream = cv.QueryFrame(cam)
+        if showStream:
+            cv.ShowImage("Americium 241", stream)
+
+
+def set_capture(onOrOff):
+    if onOrOff == bool:
+        global capture
+        capture = onOrOff
+
+
+def frame_to_mat(img):
+    cv.Smooth(img, img, cv.CV_GAUSSIAN, 3, 0)
+    mat = cv.GetMat(img)
+    frame_values = np.asarray(mat)
+    return frame_values
+
+
+# Convert a bgr matrix to grayscale
+def bgr2gray(mat):
+    b, g, r = mat[:, :, 0], mat[:, :, 1], mat[:, :, 2]
+    gray = 0.1140 * b + 0.5870 * g + 0.2989 * r
+    return gray
+
+
+# Find a white dot in the black input matrix
+def find_dot(mat_input):
+    global mat
+    global checked
+    global clusters
+    mat = mat_input.copy()
+    if np.ndim(mat) >= 2:
+        # Create array to hold the already checked pixels
+        checked = np.zeros((len(mat), len(mat[0])), dtype=np.int)
+        # Traverse the grayscale values in search of a bright pixel
+        for i in range(0, len(mat) - 1):
+            for j in range(0, len(mat[0]) - 1):
+                # Check if it hasn't been checked yet
+                if (checked[i][j] != 1):
+                    # Find clusters, if the pixel is above threshold
+                    if (mat[i][j] >= white_threshold):
+                        #print "Hit above white threshold"
+                        # Add a new cluster to the list of clusters
+                        cluster = []
+                        clusters.append(cluster)
+                        # Find the rest of the cluster
+                        find_cluster(i, j)
+                        #print "Number at: %dx%dpx : %s" % (j, i, mat[i][j])
+                checked[i][j] = 1
+        # If there's one or more clusters, calculate its or their balance point
+        if len(clusters) > 0:
+            balance_point = cluster_to_balance_point()
+            logging.info('%s, %s', balance_point[1], balance_point[0])
+            #print balance_point
+            # Empty the global clusters variable again
+            del clusters[:]
+            return balance_point
+    else:
+        logging.error('Input matrix has wrong dimension!')
+
+
+# Find cluster around a non-black pixel
+def find_cluster(x, y):
+    global checked
+    global mat
+    global clusters
+    # Append the current white dot to the last cluster
+    dot = np.array([x, y, mat[x][y]])
+    clusters[len(clusters) - 1].append(dot)
+    # Search for surrounding white dots now
+    # Search one pixel further right
+    if (len(mat) - 1 >= (x + 1)) and (mat[x + 1][y] >= white_threshold) \
+            and (checked[x + 1][y] != 1):
+        find_cluster(x + 1, y)
+    # Search one pixel further right and down
+    if (len(mat) - 1 >= (x + 1)) and (len(mat[0]) - 1 >= y + 1) and \
+            (mat[x + 1][y + 1] >= white_threshold) \
+            and (checked[x + 1][y] != 1):
+        find_cluster(x + 1, y + 1)
+    # Search one pixel further down
+    if (len(mat[0]) - 1 >= y + 1) and \
+            (mat[x][y + 1] >= white_threshold) and (checked[x][y + 1] != 1):
+        find_cluster(x, y + 1)
+    # Search one pixel further down and further left
+    if (len(mat[0]) - 1 >= y + 1) and x - 1 >= 0 \
+            and (mat[x - 1][y + 1] >= white_threshold) \
+            and (checked[x - 1][y + 1] != 1):
+        find_cluster(x - 1, y + 1)
+    # Add this pixel to the list of checked pixels
+    checked[x][y] = 1
+
+
+# Create balance point from cluster
+# TODO: Make possible to choose only most significant cluster
+def cluster_to_balance_point():
+    global clusters
+    cluster_balances = []
+    x_balance = 0.0
+    y_balance = 0.0
+    for cluster in clusters:
+        mean_x = 0.0
+        mean_y = 0.0
+        sum_total = 0.0
+        for dot in cluster:
+            # Calculate X balance (x * intensity)
+            mean_x = mean_x + dot[0] * dot[2]
+            # Calculate Y balance (y * intensity)
+            mean_y = mean_y + dot[1] * dot[2]
+            # Calculate Y total (all intensity summed up)
+            sum_total = sum_total + dot[2]
+        # Add up the balances and put them into a list
+        cluster_x_balance = mean_x / sum_total
+        cluster_y_balance = mean_y / sum_total
+        cluster_balances.append([cluster_x_balance, cluster_y_balance])
+    # If it's more than one cluster, balance between them
+    if len(cluster_balances) > 1:
+        logging.info('Balancing between a couple of clusters.')
+        total_cluster_x_balance = 0.0
+        total_cluster_y_balance = 0.0
+        for balance in cluster_balances:
+            total_cluster_x_balance = total_cluster_x_balance + balance[0]
+            total_cluster_y_balance = total_cluster_y_balance + balance[1]
+        x_balance = total_cluster_x_balance / float(len(cluster_balances))
+        y_balance = total_cluster_y_balance / float(len(cluster_balances))
+    else:
+        logging.info('Balancing between one cluster.')
+        x_balance = cluster_x_balance
+        y_balance = cluster_y_balance
+    return [x_balance, y_balance]
+
+
+# TODO: Function to add up balances
+# TODO: Function to calculate forced balance