class EdgeSnapWindow(Window):
def __init__(self):
super(EdgeSnapWindow, self).__init__('Color Segmentation Example')
self.image = Image("shapes.png", sample=True).edges()
self.points = []
self.show(self.image)
def on_mouse(self, event, x, y, mouse_key, data=None):
""" Callback for mouse events
event - int - see cv2.EVENT_* constants
x, y - int, int - position of the cursor
mouse_key - int - mouse key
"""
if event == cv2.EVENT_LBUTTONDOWN:
self.points.append((x, y))
self.image.clear_layers()
for p in self.points:
self.image.dl().circle(p, 5, color=Color.BLUE)
features = self.image.edge_snap(self.points)
for f in features:
f.draw(color=Color.RED, width=2)
self.show(self.image.apply_layers())
def on_key(self, key):
if key == 32: # Space bar to clear points
self.points = []
self.image.clear_layers()
self.show(self.image)
print "Points cleared"
class ColorSegmentationWindow(Window):
def __init__(self):
super(ColorSegmentationWindow, self).__init__('Color Segmentation Example')
self.img = Image('simplecv')
self.segmentation = ColorSegmentation()
self.normal = True # mode toggle for segment detection
self.point1 = (0, 0)
self.point2 = (0, 0)
self.mosue_down = False
def on_mouse(self, event, x, y, mouse_key, data=None):
""" Callback for mouse events
event - int - see cv2.EVENT_* constants
x, y - int, int - position of the cursor
mouse_key - int - mouse key
"""
if event == cv2.EVENT_LBUTTONDOWN:
self.point1 = (x, y)
self.point2 = (x, y)
self.mosue_down = True
elif event == cv2.EVENT_MOUSEMOVE:
if self.mosue_down == True:
self.point2 = (x, y)
elif event == cv2.EVENT_LBUTTONUP:
self.mosue_down = False
self.point2 = (x, y)
x1, y1, w, h = points_to_roi(self.point1, self.point2)
if w > 0 and h > 0:
crop = self.img.crop(x1, y1, w, h)
self.segmentation = ColorSegmentation()
self.segmentation.add_to_model(crop)
def on_key(self, key):
if key == 32: # Space bar to switch between modes
self.normal = not self.normal
print "Display Mode:", "Normal" if self.normal else "Segmented"
def on_update(self):
""" Callback for periodic update.
"""
if self.normal:
self.img.clear_layers()
self.img.dl().rectangle_to_pts(self.point1, self.point2, color=Color.RED)
self.show(self.img.apply_layers())
else:
self.segmentation.add_image(self.img)
if self.segmentation.is_ready():
img = self.segmentation.get_segmented_image()
img = img.erode(iterations = 2).dilate().invert()
self.show(img)
class EdgeSnapWindow(Window):
def __init__(self):
super(EdgeSnapWindow, self).__init__('Color Segmentation Example')
self.image = Image("shapes.png", sample=True).edges()
self.points = []
self.show(self.image)
def on_mouse(self, event, x, y, mouse_key, data=None):
""" Callback for mouse events
event - int - see cv2.EVENT_* constants
x, y - int, int - position of the cursor
mouse_key - int - mouse key
"""
if event == cv2.EVENT_LBUTTONDOWN:
self.points.append((x, y))
self.image.clear_layers()
for p in self.points:
self.image.dl().circle(p, 5, color=Color.BLUE)
features = self.image.edge_snap(self.points)
for f in features:
f.draw(color=Color.RED, width=2)
self.show(self.image.apply_layers())
def on_key(self, key):
if key == 32: # Space bar to clear points
self.points = []
self.image.clear_layers()
self.show(self.image)
print "Points cleared"
to think of this is if you played the card matching game, the cards would
pretty much have to be identical. The template method doesn't allow much
for the scale to change, nor for rotation. This is the most basic pattern
matching SimpleCV offers. If you are looking for something more complex
you will probably want to look into img.find()
"""
print __doc__
import time
from simplecv.api import Image, Color, TemplateMatch
source = Image("templatetest.png", sample=True) # the image to search
template = Image("template.png",
sample=True) # the template to search the image for
t = 5
methods = [
"SQR_DIFF", "SQR_DIFF_NORM", "CCOEFF", "CCOEFF_NORM", "CCORR", "CCORR_NORM"
] # the various types of template matching available
for m in methods:
img = Image("templatetest.png", sample=True)
img.dl().text("current method: {}".format(m), (10, 20), color=Color.RED)
fs = source.find(TemplateMatch, template, threshold=t, method=m)
for match in fs:
img.dl().rectangle((match.x, match.y), (match.width, match.height),
color=Color.RED)
img.apply_layers().show()
time.sleep(3)
from simplecv.api import Color, Image
from simplecv.core.drawing.layer import DrawingLayer
img = Image("color.jpg", sample=True)
line_l = DrawingLayer()
a = (20, 20)
b = (20, 100)
c = (100, 100)
d = (100, 20)
line_l.line(a, b, alpha=128, width=5)
line_l.line(b, c, alpha=128)
line_l.line(c, d, antialias=True)
line_l.line(d, a, color=Color.PUCE)
line_l.line(b, d, width=5)
img.add_drawing_layer(line_l)
temp = img.apply_layers()
print "line: %s" % temp.save(temp=True)
img.clear_layers()
lines_l = DrawingLayer()
a = (20, 20)
b = (20, 100)
c = (100, 100)
d = (100, 20)
pts = (a, b, c, d, a)
lines_l.lines(pts, alpha=128)
# translate over and down 10
pts = map(lambda x: ((x[0] + 10), (x[1] + 10)), pts)
lines_l.lines(pts, color=Color.BEIGE, width=10)
#translate over and down 10
pts = map(lambda x: ((x[0] + 10), (x[1] + 10)), pts)
# write the text
layer.text("Just some innocent looking dots", (50, 25), Color.BLACK)
layer.text("Use w/s keys to change intensity", (50, 50), Color.BLACK)
layer.text("a/d keys to change angle", (50, 75), Color.BLACK)
#draw 6 innocent looking dots
layer.circle((125, 200), 25, Color.RED, 1, True)
layer.circle((250, 200), 25, Color.BLUE, 1, True)
layer.circle((375, 200), 25, Color.GREEN, 1, True)
layer.circle((125, 300), 25, Color.YELLOW, 1, True)
layer.circle((250, 300), 25, Color.ORANGE, 1, True)
layer.circle((375, 300), 25, Color.CYAN, 1, True)
# apply layer
img.add_drawing_layer(layer)
img = img.apply_layers()
img.show()
power = 1
angle = 0
while True:
key = cv2.waitKey(1)
if key == -1:
continue
print chr(key)
# detect w,a,s,d key presses and modify power, angle
if key == ord('w'):
power += 10
blur = img.motion_blur2(power, angle)
blur.show()
"""
This example uses the built in template matching. The easiest way
to think of this is if you played the card matching game, the cards would
pretty much have to be identical. The template method doesn't allow much
for the scale to change, nor for rotation. This is the most basic pattern
matching SimpleCV offers. If you are looking for something more complex
you will probably want to look into img.find()
"""
print __doc__
import time
from simplecv.api import Image, Color, TemplateMatch
source = Image("templatetest.png", sample=True) # the image to search
template = Image("template.png", sample=True) # the template to search the image for
t = 5
methods = ["SQR_DIFF", "SQR_DIFF_NORM", "CCOEFF",
"CCOEFF_NORM", "CCORR", "CCORR_NORM"] # the various types of template matching available
for m in methods:
img = Image("templatetest.png", sample=True)
img.dl().text("current method: {}".format(m), (10, 20), color=Color.RED)
fs = source.find(TemplateMatch, template, threshold=t, method=m)
for match in fs:
img.dl().rectangle((match.x, match.y), (match.width, match.height), color=Color.RED)
img.apply_layers().show()
time.sleep(3)