Python Image.colorDistance方法代码示例

# 需要导入模块: from SimpleCV import Image [as 别名]
# 或者: from SimpleCV.Image import colorDistance [as 别名]
	def trataImagen(self):
		
		img = Image(self.rutaImagenReducida)
		result = img.colorDistance((self.ajustes.r, self.ajustes.g, self.ajustes.b))
		result.save(self.rutaImagenTratada_Fase1) 
		result = result.invert()
		result = result.binarize(float(self.ajustes.umbralBinarizado)).invert()
		result.save(self.rutaImagenTratada_Fase2) 

# 需要导入模块: from SimpleCV import Image [as 别名]
# 或者: from SimpleCV.Image import colorDistance [as 别名]
	def trataImagen(self, r, g, b, umbralBinarizado):
		
		inicio = time.time()
		
		img = Image(self.rutaImagenReducida)
		result = img.colorDistance((r, g, b)).invert()
		result = result.binarize(umbralBinarizado).invert()
		result.save(self.rutaImagenTratada)
		
		fin = time.time()
		self.tiempoTratamiento = fin - inicio

# 需要导入模块: from SimpleCV import Image [as 别名]
# 或者: from SimpleCV.Image import colorDistance [as 别名]
def findYellowMask(image_file):
	original = Image(image_file)

	yellow_only = original.colorDistance((232,166,30))
	yellow_only = yellow_only*4

	mask = yellow_only.invert()
	#mask.save("yellow_mask.jpg")

	binarizedMask = mask.binarize().invert()
	#binarizedMask.save("binarized_mask_yellow.jpg")

	return binarizedMask

# 需要导入模块: from SimpleCV import Image [as 别名]
# 或者: from SimpleCV.Image import colorDistance [as 别名]
def dot_blobs(si, image_path):
	new_file_path = step_file_path(si, 'dot-blobs')
	img = Image(image_path)
	new_img = img.colorDistance((160, 255, 160)).invert().binarize((200, 200, 200)).invert().erode(1)
	dots = sorted(new_img.findBlobs()[-5:], key=lambda blob: blob.centroid()[1])
	for blob in dots:
		blob.draw()
		new_img.dl().circle(blob.centroid(), 5, Color.RED)

	centroids = map(lambda blob: blob.centroid(), dots)

	bottom_screws = sorted(centroids[2:4], key=lambda centroid: centroid[0])

	shoe_measurements = ShoeMeasurements(si.foot, centroids[0], centroids[1], bottom_screws[0], bottom_screws[1], centroids[4])
	new_img = shoe_measurements.draw_on_img(new_img)
	new_img.save(new_file_path)
	si.step_outputs.append(new_file_path)
	return (new_file_path, shoe_measurements)

# 需要导入模块: from SimpleCV import Image [as 别名]
# 或者: from SimpleCV.Image import colorDistance [as 别名]
	def find(self):
		new_file_path = self.nfn('dot-blobs')
		img = Image(self.img_path)
		new_img = img.colorDistance((160, 255, 160)).invert().binarize((200, 200, 200)).invert().erode(1)
		for blob in new_img.findBlobs():
			print str(blob) + " --> " + str(self.chance_blob_is_an_ellipse(blob))

		dots = sorted(new_img.findBlobs()[-5:], key=lambda blob: blob.centroid()[1])
		for blob in dots:
			blob.draw()
			new_img.dl().circle(blob.centroid(), 5, Color.RED)

		centroids = map(lambda blob: blob.centroid(), dots)

		bottom_screws = sorted(centroids[2:4], key=lambda centroid: centroid[0])

		shoe_measurements = ShoeMeasurements(self.shoe.left_or_right, centroids[0], centroids[1], bottom_screws[0], bottom_screws[1], centroids[4])
		new_img = shoe_measurements.draw_on_img(new_img)
		new_img.save(new_file_path)
		return (new_file_path, shoe_measurements)

# 需要导入模块: from SimpleCV import Image [as 别名]
# 或者: from SimpleCV.Image import colorDistance [as 别名]
def detectCenter(image_file):

	original = Image(image_file)

	center_only = original.colorDistance((155,9,49))*8

	mask = center_only.invert()
	#mask.save("center_mask.jpg")

	binarizedMask = mask.binarize().invert()
	#binarizedMask.save("binarized_mask_center.jpg")

	blobs = original.findBlobsFromMask(binarizedMask)

	if blobs == None :
		#print "No red found"
		return detectGreenLowQuality(image_file)


	bestBlob = blobs[-1]
	bestBlob.drawMinRect(color=Color.RED,width =10)

	bestBlob.image = original

	original.save("align.png")


	centroidX = bestBlob.minRectX()
	centroidY = bestBlob.minRectY()

	#Have to find out which part of the screen centroid is in
	maxX = original.getNumpy().shape[0]
	maxY = original.getNumpy().shape[1]+100
	

	#assume width of 150 pixels
	return align_center(maxX,maxY,centroidX,centroidY,80,80)

# 需要导入模块: from SimpleCV import Image [as 别名]
# 或者: from SimpleCV.Image import colorDistance [as 别名]
def detectYellowLowQuality(image_file):

	original = Image(image_file)

	yellow_only = original.colorDistance((156,130,76))*2
	#yellow_only = yellow_only*4

	mask = yellow_only.invert()
	#mask.save("yellow_mask.jpg")

	binarizedMask = mask.binarize().invert()
	#binarizedMask.save("binarized_mask_yellow.jpg")

	blobs = original.findBlobsFromMask(binarizedMask)

	if blobs == None:
		#print "No yellow found"
		return -1

	blobs[-1].drawMinRect(color=Color.RED,width =10)
	blobs.image = original

	#original.save("foundBlobs_yellow.jpg")

	bestBlob = blobs[-1]


	centroidX = bestBlob.minRectX()
	centroidY = bestBlob.minRectY()

	#Have to find out which part of the screen centroid is in
	maxX = original.getNumpy().shape[0]
	maxY = original.getNumpy().shape[1]+100
	

	#assume width of 150 pixels
	return align_center(maxX,maxY,centroidX,centroidY,50,50)

# 需要导入模块: from SimpleCV import Image [as 别名]
# 或者: from SimpleCV.Image import colorDistance [as 别名]
    if paso1 == True:
        for marca in marcas:
            SCREEN.blit(marca[0], marca[1]) # imagen, rect

    if paso1 == False and paso2 == False:
        dibujar_Textos('GRACIAS,', font40, COLOR_AZUL_CIELO, SCREEN, 10, 100,'center')
        dibujar_Textos('CALIBRACION DE TAPETE FINALIZADA', font40, COLOR_AZUL_CIELO, SCREEN, 10, 150,'center')

    if paso2 == True:
        img = camara.getImage()
        nivel_R = control_RED.valorLevel
        nivel_G = control_GREEN.valorLevel
        nivel_B = control_BLUE.valorLevel
        UMBRAL_BINARIZADO = control_BINARIZE.valorLevel

        img = img.colorDistance((nivel_R, nivel_G, nivel_B))
        img = img.binarize(UMBRAL_BINARIZADO)
        img.save('temp/vistaTapete.png')
        imagen_calibracion =  pygame.image.load('temp/vistaTapete.png')
        SCREEN.blit(imagen_calibracion, (0,0))

        # dibujar los contoles deslizables
        for control_deslizable in listaControles:
            control_deslizable.draw(SCREEN)
            
        # Dibujar Etiquetas(y otros textos)
        dibujar_Textos('(R)   %0d'  %(nivel_R),  font20, COLOR_BLANCO_SUCIO, SCREEN, 10,  15, 0)
        dibujar_Textos('(G)   %0d' %(nivel_G), font20, COLOR_BLANCO_SUCIO, SCREEN, 10,  65, 0)
        dibujar_Textos('(B)   %0d' %(nivel_B),  font20, COLOR_BLANCO_SUCIO, SCREEN, 10, 115, 0)
        dibujar_Textos('BINARIZADO   %0d' %(UMBRAL_BINARIZADO),   font20, COLOR_BLANCO_SUCIO, SCREEN, 10, 160, 0) 

# 需要导入模块: from SimpleCV import Image [as 别名]
# 或者: from SimpleCV.Image import colorDistance [as 别名]
import SimpleCV
from SimpleCV import Image
 
display = SimpleCV.Display()

img = Image("ping/source/image3.jpeg")

# parametre pour image1 : (dilate=2), (stretch(200,255), isCircle(0.2)
# parametre pour image2 : non trouvé
# parametre pour image3 : (dilate=2), (stretch(2,120), isCircle(0.2)
# parametre pour image4 : (dilate=2), (stretch(2,120), isCircle(0.2)
# parametre pour image5 : (dilate=2), (stretch(2,120), isCircle(0.2)
# parametre pour image6 : plante
# parametre pour image7 : non trouvé
            
dist = img.colorDistance(SimpleCV.Color.ORANGE).dilate(2)

segmented = dist.stretch(2,120).invert()

blobs = segmented.findBlobs()

if blobs:

        balles = blobs.filter([b.isCircle(0.2) for b in blobs])
                
        if balles:
                for balle in balles:
                        img.drawCircle((balle.x,balle.y),balle.radius(),SimpleCV.Color.BLUE,3 )

img.show()

# 需要导入模块: from SimpleCV import Image [as 别名]
# 或者: from SimpleCV.Image import colorDistance [as 别名]
from SimpleCV import Image, Color

bluePincels = Image("ex19.jpg") # Open mm.png too :)

# Get a random value for color in a pixel 100,100 of the image
pixel = bluePincels.getPixel(100,100)
print pixel 

# Distantiate the color of pixel picked previously
colorDist = bluePincels.colorDistance(pixel)

# Binarize the image and invert the colors to show most of the blue parts of the image
colorDistBin = colorDist.binarize(50).invert()
colorDistBin.show()

# 需要导入模块: from SimpleCV import Image [as 别名]
# 或者: from SimpleCV.Image import colorDistance [as 别名]
def process(filename):
    # Preprocessing
    input_img = Image('./images/' + filename)
    img = input_img.colorDistance(Color.BLACK).stretch(PARAM_STRETCH_THRESH_LOW, PARAM_STRETCH_THRESH_HIGH).scale(2)
    img.save('./processed/' + filename)


    # OCR
    ocr_bin = shlex.split('./ocr ./processed/' + filename)
    process = subprocess.Popen(ocr_bin, shell=False, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
    out, err = process.communicate()


    # Parse output
    with open('eng.user-words', 'r') as f:
        choices = f.read().strip().split('\n')

    lines = out.split('\n')
    results = []
    confidences = []
    ratios = []
    flags = []
    ignore_count = 0
    for ln in lines:
        # don't process empty lines
        if(len(ln) == 0):
            continue

        # ignore 1st x lines of heading eg. FAIRPRICE XTRA
        if(ignore_count<HEADING_LINES_COUNT):
            ignore_count+=1
            continue

        # line in format "confidence || line"
        ocr_line = ln.split('||')
        conf, item_and_price = ocr_line[0], ocr_line[1].split(' ')

        # assume price is last word in line
        item, price = ' '.join(item_and_price[:-1]).strip(), item_and_price[-1].strip()

        # Use fuzzy string matching to correct result
        predicted, ratio = FProcess.extractOne(item, choices)
        if ratio >= FLAG_CRITERIA_FUZZY and float(conf) >= FLAG_CRITERIA_OCR:
            output_line = predicted
            flag = ''
        else:
            output_line = item
            flag = 'Flag'

        results.append(output_line + ' ' + price)
        confidences.append(conf)
        ratios.append(str(ratio))
        flags.append(flag)


    # Write results with flags for manual checking
    zipped = zip(results, confidences, ratios, flags)
    mapped = map(lambda tup: ' || '.join(tup), zipped)

    outfile = './results/' + filename + '.txt'
    with open(outfile, 'w') as f:
        f.write('\n'.join(mapped))


    return zipped

# 需要导入模块: from SimpleCV import Image [as 别名]
# 或者: from SimpleCV.Image import colorDistance [as 别名]
# encoding: utf-8

__author__ = 'yonka'

import SimpleCV
from SimpleCV import Image

Image.colorDistance()

# 需要导入模块: from SimpleCV import Image [as 别名]
# 或者: from SimpleCV.Image import colorDistance [as 别名]
#import the modules
import time
import SimpleCV
from SimpleCV import Image
from SimpleCV import Color

hay_alguien = Image("me.jpg")

win = hay_alguien.show()
time.sleep(3)
win.quit()

extraccion_color = hay_alguien.colorDistance(Color.BLACK)
win = extraccion_color.show()
time.sleep(3)
win.quit()

me = hay_alguien - extraccion_color
win = me.show()
time.sleep(3)
win.quit()

print('resultados primera comparacion:')
R = me.meanColor()[2]
print('R: ' + str(R))
G = me.meanColor()[1]
print('G: ' + str(G))
B = me.meanColor()[0]
print('B: ' + str(B))

cam = SimpleCV.Camera()

# 需要导入模块: from SimpleCV import Image [as 别名]
# 或者: from SimpleCV.Image import colorDistance [as 别名]
from SimpleCV import Image, Color
import time

yellowTool = Image('yellowtool.png')

yellowDist = yellowTool.colorDistance((223, 191, 29))

yellowDist.show()
time.sleep(3)

yellowDistBin = yellowDist.binarize(50).invert()

yellowDistBin.show()
time.sleep(3)

onlyYellow = yellowTool - yellowDistBin

onlyYellow.show()
time.sleep(3)

# 需要导入模块: from SimpleCV import Image [as 别名]
# 或者: from SimpleCV.Image import colorDistance [as 别名]
def detectGreenLowQuality(image_file):
	
	original = Image(image_file)

	#binarizedYellowMask = findYellowMask(image_file)
	#subtractedMask = original - binarizedYellowMask
	#subtractedMask.save("subtractedMask.jpg")

	#green_only = subtractedMask.colorDistance((94,116,33))
	#green_only = subtractedMask.colorDistance((50,116,45))
	green_only = original.colorDistance((0,70,6))

	green_only = green_only*6

	mask = green_only.invert()
	#mask.save("green_mask.jpg")


	binarizedMask = mask.binarize().invert()
	#binarizedMask.save("binarized_mask_green.jpg")


	blobs = original.findBlobsFromMask(binarizedMask)


	if blobs == None:
		#print "No green found"
		return detectYellowLowQuality(image_file)


	blobs.image = original
	
	#Assume best blob is the largest blob
	bestBlob = blobs[-1]

	bestBlob.drawMinRect(color=Color.RED,width =10)
	#original.save("foundBlobs_green.jpg")
	

	'''
	#blobs[-1].drawRect(color=Color.RED,width =10)
	coordinates = bestBlob.minRect()


	#Find the center point
	centroidX = bestBlob.minRectX()
	centroidY = bestBlob.minRectY()

	minLeftY = 0
	minRightY = 0

	#Find the bottom left and bottom right coordinates
	for coordinate in coordinates:
		if coordinate[0] < centroidX and coordinate[1] > minLeftY:
			bottomLeft = coordinate
			minLeftY = coordinate[1]
		elif coordinate[0] > centroidX and coordinate[1] > minRightY:
			bottomRight = coordinate
			minRightY = coordinate[1]
			
	'''


	centroidX = bestBlob.minRectX()
	centroidY = bestBlob.minRectY()

	#Have to find out which part of the screen centroid is in
	maxX = original.getNumpy().shape[0]
	maxY = original.getNumpy().shape[1]+100
	

	#assume width of 150 pixels
	return align_center(maxX,maxY,centroidX,centroidY,50,50)