コード例 #1
0
ファイル: tesseractOCR.py プロジェクト: gcca/urb-vi
    def leerPlaca(self, binarizado):
        """
        Args:
            img: imagen que contiene el texto, obtenida con la
                funcion cv2.imread.
        Returns:
            El string del texto en la imagen.
        """
        cvmat_image = cv.fromarray(binarizado)
        imgbincv = cv.GetImage(cvmat_image)
        # GetImage fuente de un error, revisar

        # Configuración del tesseract
        api = tesseract.TessBaseAPI()
        api.Init(".", "eng", tesseract.OEM_DEFAULT)
        api.SetPageSegMode(tesseract.PSM_AUTO)

        # Enviando imagen binarizada al tesseract
        tesseract.SetCvImage(imgbincv, api)
        text = api.GetUTF8Text()
        text = re.sub(r'\W+', '', text)
        return text
コード例 #2
0
ファイル: OCR.py プロジェクト: piaoger/NavPalFloorplans
def getText(image0):
    #thicken the border in order to make tesseract feel happy
    offset = textOffset
    height, width, channel = image0.shape
    image1=cv2.copyMakeBorder(image0, offset, offset,offset,offset,\
                            cv2.BORDER_CONSTANT,value=rgbWhite)

    #set up tesseract API
    api = tesseract.TessBaseAPI()
    api.Init(".", "eng", tesseract.OEM_DEFAULT)

    api.SetPageSegMode(tesseract.PSM_AUTO)
    height1, width1, channel1 = image1.shape

    #star text extraction
    cvmat_image = cv.fromarray(image1)
    iplimage = cv.GetImage(cvmat_image)
    #extract texts
    tesseract.SetCvImage(iplimage, api)
    text = api.GetUTF8Text()
    conf = api.MeanTextConf()
    return text, conf
コード例 #3
0
def hs_histogram(src):
    # Convert to HSV
    hsv = cv.CreateImage(cv.GetSize(src), 8, 3)
    cv.CvtColor(src, hsv, cv.CV_BGR2HSV)

    # Extract the H and S planes
    h_plane = cv.CreateMat(src.rows, src.cols, cv.CV_8UC1)
    s_plane = cv.CreateMat(src.rows, src.cols, cv.CV_8UC1)
    cv.Split(hsv, h_plane, s_plane, None, None)
    planes = [h_plane, s_plane]

    h_bins = 30
    s_bins = 32
    hist_size = [h_bins, s_bins]
    # hue varies from 0 (~0 deg red) to 180 (~360 deg red again */
    h_ranges = [0, 180]
    # saturation varies from 0 (black-gray-white) to
    # 255 (pure spectrum color)
    s_ranges = [0, 255]
    ranges = [h_ranges, s_ranges]
    scale = 10
    hist = cv.CreateHist([h_bins, s_bins], cv.CV_HIST_ARRAY, ranges, 1)
    cv.CalcHist([cv.GetImage(i) for i in planes], hist)
    (_, max_value, _, _) = cv.GetMinMaxHistValue(hist)

    hist_img = cv.CreateImage((h_bins*scale, s_bins*scale), 8, 3)

    for h in range(h_bins):
        for s in range(s_bins):
            bin_val = cv.QueryHistValue_2D(hist, h, s)
            intensity = cv.Round(bin_val * 255 / max_value)
            cv.Rectangle(hist_img,
                         (h*scale, s*scale),
                         ((h+1)*scale - 1, (s+1)*scale - 1),
                         cv.RGB(intensity, intensity, intensity),
                         cv.CV_FILLED)
    return hist_img
コード例 #4
0
def createHist(img):
    #cv.CvtColor(img,img,cv.CV_BGR2HSV)
    b_plane = cv.CreateImage((img.width, img.height), 8, 1)
    g_plane = cv.CreateImage((img.width, img.height), 8, 1)
    r_plane = cv.CreateImage((img.width, img.height), 8, 1)

    cv.Split(img, b_plane, g_plane, r_plane, None)
    planes = [b_plane, g_plane, r_plane]

    bins = 4
    b_bins = bins
    g_bins = bins
    r_bins = bins

    hist_size = [b_bins, g_bins, r_bins]
    b_range = [0, 255]
    g_range = [0, 255]
    r_range = [0, 255]

    ranges = [b_range, g_range, r_range]
    hist = cv.CreateHist(hist_size, cv.CV_HIST_ARRAY, ranges, 1)
    cv.CalcHist([cv.GetImage(i) for i in planes], hist)
    cv.NormalizeHist(hist, 1)
    return hist
コード例 #5
0
    def leerPlaca(self, binarizado):
        """
        Args:
            img: imagen que contiene el texto, obtenida con la
                funcion cv2.imread.
        Returns:
            El string del texto en la imagen.
        """
        cvmat_image = cv.fromarray(binarizado)
        imgbincv = cv.GetImage(cvmat_image)
        # GetImage fuente de un error, revisar

        # Configuración del tesseract
        api = tesseract.TessBaseAPI()
        api.Init('.', 'eng', tesseract.OEM_DEFAULT)
        api.SetVariable("tessedit_char_whitelist",
                        "0123456789ABCDFGHIJKLMNOPQRSTVWXYZ-UE")
        api.SetPageSegMode(tesseract.PSM_AUTO)

        # Enviando imagen binarizada al tesseract
        tesseract.SetCvImage(imgbincv, api)
        text = api.GetUTF8Text()
        text = re.sub(r'\W+', '', text)
        return text
コード例 #6
0
ファイル: camera.py プロジェクト: minhduccse/MAVProxy
def transmit_thread():
    '''thread for image transmit to GCS'''
    state = mpstate.camera_state

    tx_count = 0
    skip_count = 0
    bsend = block_xmit.BlockSender(0, bandwidth=state.settings.bandwidth, debug=False)
    state.bsocket = MavSocket(mpstate.mav_master[0])
    state.bsend2 = block_xmit.BlockSender(mss=96, sock=state.bsocket, dest_ip='mavlink', dest_port=0, backlog=5, debug=False)
    state.bsend2.set_bandwidth(state.settings.bandwidth2)

    while not state.unload.wait(0.02):
        bsend.tick(packet_count=1000, max_queue=state.settings.maxqueue1)
        state.bsend2.tick(packet_count=1000, max_queue=state.settings.maxqueue2)
        check_commands()
        if state.transmit_queue.empty():
            continue

        (frame_time, regions, im_full, im_640) = state.transmit_queue.get()
        if state.settings.roll_stabilised:
            roll=0
        else:
            roll=None
        pos = get_plane_position(frame_time, roll=roll)

        # this adds the latlon field to the regions
        log_joe_position(pos, frame_time, regions)

        # filter out any regions outside the boundary
        if state.boundary_polygon:
            regions = cuav_region.filter_boundary(regions, state.boundary_polygon, pos)
            regions = cuav_region.filter_regions(im_full, regions, min_score=state.settings.minscore)

        state.xmit_queue = bsend.sendq_size()
        state.xmit_queue2 = state.bsend2.sendq_size()
        state.efficiency = bsend.get_efficiency()
        state.bandwidth_used = bsend.get_bandwidth_used()
        state.rtt_estimate = bsend.get_rtt_estimate()

        jpeg = None

        if len(regions) > 0:
            lowscore = 0
            highscore = 0
            for r in regions:
                lowscore = min(lowscore, r.score)
                highscore = max(highscore, r.score)
                
            if state.settings.transmit:
                # send a region message with thumbnails to the ground station
                thumb = None
                if state.settings.send1:
                    thumb_img = cuav_mosaic.CompositeThumbnail(cv.GetImage(cv.fromarray(im_full)),
                                                               regions,
                                                               thumb_size=state.settings.thumbsize)
                    thumb = scanner.jpeg_compress(numpy.ascontiguousarray(cv.GetMat(thumb_img)), state.settings.quality)

                    pkt = ThumbPacket(frame_time, regions, thumb, state.frame_loss, state.xmit_queue, pos)

                    buf = cPickle.dumps(pkt, cPickle.HIGHEST_PROTOCOL)
                    bsend.set_bandwidth(state.settings.bandwidth)
                    bsend.set_packet_loss(state.settings.packet_loss)
                    bsend.send(buf,
                               dest=(state.settings.gcs_address, state.settings.gcs_view_port),
                               priority=1)
                # also send thumbnails via 900MHz telemetry
                if state.settings.send2 and highscore >= state.settings.minscore2:
                    if thumb is None or lowscore < state.settings.minscore2:
                        # remove some of the regions
                        regions = cuav_region.filter_regions(im_full, regions, min_score=state.settings.minscore2)
                        thumb_img = cuav_mosaic.CompositeThumbnail(cv.GetImage(cv.fromarray(im_full)),
                                                                   regions,
                                                                   thumb_size=state.settings.thumbsize)
                        thumb = scanner.jpeg_compress(numpy.ascontiguousarray(cv.GetMat(thumb_img)), state.settings.quality)
                        pkt = ThumbPacket(frame_time, regions, thumb, state.frame_loss, state.xmit_queue, pos)

                        buf = cPickle.dumps(pkt, cPickle.HIGHEST_PROTOCOL)
                    state.bsend2.set_bandwidth(state.settings.bandwidth2)
                    state.bsend2.send(buf, priority=highscore)

        # Base how many images we send on the send queue size
        send_frequency = state.xmit_queue // 3
        if send_frequency == 0 or (tx_count+skip_count) % send_frequency == 0:
            jpeg = scanner.jpeg_compress(im_640, state.settings.quality)

        if jpeg is None:
            skip_count += 1
            continue

        # keep filtered image size
        state.jpeg_size = 0.95 * state.jpeg_size + 0.05 * len(jpeg)
        
        tx_count += 1

        if state.settings.gcs_address is None:
            continue
        bsend.set_packet_loss(state.settings.packet_loss)
        bsend.set_bandwidth(state.settings.bandwidth)
        pkt = ImagePacket(frame_time, jpeg, state.xmit_queue, pos)
        str = cPickle.dumps(pkt, cPickle.HIGHEST_PROTOCOL)
        bsend.send(str,
                   dest=(state.settings.gcs_address, state.settings.gcs_view_port))
コード例 #7
0
from cv2 import cv
import numpy as np
from pylab import *
import glob
import os 


i = 0
for files in glob.glob('D:/pic/car/*.jpg'):
    filepath,filename = os.path.split(files)
    image = cv2.imread(filepath + '/' + filename)
     # image = cv2.imread('D:/pic/car2.jpg')
    h,w = image.shape[:2]
    #灰度化
    gray = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
    grayIPimage = cv.GetImage(cv.fromarray(gray))
    sobel  = cv.CreateImage((w, h),cv2.IPL_DEPTH_16S, 1)  #创建一张深度为16位有符号(-65536~65535)的的图像区域保持处理结果
    cv.Sobel(grayIPimage,sobel,2,0,7)         # 进行x方向的sobel检测
    temp  = cv.CreateImage(cv.GetSize(sobel),cv2.IPL_DEPTH_8U, 1)       #图像格式转换回8位深度已进行下一步处理
    cv.ConvertScale(sobel, temp,0.00390625, 0)
    cv.Threshold(temp, temp, 0, 255, cv2.THRESH_OTSU)
    kernal = cv.CreateStructuringElementEx(3,1, 1, 0, 0)
    cv.Dilate(temp, temp,kernal,2)
    cv.Erode(temp, temp,kernal,4)
    cv.Dilate(temp, temp,kernal,2)
#     cv.ShowImage('1', temp)
    kernal = cv.CreateStructuringElementEx(1,3, 0, 1, 0)
    cv.Erode(temp, temp,kernal,1)
    cv.Dilate(temp, temp,kernal,3)
#     cv.ShowImage('2', temp)
    temp = np.asarray(cv.GetMat(temp))
コード例 #8
0
 def writeImage(self):
     if(self._videoWriter != None):
         cv.WriteFrame(self._videoWriter, cv.GetImage(self._currentImage))
コード例 #9
0
ファイル: fun1.py プロジェクト: a550461053/GMCM2017
    # print cv.GetCaptureProperty(capture, cv.CV_CAP_PROP_POS_FRAMES) # frame == index

    # 2. 当前帧frame2赋给frame2gray
    frame2 = cv.QueryFrame(capture)
    cv.CvtColor(frame2, frame2gray, cv.CV_RGB2GRAY) # 原图frame2转换为frame2gray格式

    # 3. 图像做帧差法,结果为res
    cv.AbsDiff(frame1gray, frame2gray, res) # 比较frame1gray 和 frame2gray 的差,结果输出给res
    # res = cv2.absdiff(frame1gray, frame2gray) # 此为cv2新版api
    cv.ShowImage("After AbsDiff", res)

    # 4. 保存res作为前景目标foreground
    # cv.Convert(res, gray)
    # out_foreground.write(np.uint8(res)) # 保存为前景目标
    # out_foreground.write(np.asarray(cv.GetMat(res)))
    cv.WriteFrame(out_foreground, cv.GetImage(res)) # res格式为cvmat格式,转化为iplimage格式

    # 5. 平滑处理
    # cv.Smooth(res, res, cv.CV_BLUR, 5, 5) # 光滑一下res

    # 6. 形态学变换,开闭操作
    element = cv.CreateStructuringElementEx(5*2+1, 5*2+1, 5, 5,  cv.CV_SHAPE_RECT) # CreateStructuringElementEx(cols, rows, anchorX, anchorY, shape, values=None)

    cv.MorphologyEx(res, res, None, None, cv.CV_MOP_OPEN) # cv2.morphologyEx(src, op, kernel[, dst[, anchor[, iterations[, borderType[, borderValue]]]]])
    cv.MorphologyEx(res, res, None, None, cv.CV_MOP_CLOSE) # 形态学变换相应的开 闭操作

    # 7. 二值化阈值处理:对得到的前景进行阈值选择,去掉伪前景
    cv.Threshold(res, res, 10, 255, cv.CV_THRESH_BINARY) # 二值化 cv.Threshold(src, dst, threshold, maxValue, thresholdType)


    # 8. blob提取电梯区域 ------------- 未完
コード例 #10
0
print image1.dtype.itemsize
width_step = width * image1.dtype.itemsize
print width_step
#method 1
iplimage = cv.CreateImageHeader((width1, height1), cv.IPL_DEPTH_8U, channel1)
cv.SetData(iplimage, image1.tostring(),
           image1.dtype.itemsize * channel1 * (width1))
tesseract.SetCvImage(iplimage, api)

text = api.GetUTF8Text()
conf = api.MeanTextConf()
image = None
print "..............."
print "Ocred Text: %s" % text
print "Cofidence Level: %d %%" % conf

#method 2:
cvmat_image = cv.fromarray(image1)
iplimage = cv.GetImage(cvmat_image)
print iplimage

tesseract.SetCvImage(iplimage, api)
#api.SetImage(m_any,width,height,channel1)
text = api.GetUTF8Text()
conf = api.MeanTextConf()
image = None
print "..............."
print "Ocred Text: %s" % text
print "Cofidence Level: %d %%" % conf
api.End()
コード例 #11
0
#s_plane = cv.Threshold(s_plane, s_plane, minSat, 255, cv.CV_THRESH_BINARY)

h_bins = 30
s_bins = 32
hist_size = [h_bins, s_bins]

# hue varies from 0 (~0 deg red) to 180 (~360 deg red again */
h_ranges = [0, 180]
# saturation varies from 0 (black-gray-white) to
# 255 (pure spectrum color)
s_ranges = [0, 255]
ranges = [h_ranges, s_ranges]
scale = 10
hist = cv.CreateHist([h_bins, s_bins], cv.CV_HIST_ARRAY, ranges, 1)
cv.CalcHist([cv.GetImage(i) for i in planes], hist)

#SetHistogramm ???
#Normalize

im2 = cv.LoadImage("../img/build.png")
hsv2 = cv.CreateImage(cv.GetSize(im2), 8, 3)
cv.CvtColor(im2, hsv2, cv.CV_BGR2HSV)
h_plane2 = cv.CreateImage(cv.GetSize(im2), 8, 1)
s_plane2 = cv.CreateImage(cv.GetSize(im2), 8, 1)
cv.Split(hsv2, h_plane2, s_plane2, None, None)

res = cv.CreateImage((im2.width, im2.height), 8, 3)
cv.CalcBackProject([h_plane2, s_plane2], res, hist)

cv.MeanShift(res, (10, 10, 30, 30),
コード例 #12
0
        pre_y_flag = y_flag
        if count > 0:
            y_flag = 1
        else:
            y_flag = 0
        if pre_y_flag != y_flag:
            h_pos.append(y)

match_img = []
tmp_mg = []

for i in range(0, leng / 2):
    cv2.waitKey(3)
    cv2.rectangle(image, (w_pos[i], h_pos[i]), (w_pos[i + 1], h_pos[i + 1]),
                  (255, 255, 0))
    imgIP = cv.GetImage(cv.fromarray(image))
    cv.SetImageROI(imgIP, (w_pos[2 * i], h_pos[2 * i], w_pos[2 * i + 1] -
                           w_pos[2 * i], h_pos[2 * i + 1] - h_pos[2 * i]))
    img_cache = cv.CreateImage(
        (w_pos[2 * i + 1] - w_pos[2 * i], h_pos[2 * i + 1] - h_pos[2 * i]),
        cv.IPL_DEPTH_8U, 3)
    cv.Copy(imgIP, img_cache)
    match_img.append(img_cache)
    #    cv.SaveImage('ss'+bytes(i)+'.jpg',match_img[i])
    cv.ResetImageROI(imgIP)
#    cv.ShowImage('window'+bytes(i),match_img[i])

#aa=image.copy((range(10,20),range(20,100)))
#cv2.imshow("hello",aa)
#cv2.imshow("img",image)
print w_pos