LineBreakMeasurer produces result differ from MS Word / LibreOffice - java

In a swing application, I need to foresee text wrapping of a string like when putting it in a word processor program such as MS Word or LibreOffice. Providing the same width of the displayable area, the same font (face and size) and the same string as following:
displayable area width: 179mm (in a .doc file, setup an A4 portrait page - width = 210mm, margin left = 20mm, right = 11mm; the paragraph is formatted with zero margins)
Font Times New Roman, size 14
Test string: Tadf fdas fdas daebjnbvx dasf opqwe dsa: dfa fdsa ewqnbcmv caqw vstrt vsip d asfd eacc
And the result:
On both MS Word and LibreOffice, that test string is displayed on single line, no text wrapping occurs.
My bellow program report a text wrapping occurs, 2 lines
Line 1: Tadf fdas fdas daebjnbvx dasf opqwe dsa: dfa fdsa ewqnbcmv caqw vstrt vsip d asfd
Line 2: eacc
Is it possible to achieve the same text wrapping effect like MS Word in swing? What could be wrong in the code?
Bellow the my program
public static List<String> wrapText(String text, float maxWidth,
Graphics2D g, Font displayFont) {
// Normalize the graphics context so that 1 point is exactly
// 1/72 inch and thus fonts will display at the correct sizes:
GraphicsConfiguration gc = g.getDeviceConfiguration();
g.transform(gc.getNormalizingTransform());
AttributedCharacterIterator paragraph = new AttributedString(text).getIterator();
Font backupFont = g.getFont();
g.setFont(displayFont);
LineBreakMeasurer lineMeasurer = new LineBreakMeasurer(
paragraph, BreakIterator.getWordInstance(), g.getFontRenderContext());
// Set position to the index of the first character in the paragraph.
lineMeasurer.setPosition(paragraph.getBeginIndex());
List<String> lines = new ArrayList<String>();
int beginIndex = 0;
// Get lines until the entire paragraph has been displayed.
while (lineMeasurer.getPosition() < paragraph.getEndIndex()) {
lineMeasurer.nextLayout(maxWidth);
lines.add(text.substring(beginIndex, lineMeasurer.getPosition()));
beginIndex = lineMeasurer.getPosition();
}
g.setFont(backupFont);
return lines;
}
public static void main(String[] args) throws Exception {
JFrame frame = new JFrame();
frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
JTextPane txtp = new JTextPane();
frame.add(txtp);
frame.setSize(200,200);
frame.setVisible(true);
Font displayFont = new Font("Times New Roman", Font.PLAIN, 14);
float textWith = (179 * 0.0393701f) // from Millimeter to Inch
* 72f; // From Inch to Pixel (User space)
List<String> lines = wrapText(
"Tadf fdas fdas daebjnbvx dasf opqwe dsa: dfa fdsa ewqnbcmv caqw vstrt vsip d asfd eacc",
textWith,
(Graphics2D) txtp.getGraphics(),
displayFont);
for (int i = 0; i < lines.size(); i++) {
System.out.print("Line " + (i + 1) + ": ");
System.out.println(lines.get(i));
}
frame.dispose();
}


+1 for the question
From my experience with text editors it's not possible to achieve exactly the same measuring.
You can try to play with DPI there is default DPI=72 and 96 on windows.
Also you can try to play with all the rendering hints of the Graphics - text antialiasing etc.

Related

How to edit image with opencv to read text with OCR

I'm developing an android app to recognize text in particular plate, as in photo here:
I have to recognize the texts in white (e.g. near to "Mod."). I'm using Google ML Kit's text recognition APIs, but it fails. So, I'm using OpenCV to edit image but I don't know how to emphasize the (white) texts so OCR recognize it. I tried more stuff, like contrast, brightness, gamma correction, adaptive thresholding, but the cases vary a lot depending on how the photo is taken. Do you have any ideas?
Thank u very much.

I coded this example in Python (since OpenCV's SIFT in Android is paid) but you can still use this to understand how to solve it.
First I created this image as a template:
Step 1: Load images
""" 1. Load images """
# load image of plate
src_path = "nRHzD.jpg"
src = cv2.imread(src_path)
# load template of plate (to be looked for)
src_template_path = "nRHzD_template.jpg"
src_template = cv2.imread(src_template_path)
Step 2: Find the template using SIFT and perspective transformation
# convert images to gray scale
src_gray = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY)
src_template_gray = cv2.cvtColor(src_template, cv2.COLOR_BGR2GRAY)
# use SIFT to find template
n_matches_min = 10
template_found, homography = find_template(src_gray, src_template_gray, n_matches_min)
warp = transform_perspective_and_crop(homography, src, src_gray, src_template)
warp_gray = cv2.cvtColor(warp, cv2.COLOR_BGR2GRAY)
warp_hsv = cv2.cvtColor(warp, cv2.COLOR_BGR2HSV)
template_hsv = cv2.cvtColor(src_template, cv2.COLOR_BGR2HSV)
Step 3: Find regions of interest (using the green parts of the template image)
green_hsv_lower_bound = [50, 250, 250]
green_hsv_upper_bound = [60, 255, 255]
mask_rois, mask_rois_img = crop_img_in_hsv_range(warp, template_hsv, green_hsv_lower_bound, green_hsv_upper_bound)
roi_list = separate_rois(mask_rois, warp_gray)
# sort the rois by distance to top right corner -> x (value[1]) + y (value[2])
roi_list = sorted(roi_list, key=lambda values: values[1]+values[2])
Step 4: Apply a Canny Edge detection to the rois (regions of interest)
for i, roi in enumerate(roi_list):
roi_img, roi_x_offset, roi_y_offset = roi
print("#roi:{} x:{} y:{}".format(i, roi_x_offset, roi_y_offset))
roi_img_blur_threshold = cv2.Canny(roi_img, 40, 200)
cv2.imshow("ROI image", roi_img_blur_threshold)
cv2.waitKey()
There are many ways for you to detect the digits, one of the easiest approaches is to run a K-Means Clustering on each of the contours.
Full code:
""" This code shows a way of getting the digit's edges in a pre-defined position (in green) """
import cv2
import numpy as np
def find_template(src_gray, src_template_gray, n_matches_min):
# Initiate SIFT detector
sift = cv2.xfeatures2d.SIFT_create()
""" find grid using SIFT """
# find the keypoints and descriptors with SIFT
kp1, des1 = sift.detectAndCompute(src_template_gray, None)
kp2, des2 = sift.detectAndCompute(src_gray, None)
FLANN_INDEX_KDTREE = 0
index_params = dict(algorithm = FLANN_INDEX_KDTREE, trees = 5)
search_params = dict(checks = 50)
flann = cv2.FlannBasedMatcher(index_params, search_params)
matches = flann.knnMatch(des1, des2, k=2)
# store all the good matches as per Lowe's ratio test.
good = []
for m,n in matches:
if m.distance < 0.7*n.distance:
good.append(m)
if len(good) > n_matches_min:
src_pts = np.float32([kp1[m.queryIdx].pt for m in good ]).reshape(-1,1,2)
dst_pts = np.float32([kp2[m.trainIdx].pt for m in good ]).reshape(-1,1,2)
M, mask = cv2.findHomography(src_pts, dst_pts, cv2.RANSAC,5.0)
matchesMask = mask.ravel().tolist()
h_template, w_template = src_template_gray.shape
pts = np.float32([[0, 0], [0, h_template - 1], [w_template - 1, h_template - 1], [w_template - 1,0]]).reshape(-1,1,2)
homography = cv2.perspectiveTransform(pts, M)
else:
print "Not enough matches are found - %d/%d" % (len(good), n_matches_min)
matchesMask = None
# show matches
draw_params = dict(matchColor = (0, 255, 0), # draw matches in green color
singlePointColor = None,
matchesMask = matchesMask, # draw only inliers
flags = 2)
if matchesMask:
src_gray_copy = src_gray.copy()
sift_matches = cv2.polylines(src_gray_copy, [np.int32(homography)], True, 255, 2, cv2.LINE_AA)
sift_matches = cv2.drawMatches(src_template_gray, kp1, src_gray_copy, kp2, good, None, **draw_params)
return sift_matches, homography
def transform_perspective_and_crop(homography, src, src_gray, src_template_gray):
""" get mask and contour of template """
mask_img_template = np.zeros(src_gray.shape, dtype=np.uint8)
mask_img_template = cv2.polylines(mask_img_template, [np.int32(homography)], True, 255, 1, cv2.LINE_AA)
_ret, contours, hierarchy = cv2.findContours(mask_img_template, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
template_contour = None
# approximate the contour
c = contours[0]
peri = cv2.arcLength(c, True)
approx = cv2.approxPolyDP(c, 0.02 * peri, True)
# if our approximated contour has four points, then
# we can assume that we have found our template
warp = None
if len(approx) == 4:
template_contour = approx
cv2.drawContours(mask_img_template, [template_contour] , -1, (255,0,0), -1)
""" Transform perspective """
# now that we have our template contour, we need to determine
# the top-left, top-right, bottom-right, and bottom-left
# points so that we can later warp the image -- we'll start
# by reshaping our contour to be our finals and initializing
# our output rectangle in top-left, top-right, bottom-right,
# and bottom-left order
pts = template_contour.reshape(4, 2)
rect = np.zeros((4, 2), dtype = "float32")
# the top-left point has the smallest sum whereas the
# bottom-right has the largest sum
s = pts.sum(axis = 1)
rect[0] = pts[np.argmin(s)]
rect[2] = pts[np.argmax(s)]
# compute the difference between the points -- the top-right
# will have the minumum difference and the bottom-left will
# have the maximum difference
diff = np.diff(pts, axis = 1)
rect[1] = pts[np.argmin(diff)]
rect[3] = pts[np.argmax(diff)]
# now that we have our rectangle of points, let's compute
# the width of our new image
(tl, tr, br, bl) = rect
widthA = np.sqrt(((br[0] - bl[0]) ** 2) + ((br[1] - bl[1]) ** 2))
widthB = np.sqrt(((tr[0] - tl[0]) ** 2) + ((tr[1] - tl[1]) ** 2))
# ...and now for the height of our new image
heightA = np.sqrt(((tr[0] - br[0]) ** 2) + ((tr[1] - br[1]) ** 2))
heightB = np.sqrt(((tl[0] - bl[0]) ** 2) + ((tl[1] - bl[1]) ** 2))
# take the maximum of the width and height values to reach
# our final dimensions
maxWidth = max(int(widthA), int(widthB))
maxHeight = max(int(heightA), int(heightB))
# construct our destination points which will be used to
# map the screen to a top-down, "birds eye" view
homography = np.array([
[0, 0],
[maxWidth - 1, 0],
[maxWidth - 1, maxHeight - 1],
[0, maxHeight - 1]], dtype = "float32")
# calculate the perspective transform matrix and warp
# the perspective to grab the screen
M = cv2.getPerspectiveTransform(rect, homography)
warp = cv2.warpPerspective(src, M, (maxWidth, maxHeight))
# resize warp
h_template, w_template, _n_channels = src_template_gray.shape
warp = cv2.resize(warp, (w_template, h_template), interpolation=cv2.INTER_AREA)
return warp
def crop_img_in_hsv_range(img, hsv, lower_bound, upper_bound):
mask = cv2.inRange(hsv, np.array(lower_bound), np.array(upper_bound))
# do an MORPH_OPEN (erosion followed by dilation) to remove isolated pixels
kernel = np.ones((5,5), np.uint8)
mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel)
# Bitwise-AND mask and original image
res = cv2.bitwise_and(img, img, mask=mask)
return mask, res
def separate_rois(column_mask, img_gray):
# go through each of the boxes
# https://stackoverflow.com/questions/41592039/contouring-a-binary-mask-with-opencv-python
border = cv2.copyMakeBorder(column_mask, 1, 1, 1, 1, cv2.BORDER_CONSTANT, value=0)
_, contours, hierarchy = cv2.findContours(border, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE, offset=(-1, -1))
cell_list = []
for contour in contours:
cell_mask = np.zeros_like(img_gray) # Create mask where white is what we want, black otherwise
cv2.drawContours(cell_mask, [contour], -1, 255, -1) # Draw filled contour in mask
# turn that mask into a rectangle
(x,y,w,h) = cv2.boundingRect(contour)
#print("x:{} y:{} w:{} h:{}".format(x, y, w, h))
cv2.rectangle(cell_mask, (x, y), (x+w, y+h), 255, -1)
# copy the img_gray using that mask
img_tmp_region = cv2.bitwise_and(img_gray, img_gray, mask= cell_mask)
# Now crop
(y, x) = np.where(cell_mask == 255)
(top_y, top_x) = (np.min(y), np.min(x))
(bottom_y, bottom_x) = (np.max(y), np.max(x))
img_tmp_region = img_tmp_region[top_y:bottom_y+1, top_x:bottom_x+1]
cell_list.append([img_tmp_region, top_x, top_y])
return cell_list
""" 1. Load images """
# load image of plate
src_path = "nRHzD.jpg"
src = cv2.imread(src_path)
# load template of plate (to be looked for)
src_template_path = "nRHzD_template.jpg"
src_template = cv2.imread(src_template_path)
""" 2. Find the plate (using the template image) and crop it into a rectangle """
# convert images to gray scale
src_gray = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY)
src_template_gray = cv2.cvtColor(src_template, cv2.COLOR_BGR2GRAY)
# use SIFT to find template
n_matches_min = 10
template_found, homography = find_template(src_gray, src_template_gray, n_matches_min)
warp = transform_perspective_and_crop(homography, src, src_gray, src_template)
warp_gray = cv2.cvtColor(warp, cv2.COLOR_BGR2GRAY)
warp_hsv = cv2.cvtColor(warp, cv2.COLOR_BGR2HSV)
template_hsv = cv2.cvtColor(src_template, cv2.COLOR_BGR2HSV)
""" 3. Find regions of interest (using the green parts of the template image) """
green_hsv_lower_bound = [50, 250, 250]
green_hsv_upper_bound = [60, 255, 255]
mask_rois, mask_rois_img = crop_img_in_hsv_range(warp, template_hsv, green_hsv_lower_bound, green_hsv_upper_bound)
roi_list = separate_rois(mask_rois, warp_gray)
# sort the rois by distance to top right corner -> x (value[1]) + y (value[2])
roi_list = sorted(roi_list, key=lambda values: values[1]+values[2])
""" 4. Apply a Canny Edge detection to the rois (regions of interest) """
for i, roi in enumerate(roi_list):
roi_img, roi_x_offset, roi_y_offset = roi
print("#roi:{} x:{} y:{}".format(i, roi_x_offset, roi_y_offset))
roi_img_blur_threshold = cv2.Canny(roi_img, 40, 200)
cv2.imshow("ROI image", roi_img_blur_threshold)
cv2.waitKey()

Apache POI XSLFAutoShape - Shape OffSet property

I am drawing a pptx from scratch using ApachePOI-XSLF (ooxml implementation) and I am struggling to find good documentation and good examples. Also the library isn't easy to follow and not straight forward.
I would like to know how do I set the offset of two shapes of XSFLAutoShape connected by XSLFConnectorShape.
This is my code right now:
XMLSlideShow pptx = new XMLSlideShow();
XSLFSlide slide = pptx.createSlide();
XSLFAutoShape rectangle = slide.createAutoShape();
rectangle.setShapeType(ShapeType.RECT);
rectangle.setAnchor(new Rectangle2D.Double(100, 100, 100, 50));
rectangle.setLineColor(Color.blue);
rectangle.setFillColor(Color.lightGray);
XSLFAutoShape miniCircle = slide.createAutoShape();
miniCircle.setShapeType(ShapeType.ELLIPSE);
miniCircle.setAnchor(new Rectangle2D.Double(rectangle.getAnchor().getMaxX() + 200, rectangle.getAnchor().getCenterY()+50, 1, 1));
miniCircle.setLineColor(Color.yellow);
miniCircle.setFillColor(Color.yellow);
connect(slide, rectangle, miniCircle);
XSLFAutoShape anotherRectangle = slide.createAutoShape();
anotherRectangle.setShapeType(ShapeType.RECT);
anotherRectangle.setAnchor(new Rectangle2D.Double(miniCircle.getAnchor().getMaxX() + 200, 100, 100, 50));
anotherRectangle.setLineColor(Color.blue);
anotherRectangle.setFillColor(Color.lightGray);
connect(slide, miniCircle, anotherRectangle);
and the connect method:
public static void connect(XSLFSlide slide, XSLFAutoShape start, XSLFAutoShape end){
XSLFConnectorShape connector = slide.createConnector();
connector.setAnchor(new Rectangle2D.Double(start.getAnchor().getX() + 100, start.getAnchor().getCenterY(), 100, 1));
CTConnector ctConnector = (CTConnector)connector.getXmlObject();
ctConnector.getSpPr().getPrstGeom().setPrst(STShapeType.STRAIGHT_CONNECTOR_1);
CTNonVisualConnectorProperties cx = ctConnector.getNvCxnSpPr().getCNvCxnSpPr();
// connection start
CTConnection stCxn = cx.addNewStCxn();
stCxn.setId(start.getShapeId());
// side of the rectangle to attach the connector: left=1, bottom=2,right=3, top=4
stCxn.setIdx(3);
CTConnection endCxn = cx.addNewEndCxn();
endCxn.setId(end.getShapeId());
// side of the rectangle to attach the connector: left=1, bottom=2,right=3, top=4
endCxn.setIdx(3);
}
The output of is:
This is the output
But I want this:
This is what I want
p.s. I edit the post because someone thumbs down the post without a reason. I added more info but still complicated because the library is complicated :-/. would mind help and thumbs up again ? If you cannot help at least do not destroy my reputation. I am serious developer. Tkx.

Java Graphics2D Path2D Simplify or call from separate class

I'm wondering if I can clean up my code somehow using a list or call it from another class because I have a lot of exact Path2D coordinates just cluttering my paintComponent.
public void paintComponent(Graphics g)
{ Graphics2D g2=(Graphics2D)g;
super.paintComponent(g2);
//Background
Rectangle background = new Rectangle(0,0,getWidth(),getHeight());
Color skyBlue = new Color(135,206,235);
g2.setColor(skyBlue);
g2.fill (background);
Path2D bunny = new Path2D.Float();
bunny.moveTo(486.63,530.25);
bunny.lineTo(483.13,532.25);
bunny.lineTo(483.13,532.25);
bunny.lineTo(483.13,532.25);
bunny.lineTo(477.38,534.38);
bunny.lineTo(477.38,534.38);
bunny.lineTo(477.38,534.38);
bunny.lineTo(469.88,535.50);
bunny.lineTo(469.88,535.50);
bunny.lineTo(469.88,535.50);
bunny.lineTo(453.50,536.38);
bunny.lineTo(453.50,536.38);
bunny.lineTo(453.50,536.38);
bunny.lineTo(437.63,537.75);
bunny.lineTo(437.63,537.75);
bunny.lineTo(437.63,537.75);
bunny.lineTo(418.75,539.25);
bunny.lineTo(418.75,539.25);
bunny.lineTo(418.75,539.25);
bunny.lineTo(405.00,539.88);
bunny.lineTo(405.00,539.88);
bunny.lineTo(405.00,539.88);
bunny.lineTo(392.25,539.63);
bunny.lineTo(392.25,539.63);
bunny.lineTo(392.25,539.63);
bunny.lineTo(385.50,539.13);
bunny.lineTo(385.50,539.13);
bunny.lineTo(385.50,539.13);
bunny.lineTo(381.00,538.63);
bunny.lineTo(381.00,538.63);
bunny.lineTo(381.00,538.63);
bunny.lineTo(375.50,537.88);
bunny.lineTo(375.50,537.88);
bunny.lineTo(375.50,537.88);
bunny.lineTo(370.13,537.75);
bunny.lineTo(370.13,537.75);
bunny.lineTo(370.13,537.75);
bunny.lineTo(364.88,537.13);
bunny.lineTo(364.88,537.13);
bunny.lineTo(364.88,537.13);
bunny.lineTo(357.75,536.63);
bunny.lineTo(357.75,536.63);
bunny.lineTo(357.75,536.63);
bunny.lineTo(353.50,536.25);
bunny.lineTo(353.50,536.25);
bunny.lineTo(353.50,536.25);
bunny.lineTo(347.88,535.75);
bunny.lineTo(347.88,535.75);
bunny.lineTo(347.88,535.75);
bunny.lineTo(341.75,535.38);
bunny.lineTo(341.75,535.38);
bunny.lineTo(341.75,535.38);
bunny.lineTo(336.25,534.38);
bunny.lineTo(336.25,534.38);
bunny.lineTo(336.25,534.38);
bunny.lineTo(328.25,532.88);
bunny.lineTo(328.25,532.88);
bunny.lineTo(328.25,532.88);
bunny.lineTo(323.00,530.63);
bunny.lineTo(323.00,530.63);
bunny.lineTo(323.00,530.63);
bunny.lineTo(318.50,528.13);
bunny.lineTo(318.50,528.13);
bunny.lineTo(318.50,528.13);
bunny.lineTo(313.50,524.63);
bunny.lineTo(313.50,524.63);
bunny.lineTo(313.50,524.63);
bunny.lineTo(311.63,521.25);
bunny.lineTo(311.63,521.25);
bunny.lineTo(311.63,521.25);
bunny.lineTo(310.38,516.25);
bunny.lineTo(310.38,516.25);
bunny.lineTo(310.38,516.25);
bunny.lineTo(309.88,513.00);
bunny.lineTo(309.88,513.00);
bunny.lineTo(309.88,513.00);
bunny.lineTo(311.13,508.38);
bunny.lineTo(311.13,508.38);
bunny.lineTo(311.13,508.38);
bunny.lineTo(312.25,505.38);
bunny.lineTo(312.25,505.38);
bunny.lineTo(312.25,505.38);
bunny.lineTo(313.00,502.63);
bunny.lineTo(313.00,502.63);
bunny.lineTo(313.00,502.63);
bunny.lineTo(314.75,500.00);
bunny.lineTo(314.75,500.00);
bunny.lineTo(314.75,500.00);
bunny.lineTo(316.38,497.63);
bunny.lineTo(316.38,497.63);
bunny.lineTo(316.38,497.63);
bunny.lineTo(316.25,494.00);
bunny.lineTo(316.25,494.00);
bunny.lineTo(316.25,494.00);
bunny.lineTo(314.88,491.00);
bunny.lineTo(314.88,491.00);
bunny.lineTo(314.88,491.00);
bunny.lineTo(312.88,486.38);
bunny.lineTo(312.88,486.38);
bunny.lineTo(312.88,486.38);
bunny.lineTo(310.13,480.00);
bunny.lineTo(310.13,480.00);
bunny.lineTo(310.13,480.00);
bunny.lineTo(308.50,474.75);
bunny.lineTo(308.50,474.75);
bunny.lineTo(308.50,474.75);
bunny.lineTo(306.63,468.75);
bunny.lineTo(306.63,468.75);
bunny.lineTo(306.63,468.75);
bunny.lineTo(305.25,462.75);
bunny.lineTo(305.25,462.75);
bunny.lineTo(305.25,462.75);
bunny.lineTo(304.88,456.63);
bunny.lineTo(304.88,456.63);
bunny.lineTo(304.88,456.63);
bunny.lineTo(304.88,449.88);
bunny.lineTo(304.88,449.88);
bunny.lineTo(304.88,449.88);
bunny.lineTo(305.00,446.38);
bunny.lineTo(305.00,446.38);
bunny.lineTo(305.00,446.38);
bunny.lineTo(305.88,442.75);
bunny.lineTo(305.88,442.75);
bunny.lineTo(305.88,442.75);
bunny.lineTo(307.63,437.88);
bunny.lineTo(307.63,437.88);
bunny.lineTo(307.63,437.88);
bunny.lineTo(309.25,434.50);
bunny.lineTo(309.25,434.50);
bunny.lineTo(309.25,434.50);
bunny.lineTo(310.50,432.25);
bunny.lineTo(310.50,432.25);
bunny.lineTo(310.50,432.25);
bunny.lineTo(311.63,430.25);
bunny.lineTo(311.63,430.25);
bunny.lineTo(311.63,430.25);
bunny.lineTo(312.50,427.25);
bunny.lineTo(312.50,427.25);
bunny.lineTo(312.50,427.25);
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bunny.closePath();
g2.draw(bunny);
Color gold = new Color(255,215,0);
g2.setColor(gold);
g2.fill(bunny);
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chocoears.lineTo(396.63,275.50);
chocoears.lineTo(400.50,271.38);
chocoears.lineTo(400.50,271.38);
chocoears.lineTo(400.50,271.38);
chocoears.lineTo(406.25,266.75);
chocoears.lineTo(406.25,266.75);
chocoears.lineTo(406.25,266.75);
chocoears.lineTo(411.50,262.13);
chocoears.lineTo(411.50,262.13);
chocoears.lineTo(411.50,262.13);
chocoears.lineTo(414.88,259.75);
chocoears.lineTo(414.88,259.75);
chocoears.lineTo(414.88,259.75);
chocoears.lineTo(420.25,256.63);
chocoears.lineTo(420.25,256.63);
chocoears.lineTo(420.25,256.63);
chocoears.lineTo(424.63,253.88);
chocoears.lineTo(424.63,253.88);
chocoears.lineTo(424.63,253.88);
chocoears.lineTo(427.50,252.88);
chocoears.lineTo(427.50,252.88);
chocoears.lineTo(427.50,252.88);
chocoears.lineTo(431.13,251.50);
chocoears.lineTo(431.13,251.50);
chocoears.lineTo(431.13,251.50);
chocoears.lineTo(434.25,251.13);
chocoears.lineTo(434.25,251.13);
chocoears.lineTo(434.25,251.13);
chocoears.lineTo(437.63,251.00);
chocoears.lineTo(437.63,251.00);
chocoears.lineTo(437.63,251.00);
chocoears.lineTo(442.50,252.25);
chocoears.lineTo(442.50,252.25);
chocoears.lineTo(442.50,252.25);
chocoears.lineTo(445.50,253.75);
chocoears.lineTo(445.50,253.75);
chocoears.lineTo(445.50,253.75);
chocoears.lineTo(447.88,255.25);
chocoears.lineTo(447.88,255.25);
chocoears.lineTo(447.88,255.25);
chocoears.lineTo(450.50,258.25);
chocoears.lineTo(450.50,258.25);
chocoears.lineTo(450.50,258.25);
chocoears.lineTo(451.88,260.75);
chocoears.lineTo(451.88,260.75);
chocoears.lineTo(451.88,260.75);
chocoears.lineTo(453.38,264.13);
chocoears.lineTo(453.38,264.13);
chocoears.lineTo(453.38,264.13);
chocoears.lineTo(454.25,266.88);
chocoears.lineTo(454.25,266.88);
chocoears.lineTo(454.25,266.88);
chocoears.lineTo(455.50,271.13);
chocoears.lineTo(455.50,271.13);
chocoears.lineTo(455.50,271.13);
chocoears.lineTo(455.63,274.75);
chocoears.lineTo(455.63,274.75);
chocoears.lineTo(455.63,274.75);
chocoears.lineTo(456.75,276.50);
chocoears.lineTo(456.75,276.50);
chocoears.lineTo(456.75,276.50);
chocoears.lineTo(458.63,278.00);
chocoears.lineTo(458.63,278.00);
chocoears.lineTo(458.63,278.00);
chocoears.lineTo(460.00,278.88);
chocoears.lineTo(460.00,278.88);
chocoears.lineTo(460.00,278.88);
chocoears.lineTo(461.00,280.75);
chocoears.lineTo(461.00,280.75);
chocoears.lineTo(461.00,280.75);
chocoears.lineTo(462.75,281.00);
chocoears.lineTo(462.75,281.00);
chocoears.lineTo(462.75,281.00);
chocoears.lineTo(464.88,281.88);
chocoears.lineTo(464.88,281.88);
chocoears.lineTo(464.88,281.88);
chocoears.lineTo(467.38,283.00);
chocoears.lineTo(467.38,283.00);
chocoears.lineTo(467.38,283.00);
chocoears.lineTo(470.13,284.50);
chocoears.lineTo(470.13,284.50);
chocoears.lineTo(470.13,284.50);
chocoears.lineTo(472.00,286.13);
chocoears.lineTo(472.00,286.13);
chocoears.closePath();
g2.draw(chocoears);
Color milkChocolate = new Color(111,68,51);
g2.setColor(milkChocolate);
g2.fill(chocoears);
//Grass
Rectangle grass = new Rectangle(0,525,getWidth(),100);
Color lawnGreen = new Color(124,252,0);
g2.setColor(lawnGreen);
g2.fill(grass);
List<Arc2D> blades = new ArrayList<Arc2D>();
for (int x = 0; x < getWidth(); x += 10) {
blades.add(new Arc2D.Double(x, 500, 10, 35, 105, 180, Arc2D.OPEN));
blades.add(new Arc2D.Double(x - 5, 510, 10, 35, 105, 180, Arc2D.OPEN));
blades.add(new Arc2D.Double(x, 520, 10, 35, 105, 180, Arc2D.OPEN));
}
Color yellowGreen = new Color(107, 142, 35);
g2.setColor(yellowGreen);
for (Shape blade : blades) {
g2.draw(blade);
}
Ellipse2D.Double circle = new Ellipse2D.Double(60,100,25,25);
g2.setColor(Color.RED);
g2.fill(circle);
Rectangle box = new Rectangle(150,100,20,80);
g2.setColor(Color.YELLOW);
g2.fill(box);
}
}

Whatever you do I would
create the Path2D objects outside of the paintComponent() method.
add each Path2D object to an ArrayList
in the paintComponent() method you can iterate through the ArrayList to paint each Path2D
Or another approach is to just have a method that:
creates each Path2D object when the class is created
then you paint the Path2D object to a BufferedImage
now that you have a BufferedImage you can create an ImageIcon and Just use a JLabel in you app and you don't need the custom panel.

Heres 2 options I would consider for cleaning up the pathing.
Use SVG, one library I know is Batik found at: http://xmlgraphics.apache.org/batik/
Once I did a project where the paths I needed would be created in photoshop then exported to Illustrator. The file format was each action was line delineated, each line was space delineated and consisted of a set of points with the last entry the command name. Here was a sample input.
10 10 m
15 15 l
10 10 12 12 v
As you can see you just read the file, create your path and do an if test for the last letter on the line and use the appropriate command with for the points. Of course you can make up your own format or procedures but it sure was nice using photoshop for me :)

How to retrieve the native font name in Java?

Is there a way in Java to get the native font name from a Font object?
I get my Font using this code Font.decode("Serif") and for debugging purpose I would like to know the native font used.

It might not be that simple. Some fonts are composed of many physical fonts, using different physical fonts for different glyphs.
For example, on my Windows system the Serif font uses 12 physical fonts:
** TrueType Font: Family=Times New Roman Name=Times New Roman style=0 fileName=C:\Windows\Fonts\TIMES.TTF
** TrueType Font: Family=Wingdings Name=Wingdings style=0 fileName=C:\Windows\Fonts\WINGDING.TTF
** TrueType Font: Family=Symbol Name=Symbol style=0 fileName=C:\Windows\Fonts\SYMBOL.TTF
** TrueType Font: Family=Lucida Sans Name=Lucida Sans Regular style=0 fileName=C:\Java\jdk\jdk1.6.0_37\jre\lib\fonts\LucidaSansRegular.ttf
** TrueType Font: Family=MingLiU Name=MingLiU style=0 fileName=C:\Windows\Fonts\MINGLIU.TTC
** TrueType Font: Family=Lucida Sans Name=Lucida Sans Regular style=0 fileName=C:\Java\jdk\jdk1.6.0_37\jre\lib\fonts\LucidaSansRegular.ttf
** TrueType Font: Family=SimSun Name=SimSun style=0 fileName=C:\Windows\Fonts\SIMSUN.TTC
** TrueType Font: Family=Lucida Sans Name=Lucida Sans Regular style=0 fileName=C:\Java\jdk\jdk1.6.0_37\jre\lib\fonts\LucidaSansRegular.ttf
** TrueType Font: Family=MS Mincho Name=MS Mincho style=0 fileName=C:\Windows\Fonts\MSMINCHO.TTC
** TrueType Font: Family=Batang Name=Batang style=0 fileName=C:\Windows\Fonts\batang.TTC
** TrueType Font: Family=MingLiU-ExtB Name=MingLiU-ExtB style=0 fileName=C:\Windows\Fonts\MINGLIUB.TTC
** TrueType Font: Family=SimSun-ExtB Name=SimSun-ExtB style=0 fileName=C:\Windows\Fonts\SIMSUNB.TTF
The following code can break down a font into its physical components. It uses a reflection hack to access a sun.awt.Font2D object, so use at your own risk (works with Oracle Java 6u37):
import java.awt.Font;
import java.lang.reflect.Method;
import java.util.Locale;
import sun.font.CompositeFont;
import sun.font.Font2D;
import sun.font.PhysicalFont;
public class FontTester
{
public static void main(String... args)
throws Exception
{
Font font = new Font("Serif", Font.PLAIN, 12);
describeFont(font);
}
private static void describeFont(Font font)
throws Exception
{
Method method = font.getClass().getDeclaredMethod("getFont2D");
method.setAccessible(true);
Font2D f = (Font2D)method.invoke(font);
describeFont2D(f);
}
private static void describeFont2D(Font2D font)
{
if (font instanceof CompositeFont)
{
System.out.println("Font '" + font.getFontName(Locale.getDefault()) + "' is composed of:");
CompositeFont cf = (CompositeFont)font;
for (int i = 0; i < cf.getNumSlots(); i++)
{
PhysicalFont pf = cf.getSlotFont(i);
describeFont2D(pf);
}
}
else
System.out.println("-> " + font);
}
}

prunge's answer was nearly perfect, except that it didn't actually expose the native (physical) font's name. The following tiny change to the describeFont2D method does the trick by again leveraging Java reflection:
Don't forget to import java.lang.reflect.Field;
private static void describeFont2D( Font2D font ) throws Exception{
if( font instanceof CompositeFont ){
System.out.println( "Font '"+font.getFontName( Locale.getDefault() )+"' is composed of:" );
CompositeFont cf = ( CompositeFont )font;
for( int i = 0; i<cf.getNumSlots(); i++ ){
PhysicalFont pf = cf.getSlotFont( i );
describeFont2D( pf );
}
}else if( font instanceof CFont ){
Field field = CFont.class.getDeclaredField( "nativeFontName" );
field.setAccessible( true );
String nativeFontName = ( String )field.get( font );
System.out.println( "-> "+nativeFontName );
}else
System.out.println( "-> "+font );
}

This code will get the system fonts if they are available, and will get default families if for some reason they are not available:
static String[] AS_System_Fonts = null;
public static String[] getFontFamilies(){
if( AS_System_Fonts != null ) return AS_System_Fonts;
java.awt.GraphicsEnvironment gEnv = java.awt.GraphicsEnvironment.getLocalGraphicsEnvironment();
AS_System_Fonts = gEnv.getAvailableFontFamilyNames();
if( AS_System_Fonts == null ){ // should not happen
AS_System_Fonts = new String[8];
AS_System_Fonts[0] = "Serif";
AS_System_Fonts[1] = "Sans-Serif";
AS_System_Fonts[2] = "Monospaced";
AS_System_Fonts[3] = "Dialog";
AS_System_Fonts[4] = "Dialog Input";
AS_System_Fonts[5] = "Lucida Bright";
AS_System_Fonts[6] = "Lucida Sans";
AS_System_Fonts[7] = "Lucida Sans Typewriter";
}
return AS_System_Fonts;
}

How to know the resolution screen width and height when i have dual head or triple head from one PC?

I have dual head (VGA output, DVI or HDMI output) from 1 PC using this xrandr --output VGA1 --left-of LVDS1. Each having 1024x768 resolution.
When i use this using Java:
screen = Toolkit.getDefaultToolkit().getScreenSize();
I get a huge two screen width together. As a result my Width and height is huge.
Where i only need to place my application in one screen either VGA or DVI. But using Java how do i know that?
How do i tell that using Toolkit.getDefaultToolkit() ?
Example: (my application has to run where Java is labeled)
Test.java
import java.awt.GraphicsDevice;
import java.awt.GraphicsEnvironment;
public class Test {
public static void main(String[] a) throws Exception {
GraphicsEnvironment ge = GraphicsEnvironment.getLocalGraphicsEnvironment();
GraphicsDevice[] screenDevices = ge.getScreenDevices();
for (int i = 0; i < screenDevices.length; i++) {
System.out.println(screenDevices[i].getIDstring());
DisplayMode dm = screenDevices[i].getDisplayMode();
int screenWidth = dm.getWidth();
int screenHeight = dm.getHeight();
System.out.println("Cake: " + screenWidth + " " + screenHeight);
}
}
}
Output:
:0.0
Cake: 1024 768
:0.1
Cake: 1024 768

I think
GraphicsEnvironment.getLocalGraphicsEnvironment().getScreenDevices()
is what you are looking for. And then from there you can iterate through the screens and get the screen dimension by getDisplayMode()

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