def drawGrid(self, placed_list, source_dir=None,
cm_per_pixel=15.0, blend_cm=200,
dim=4096):
# compute blend diameter in consistent pixel units
blend_px = int(blend_cm/cm_per_pixel)+1
if blend_px % 2 == 0:
blend_px += 1
(xmin, ymin, xmax, ymax) = ImageList.coverage(self.image_list)
grid_m = (dim * cm_per_pixel) / 100.0
print "grid square size = (%.2f x %.2f)" % (grid_m, grid_m)
#xpixel = (xmax - xmin) * 100.0 / cm_per_pixel
#ypixel = (ymax - ymin) * 100.0 / cm_per_pixel
f = open('gdalscript.sh', 'w')
f.write('#!/bin/sh\n\n')
f.write('rm -f tile*.tif\n')
count = 0
y = ymin
while y < ymax:
x = xmin
while x < xmax:
print "grid = (%.2f %.2f)" % (x, y)
base = "tile%03d" % count
jpgfile = base + ".jpg"
tifffile = base + ".tif"
images = self.drawSquare( placed_list, source_dir=source_dir,
cm_per_pixel=cm_per_pixel,
blend_cm=blend_cm,
bounds=(x, y, x+grid_m, y+grid_m),
file=jpgfile)
if len(images):
(ul_lon, ul_lat) = ImageList.cart2wgs84(x, y+grid_m,
self.ref_lon,
self.ref_lat)
(lr_lon, lr_lat) = ImageList.cart2wgs84(x+grid_m, y,
self.ref_lon,
self.ref_lat)
cmd = 'gdal_translate -a_srs "+proj=latlong +datum=WGS84" '
cmd += '-of GTiff -co "INTERLEAVE=PIXEL" '
cmd += '-a_ullr %.15f %.15f %.15f %.15f ' % \
( ul_lon, ul_lat, lr_lon, lr_lat )
cmd += '%s %s\n' % (jpgfile, tifffile)
f.write('echo running gdal_translate...\n')
f.write(cmd)
count += 1
x += grid_m
y += grid_m
f.write('rm output.tif\n')
f.write('echo running gdal_merge\n')
f.write('gdal_merge.py -o output.tif tile*.tif\n')
f.write('echo running gdalwarp\n')
f.write('rm output_3857.tif\n')
f.write('gdalwarp -t_srs EPSG:3857 output.tif output_3857.tif\n')
f.write('echo running gdal2tiles.py\n')
f.write('rm -rf output\n')
f.write('gdal2tiles.py -z 16-21 -s_srs=EPSG:3857 output_3857.tif output\n')
f.close()
def drawImages(self, draw_list=[], source_dir=None,
cm_per_pixel=15.0, blend_cm=200,
bounds=None, file=None, keypoints=False):
print "drawImages() bounds = %s" % str(bounds)
# compute blend diameter in consistent pixel units
blend_px = int(blend_cm/cm_per_pixel)+1
if blend_px % 2 == 0:
blend_px += 1
if bounds == None:
(xmin, ymin, xmax, ymax) = ImageList.coverage(draw_list)
else:
(xmin, ymin, xmax, ymax) = bounds
x = int(100.0 * (xmax - xmin) / cm_per_pixel)
y = int(100.0 * (ymax - ymin) / cm_per_pixel)
print "New image dimensions: (%d %d)" % (x, y)
base_image = np.zeros((y,x,3), np.uint8)
for image in reversed(draw_list):
w, h, out = self.drawImage(image, source_dir,
cm_per_pixel,
keypoints,
bounds=(xmin, ymin, xmax, ymax))
base_image = self.compositeOverlayBottomup(base_image, out,
blend_px)
#cv2.imshow('output', base_image)
#cv2.waitKey()
cv2.imwrite(file, base_image)
def reviewPoint(self, lon_deg, lat_deg, ref_lon, ref_lat):
(x, y) = ImageList.wgs842cart(lon_deg, lat_deg, ref_lon, ref_lat)
print "Review images touching %.2f %.2f" % (x, y)
review_list = ImageList.getImagesCoveringPoint(self.image_list, x, y, pad=25.0, only_placed=False)
#print " Images = %s" % str(review_list)
for image in review_list:
print " %s -> " % image.name,
for j, pairs in enumerate(image.match_list):
if len(pairs):
print "%s (%d) " % (self.image_list[j].name, len(pairs)),
print
r2 = image.coverage()
p = ImageList.getImagesCoveringRectangle(self.image_list, r2)
p_names = []
for i in p:
p_names.append(i.name)
print " possible matches: %d" % len(p_names)
class R_CNN:
list = ImageList()
roi_pooling = ROIPooling()
"""
Segments the given image and returns the segmented image.
@param img: Image item retrieved from ImageList
"""
def SegmentImages(img):
pass
class User:
userImage = ""
list = ImageList()
itemsLibrary = ItemsLibrary()
"""
Insert user provided image into the list.
@param item: Image which is provided by user and stored in the array
"""
def InsertToList(item):
pass
def reviewPoint(self, lon_deg, lat_deg, ref_lon, ref_lat):
(x, y) = ImageList.wgs842cart(lon_deg, lat_deg, ref_lon, ref_lat)
print("Review images touching %.2f %.2f" % (x, y))
review_list = ImageList.getImagesCoveringPoint(self.image_list,
x,
y,
pad=25.0,
only_placed=False)
#print " Images = %s" % str(review_list)
for image in review_list:
print(" %s -> " % image.name, )
for j, pairs in enumerate(image.match_list):
if len(pairs):
print("%s (%d) " % (self.image_list[j].name, len(pairs)), )
print
r2 = image.coverage()
p = ImageList.getImagesCoveringRectangle(self.image_list, r2)
p_names = []
for i in p:
p_names.append(i.name)
print(" possible matches: %d" % len(p_names))
def drawSquare(self, placed_list, source_dir=None,
cm_per_pixel=15.0, blend_cm=200, bounds=None, file=None):
(xmin, ymin, xmax, ymax) = bounds
xcenter = (xmin + xmax) * 0.5
ycenter = (ymin + ymax) * 0.5
pad = (xmax - xmin) * 0.5
draw_list = ImageList.getImagesCoveringPoint(placed_list,
xcenter, ycenter, pad,
only_placed=True)
if len(draw_list):
self.drawImages( draw_list, source_dir=source_dir,
cm_per_pixel=cm_per_pixel, blend_cm=blend_cm,
bounds=bounds, file=file)
return draw_list
class ROIPooling:
list = ImageList()
# list of ItemDetails
itemDetails = []
"""
Classify item types of image details.
@param img: Image item retrieved from R-CNN class
"""
def ClassifyItemType(img):
return img
"""
Frame objects on images
@param item: Image item retrieved from R-CNN class
"""
def FrameImage(item):
pass
def __init__(self, framesDir, width = 533, height = 300, width_margin_ratio = 0.95, height_margin_ratio = 0.95) : self.framesDir = framesDir self.width = width self.height = height self.width_margin_ratio = width_margin_ratio self.height_margin_ratio = height_margin_ratio self.win_width = self.width * self.width_margin_ratio self.win_height = self.height * self.height_margin_ratio self.curr_frame = 0 self.last_frame = fc.frame_counter(framesDir) - 1 self.playing = 0 self.playing_thread = 0 self.progress_label_width = 2 * fc.ndigits(self.last_frame) + 2 self.progress_label_text = "%d/%d" % (self.curr_frame+1, self.last_frame+1) self.appended_images = ImgList.Model()
def drawSquare(self,
placed_list,
source_dir=None,
cm_per_pixel=15.0,
blend_cm=200,
bounds=None,
file=None):
(xmin, ymin, xmax, ymax) = bounds
xcenter = (xmin + xmax) * 0.5
ycenter = (ymin + ymax) * 0.5
pad = (xmax - xmin) * 0.5
draw_list = ImageList.getImagesCoveringPoint(placed_list,
xcenter,
ycenter,
pad,
only_placed=True)
if len(draw_list):
self.drawImages(draw_list,
source_dir=source_dir,
cm_per_pixel=cm_per_pixel,
blend_cm=blend_cm,
bounds=bounds,
file=file)
return draw_list
def drawImages(self,
draw_list=[],
source_dir=None,
cm_per_pixel=15.0,
blend_cm=200,
bounds=None,
file=None,
keypoints=False):
print "drawImages() bounds = %s" % str(bounds)
# compute blend diameter in consistent pixel units
blend_px = int(blend_cm / cm_per_pixel) + 1
if blend_px % 2 == 0:
blend_px += 1
if bounds == None:
(xmin, ymin, xmax, ymax) = ImageList.coverage(draw_list)
else:
(xmin, ymin, xmax, ymax) = bounds
x = int(100.0 * (xmax - xmin) / cm_per_pixel)
y = int(100.0 * (ymax - ymin) / cm_per_pixel)
print "New image dimensions: (%d %d)" % (x, y)
base_image = np.zeros((y, x, 3), np.uint8)
for image in reversed(draw_list):
w, h, out = self.drawImage(image,
source_dir,
cm_per_pixel,
keypoints,
bounds=(xmin, ymin, xmax, ymax))
base_image = self.compositeOverlayBottomup(base_image, out,
blend_px)
#cv2.imshow('output', base_image)
#cv2.waitKey()
cv2.imwrite(file, base_image)
def new_item():
import ImageList
response.content_type = 'application/json'
return ImageList.getImageList()
def drawGrid(self,
placed_list,
source_dir=None,
cm_per_pixel=15.0,
blend_cm=200,
dim=4096):
# compute blend diameter in consistent pixel units
blend_px = int(blend_cm / cm_per_pixel) + 1
if blend_px % 2 == 0:
blend_px += 1
(xmin, ymin, xmax, ymax) = ImageList.coverage(self.image_list)
grid_m = (dim * cm_per_pixel) / 100.0
print "grid square size = (%.2f x %.2f)" % (grid_m, grid_m)
#xpixel = (xmax - xmin) * 100.0 / cm_per_pixel
#ypixel = (ymax - ymin) * 100.0 / cm_per_pixel
f = open('gdalscript.sh', 'w')
f.write('#!/bin/sh\n\n')
f.write('rm -f tile*.tif\n')
count = 0
y = ymin
while y < ymax:
x = xmin
while x < xmax:
print "grid = (%.2f %.2f)" % (x, y)
base = "tile%03d" % count
jpgfile = base + ".jpg"
tifffile = base + ".tif"
images = self.drawSquare(placed_list,
source_dir=source_dir,
cm_per_pixel=cm_per_pixel,
blend_cm=blend_cm,
bounds=(x, y, x + grid_m, y + grid_m),
file=jpgfile)
if len(images):
(ul_lon,
ul_lat) = ImageList.cart2wgs84(x, y + grid_m,
self.ref_lon, self.ref_lat)
(lr_lon,
lr_lat) = ImageList.cart2wgs84(x + grid_m, y,
self.ref_lon, self.ref_lat)
cmd = 'gdal_translate -a_srs "+proj=latlong +datum=WGS84" '
cmd += '-of GTiff -co "INTERLEAVE=PIXEL" '
cmd += '-a_ullr %.15f %.15f %.15f %.15f ' % \
( ul_lon, ul_lat, lr_lon, lr_lat )
cmd += '%s %s\n' % (jpgfile, tifffile)
f.write('echo running gdal_translate...\n')
f.write(cmd)
count += 1
x += grid_m
y += grid_m
f.write('rm output.tif\n')
f.write('echo running gdal_merge\n')
f.write('gdal_merge.py -o output.tif tile*.tif\n')
f.write('echo running gdalwarp\n')
f.write('rm output_3857.tif\n')
f.write('gdalwarp -t_srs EPSG:3857 output.tif output_3857.tif\n')
f.write('echo running gdal2tiles.py\n')
f.write('rm -rf output\n')
f.write(
'gdal2tiles.py -z 16-21 -s_srs=EPSG:3857 output_3857.tif output\n')
f.close()
