def __main__():
args = argparser()
out = args['output']
orig_img = image.load(args['image']).convert('RGB')
if args['contrast'] != None:
orig_img = ImageEnhance.Contrast(orig_img).enhance(args['contrast'])
orig_img = resizer.resize(orig_img, 1, ANTI_FONT_DISTORTION)
fit_ratio = resizer.fit_in_ratio(orig_img.size, term.size())
if args['ratio']:
fit_ratio *= args['ratio']
img = resizer.resize(orig_img, fit_ratio, (1, 1))
lows, mids, highs = posterizer.thresholds(img)
if args['color'] != None:
lows = map(lambda val: bound_addition(val, args['color']), lows)
mids = map(lambda val: bound_addition(val, args['color']), mids)
highs = map(lambda val: bound_addition(val, args['color']), highs)
colors = posterizer.posterize(img, mids, highs)
# img.show()
shapes = resizer.resize(orig_img, fit_ratio, (2, 4))
# shapes.show()
shapes = shapes.convert('L')
threshold = otsu.threshold(shapes.histogram())
# mask = shapes.point(lambda val: 255 if val <= threshold else 0).convert('1')
# threshold = otsu.threshold(shapes.histogram(mask))
if args['shape'] != None:
threshold = bound_addition(threshold, args['shape'])
shapes = shapes.point(lambda val: 255
if val > threshold else 0).convert('1')
# shapes.show()
dots = Canvas()
w, h = shapes.size
for index, pixel in enumerate(list(shapes.getdata()), 0):
if pixel:
dots.set(index % w, index // w)
# out.write(dots.frame(0,0,w,h))
# out.write('\n')
w, h = colors.size
for index, pixel in enumerate(list(colors.getdata()), 0):
x = (index % w) * 2
y = (index // w) * 4
miniframe = unicode(dots.frame(x, y, x + 2, y + 4), 'utf-8')
miniframe = miniframe if len(miniframe) else u'\u2800'
out.write(color_print.rgb2esc(pixel, [0, 0, 0], lows, highs,
miniframe))
if not (1 + index) % w:
out.write('\n')
def loadin():
x=['sqr','sphr']
ret=[]
lbl=[]
ret2=[]
lbl2=[]
ret_labels=[]
cnt=0
print('start')
for j in range(110):
cnt=0
for i in x:
if j%30==0:
print('x')
if j<=2:
cloud=dl.DataLoader('../data_pcd/'+x[cnt]+str(j)+'.pcd')
for i in range(6):
cloud[i]=rs.resize(cloud[i],250)
ret.append(cloud)
if x[cnt]=='sqr':
lbl.append(0)
else:
lbl.append(1)
else:
cloud=dl.DataLoader('../data_pcd/'+x[cnt]+str(j)+'.pcd')
for i in range(6):
cloud[i]=rs.resize(cloud[i],250)
ret2.append(cloud)
if x[cnt]=='sqr':
lbl2.append(0)
else:
lbl2.append(1)
cnt+=1
#print(ret)
try:
np.save('ret',ret)
np.save('lbl',lbl)
np.save('ret2',ret2)
np.save('lbl2',lbl2)
except:
print('saving unsuccesful')
return ret,lbl,ret2,lbl2
def load_image(path):
img = cv2.imread(path)
img = resizer.fill_to_square(img)
img = resizer.resize(img, IMAGE_SIZE)
img = np.asarray(img) / (255.0) # normalize Data
img = img.reshape(-1, IMAGE_SIZE, IMAGE_SIZE, 3)
return img
def loadin_pred(file):
ret=[]
cloud=dl.DataLoader(file)
for i in range(6):
cloud[i]=rs.resize(ab.fill(cloud[i]),250)
cv2.imwrite('as'+str(i)+'.jpg',cloud[i])
ret.append(cloud)
return ret
def __call__(self, image):
try:
opened_image = Image.open(image.path)
squared_image = square(opened_image)
except OSError:
return image.path
for resolution in self.output_folders:
resized_image = resize(resolution, squared_image)
save_path = self.output_folders[resolution]
save_name = '_'.join([image.prefix, image.name])
print("saving image %s in resolution %dpx" %
(save_name, resolution))
resized_image.save(path.join(save_path, save_name))
def openFile(self):
options = QFileDialog.Options()
options |= QFileDialog.DontUseNativeDialog
tuple = QFileDialog.getOpenFileName(
None,
"QFileDialog.getOpenFileName()",
"",
"All Files (*);;PNG (*.png);;JPEG (*.jpeg *jpg)",
options=options)
fileName = tuple[0]
if fileName != '':
self.input_file_name = os.path.split(fileName)[1]
img1 = cv2.imread(fileName, cv2.IMREAD_GRAYSCALE)
img_converted = convert(img1)
self.imgDraw.setPixmap(QPixmap(img_converted))
self.input_img = img1
#Converted to set to a QLabel for Matcheswindow
self.input_img_converted = convert(resize(img1, 300))
import argparse
import os
import re
import resizer
parser = argparse.ArgumentParser()
parser.add_argument('--output_dir', type=str, action='store', default='.')
parser.add_argument('--width', type=int, action='store', default=32)
parser.add_argument('--height', type=int, action='store', default=32)
parser.add_argument('input_dir', type=str, action='store')
args = parser.parse_args()
if args.input_dir == args.output_dir:
print('Error: output directory is same as input directory.')
exit()
if not os.path.exists(args.output_dir):
os.makedirs(args.output_dir)
print("resize target=(%d, %d)" % (args.width, args.height))
files = os.listdir(args.input_dir)
files = [file for file in files if not re.match('^\.', file)]
for i, file in enumerate(files):
inputname = os.path.join(args.input_dir, file)
outputname = os.path.join(args.output_dir, file)
print('%d: input=%s, output=%s' % (i, inputname, outputname))
resizer.resize(inputname, outputname, args.width, args.height)
def upload():
if(request.cookies.get("pwauname")):
email = str(request.cookies.get("pwauname"))
projectName = request.form.get("project_name")
projectImage = request.files.get("project_image")
projectImageName = ""
json_file = open(f"{APP_ROOT}/db/data.json", "r")
data = json.load(json_file)
json_file.close()
for key,value in data.items():
if((value["email"]==email) and (value["projectName"]==projectName)):
flash("Project already exists!")
return redirect(url_for("index"))
if(projectImage):
os.makedirs(f"{APP_ROOT}/static/folders/{email}/{projectName}")
projectImageName = projectImage.filename
target = f"{APP_ROOT}/static/folders/{email}/{projectName}"
destination = "/".join([target, projectImageName])
projectImage.save(destination)
else:
flash("No image provided!")
return redirect(url_for("index"))
json_file = open(f"{APP_ROOT}/db/data.json", "r")
data = json.load(json_file)
json_file.close()
newDataId = str(uuid.uuid4())
curDate = dt.datetime.now()
day = curDate.strftime("%d-%m-%Y")
newData = {
newDataId: {
"email": email,
"projectName": str(projectName),
"date": str(day),
# "projectImage": str(projectImageName),
"48": "logo48.png",
"72": "logo72.png",
"96": "logo96.png",
"144": "logo144.png",
"196": "logo196.png",
"512": "logo512.png",
"app": "app.js",
"serviceWorker": "serviceWorker.js",
"manifest": "manifest.json"
}
}
data.update(newData)
json_file = open(f"{APP_ROOT}/db/data.json", "w")
json_file.seek(0)
json.dump(data, json_file, indent=2)
json_file.close()
resizer.resize(48,48,email,projectName,projectImageName)
resizer.resize(72,72,email,projectName,projectImageName)
resizer.resize(96,96,email,projectName,projectImageName)
resizer.resize(144,144,email,projectName,projectImageName)
resizer.resize(196,196,email,projectName,projectImageName)
resizer.resize(512,512,email,projectName,projectImageName)
os.remove(
f"{APP_ROOT}/static/folders/{email}/{projectName}/{projectImageName}"
)
data = {
"manifest_version": 2,
"name": f"{projectName}",
"short_name": f"{projectName}",
"start_url": "/",
"display": "standalone",
"background_color": "#FFFFFF",
"theme_color": "#FFFFFF",
"orientation": "portrait",
"icons": [
{
"src": "./logo48.png",
"type": "image/png",
"sizes": "48x48"
},
{
"src": "./logo72.png",
"type": "image/png",
"sizes": "72x72"
},
{
"src": "./logo96.png",
"type": "image/png",
"sizes": "96x96"
},
{
"src": "./logo144.png",
"type": "image/png",
"sizes": "144x144"
},
{
"src": "./logo196.png",
"type": "image/png",
"sizes": "196x196"
},
{
"src": "./logo512.png",
"type": "image/png",
"sizes": "512x512"
}
],
"scope": "/"
}
json_file = open(f"{APP_ROOT}/static/folders/{email}/{projectName}/manifest.json", "w")
json_file.seek(0)
json.dump(data, json_file, indent=2)
json_file.close()
flash(f"{projectName} created!")
return redirect(url_for('index'))
else:
return redirect(url_for('login'))
def load_image(self, path):
img = cv2.imread(path) # Read Image as numbers
img_square = resizer.fill_to_square(img)
img_resized = resizer.resize(img_square, self.IMAGE_SIZE)
return img_resized
def __init__(self, input_window, mainwindow_object, modified=False):
super().__init__()
self.input_window = input_window
self.setupUi(input_window)
self.mainwindow_object = mainwindow_object
self.input_pic = mainwindow_object.input_img_converted
#Original Bilder die zum Input gematched wurden
self.match1 = convert(resize(self.mainwindow_object.top5Objects[0].imgdata, 150))
self.match2 = convert(resize(self.mainwindow_object.top5Objects[1].imgdata, 150))
self.match3 = convert(resize(self.mainwindow_object.top5Objects[2].imgdata, 150))
self.match4 = convert(resize(self.mainwindow_object.top5Objects[3].imgdata, 150))
self.match5 = convert(resize(self.mainwindow_object.top5Objects[4].imgdata, 150))
#Modifizierte Bilder die zum Input gematched wurden
self.match1_modified = convert(resize(self.mainwindow_object.top5Objects[0].img_data_skeleton, 150))
self.match2_modified = convert(resize(self.mainwindow_object.top5Objects[1].img_data_skeleton, 150))
self.match3_modified = convert(resize(self.mainwindow_object.top5Objects[2].img_data_skeleton, 150))
self.match4_modified = convert(resize(self.mainwindow_object.top5Objects[3].img_data_skeleton, 150))
self.match5_modified = convert(resize(self.mainwindow_object.top5Objects[4].img_data_skeleton, 150))
#Matching Ergebnisse der Einzelnen Matches
self.match1Result = rgb2qimage(cv2.resize(self.mainwindow_object.top5Objects[0].matching_result,(360,300)))
self.match2Result = rgb2qimage(cv2.resize(self.mainwindow_object.top5Objects[1].matching_result,(360,300)))
self.match3Result = rgb2qimage(cv2.resize(self.mainwindow_object.top5Objects[2].matching_result,(360,300)))
self.match4Result = rgb2qimage(cv2.resize(self.mainwindow_object.top5Objects[3].matching_result,(360,300)))
self.match5Result = rgb2qimage(cv2.resize(self.mainwindow_object.top5Objects[4].matching_result,(360,300)))
self.matchresults = [self.match1Result, self.match2Result, self.match3Result, self.match4Result,
self.match5Result]
# Ab hier Events
# Vorschaubilder
self.m1.setPixmap(QPixmap(self.match1))
self.m2.setPixmap(QPixmap(self.match2))
self.m3.setPixmap(QPixmap(self.match3))
self.m4.setPixmap(QPixmap(self.match4))
self.m5.setPixmap(QPixmap(self.match5))
self.inputIMG.setPixmap(QPixmap(self.input_pic))
if modified == True:
# Vorschau der modifizierten Bilder
self.modified_label.setText("Modifiziertes Bild")
self.original_label.setText("Original Bild")
self.skel1.setPixmap(QPixmap(self.match1_modified))
self.skel2.setPixmap(QPixmap(self.match2_modified))
self.skel3.setPixmap(QPixmap(self.match3_modified))
self.skel4.setPixmap(QPixmap(self.match4_modified))
self.skel5.setPixmap(QPixmap(self.match5_modified))
self.skel_input.setPixmap(QPixmap(convert(resize(self.mainwindow_object.input_sift_object.img_data_skeleton, 300))))
# VorschauNamen
self.match1Name.setText(self.mainwindow_object.top5Objects[0].imgname)
self.match2Name.setText(self.mainwindow_object.top5Objects[1].imgname)
self.match3Name.setText(self.mainwindow_object.top5Objects[2].imgname)
self.match4Name.setText(self.mainwindow_object.top5Objects[3].imgname)
self.match5Name.setText(self.mainwindow_object.top5Objects[4].imgname)
self.inputImgName.setText(self.mainwindow_object.input_file_name)
# Buttons
self.match1Btn.clicked.connect(self.showMatch1)
self.match2Btn.clicked.connect(self.showMatch2)
self.match3Btn.clicked.connect(self.showMatch3)
self.match4Btn.clicked.connect(self.showMatch4)
self.match5Btn.clicked.connect(self.showMatch5)
self.backBtn.clicked.connect(self.closeSecond)