def find():
global clipboard_image
try:
img = LAYERS_DICT['image']
img = img.resize((root.winfo_screenwidth(), root.winfo_screenheight()))
img = img.filter(ImageFilter.FIND_EDGES())
canvas.image_tk = ImageTk.PhotoImage(img)
image_id = LAYERS_DICT['canvas'].create_image(0, 0, anchor=NW)
LAYERS_DICT['canvas'].itemconfigure(image_id, image=canvas.image_tk)
LAYERS_DICT['image'] = img
LAYERS_DICT['img'] = image_id
except NameError:
pass
try:
clipboard_image = ImageGrab.grabclipboard()
clipboard_image = clipboard_image.resize(
(root.winfo_screenwidth(), root.winfo_screenheight()))
clipboard_image = clipboard_image.filter(ImageFilter.FIND_EDGES())
canvas.image_tk = ImageTk.PhotoImage(clipboard_image)
image_id = LAYERS_DICT['canvas'].create_image(0, 0, anchor=NW)
LAYERS_DICT['canvas'].itemconfigure(image_id, image=canvas.image_tk)
LAYERS_DICT['image'] = clipboard_image
LAYERS_DICT['img'] = image_id
except Exception:
pass
if SAVED == False:
root.title('Shape Editor • Unsaved')
else:
root.title(f'Shape Editor • {str(root.filename)} •')
def augment_data(label_path):
label = label_path.split('/')[-1]
if label == "0":
files = os.listdir(label_path)
for file in files:
file_name = file.split(".")[0]
file_ext = file.split(".")[1]
img = Image.open(label_path + "/" + file)
img_rotate_120 = img.rotate(120)
img_rotate_120.save(label_path + "/" + file_name + "rotate_120." + file_ext)
img_enhance = img.filter(ImageFilter.EDGE_ENHANCE())
img_edge = img.filter(ImageFilter.FIND_EDGES())
img_enhance.save(label_path + "/" + file_name + "enhance." + file_ext)
img_edge.save(label_path + "/" + file_name + "edge." + file_ext)
if label == "1":
files = os.listdir(label_path)
for file in files:
file_name = file.split(".")[0]
file_ext = file.split(".")[1]
img = Image.open(label_path + "/" + file)
img_rotate_120 = img.rotate(120)
img_rotate_120.save(label_path + "/" + file_name + "rotate_120." + file_ext)
img_enhance = img.filter(ImageFilter.EDGE_ENHANCE())
img_edge = img.filter(ImageFilter.FIND_EDGES())
img_enhance.save(label_path + "/" + file_name + "enhance." + file_ext)
img_edge.save(label_path + "/" + file_name + "edge." + file_ext)
def edgestext():
img = Image.open("lionimg.jpg")
img.show()
img = img.filter(ImageFilter.FIND_EDGES()) # [-1-1-1-18-1-1-1-1]
img.save("edgesimg.jpg")
img.show()
pass
def augment_data(label_path):
label = label_path.split('/')[-1]
if label == "120":
files = os.listdir(label_path)
for file in files:
file_name = file.split(".")[0]
file_ext = file.split(".")[1]
img = Image.open(label_path + "/" + file)
img_rotate_90 = img.rotate(90)
img_rotate_90.save(label_path + "/" + file_name + "rotate_90." + file_ext)
if label == "Stop":
files = os.listdir(label_path)
for file in files:
file_name = file.split(".")[0]
file_ext = file.split(".")[1]
img = Image.open(label_path + "/" + file)
img_rotate_90 = img.rotate(90)
img_rotate_120 = img.rotate(120)
img_rotate_90.save(label_path + "/" + file_name + "rotate_90." + file_ext)
img_rotate_120.save(label_path + "/" + file_name + "rotate_120." + file_ext)
if label == "Right":
files = os.listdir(label_path)
for file in files:
file_name = file.split(".")[0]
file_ext = file.split(".")[1]
img = Image.open(label_path + "/" + file)
img_enhance = img.filter(ImageFilter.EDGE_ENHANCE())
img_edge = img.filter(ImageFilter.FIND_EDGES())
img_enhance.save(label_path + "/" + file_name + "enhance." + file_ext)
img_edge.save(label_path + "/" + file_name + "edge." + file_ext)
if label == "Left":
files = os.listdir(label_path)
for file in files:
file_name = file.split(".")[0]
file_ext = file.split(".")[1]
img = Image.open(label_path + "/" + file)
img_enhance = img.filter(ImageFilter.EDGE_ENHANCE())
img_edge = img.filter(ImageFilter.FIND_EDGES())
img_gaussian = img.filter(ImageFilter.GaussianBlur(radius = 3))
img_invert = ImageChops.invert(img)
img_enhance.save(label_path + "/" + file_name + "enhance." + file_ext)
img_edge.save(label_path + "/" + file_name + "edge." + file_ext)
img_gaussian.save(label_path + "/" + file_name + "gaussian." + file_ext)
img_invert.save(label_path + "/" + file_name + "invert." + file_ext)
def edges():
#img=Image.open("imgsayphoto.jpg")
speak("may I get the image : ")
img1 = takecommand().lower()
if "photo" in img1:
img = Image.open("photo.jpg")
img.show()
img = img.filter(ImageFilter.FIND_EDGES()) #[-1-1-1-18-1-1-1-1]
img.save("edgesimg.jpg")
img.show()
else:
speak("sorry")
pass
def applyFilter(imgObj, outpLoc, filterType, customArgs=[0]):
"""Aplly filter to an image, if arguments arr required use the list customArgs
Help from: https://hhsprings.bitbucket.io/docs/programming/examples/python/PIL/ImageFilter.html"""
# format the output dir: if it doesnt exist create it
if os.path.isdir(outpLoc):
pass
else:
os.makedirs(outpLoc)
# check if the imgObj is a thumbnail already
if "filtr" in imgObj.fileName:
# don't do anything
return False
# apply filter based on filter type:
# open image file
im = Image.open(imgObj.fileLOC)
# apply filter based on filterType argument
if filterType == "BLUR":
currImFltr = im.filter(ImageFilter.BoxBlur(customArgs[0]))
elif filterType == "CONTOUR":
currImFltr = im.filter(ImageFilter.CONTOUR())
elif filterType == "DETAIL":
currImFltr = im.filter(ImageFilter.DETAIL())
elif filterType == "EDGE_ENHANCE":
currImFltr = im.filter(ImageFilter.EDGE_ENHANCE_MORE())
elif filterType == "EMBOSS":
currImFltr = im.filter(ImageFilter.EMBOSS())
elif filterType == "FIND_EDGES":
currImFltr = im.filter(ImageFilter.FIND_EDGES())
elif filterType == "UNSHARP_MASK":
currImFltr = im.filter(
ImageFilter.UnsharpMask(radius=customArgs[0],
percent=customArgs[1],
threshold=customArgs[2]))
else:
print(f"no filter for filter type: {filterType}")
return False
# save filtered image
currImFltr.save(outpLoc + "filtr-" + filterType + "-" + imgObj.fileName)
def process_image_findedges(img_name):
img = Image.open(pathlib.Path(img_name))
img = img.filter(ImageFilter.FIND_EDGES())
img.save(export_folder + "/FindEdges_" + format(Path(img_name).stem) +
image_extension)
print("FindEdges Filter added successfully")
import PIL
from PIL import Image, ImageStat, ImageFilter
im = Image.open('brain_enhanced_4.jpg')
im1 = im.filter(ImageFilter.FIND_EDGES())
im1.save('brain_sobel_enhanced.jpg')
#!/usr/python2.7.12
#-*-coding:Latin-1 -*
from PIL import Image
from PIL import ImageFilter
from PIL import ImageOps
import numpy as np
import matplotlib.pyplot as plt
img = Image.open('MissionU1.pbm')
#img.show()
img = img.filter(ImageFilter.FIND_EDGES())
for x in range(img.size[0]):
for y in range(img.size[1]):
pixel = img.getpixel((x, y))
if pixel > 77.5:
img.putpixel((x, y), 255)
else:
img.putpixel((x, y), 0)
img.save("u1Contour.pbm")
img = img.filter(ImageFilter.MaxFilter(
3)) #remplace le pixel du milieu par la plus haute intensité
img.show()
img = img.filter(ImageFilter.SMOOTH) #lisse l'image
#img.show()
img = img.filter(ImageFilter.MinFilter(3)) #inverse max
#img.show()
img = img.filter(ImageFilter.DETAIL) #accentue les details
img.show()
img.save("finalimage.pbm")
def export(self, r=10):
sharp = Image.new('RGB', (self.w, self.h), (127, 127, 127))
for name, pos1, pos2, scale in self.objects:
if name == 'truck':
ox, oy = pos2
dist = ((pos1[0] - pos2[0])**2 + (pos1[1] - pos2[1])**2)**0.5
for n in range(int(dist / scale), 0, -1):
x = int(pos1[0] + (pos2[0] - pos1[0]) / (dist / scale) * n)
y = int(pos1[1] + (pos2[1] - pos1[1]) / (dist / scale) * n)
dir = math.degrees(math.atan2(ox - x, oy - y))
figure = Image.open(
os.path.dirname(__file__) + '/samples/truck_gray.png')
sharp.paste(
figure.rotate(dir - 90,
fillcolor=(127, 127, 127)).resize(
(int(scale * 2), int(scale * 2))),
(int(x - scale), int(y - scale)))
ox, oy = x, y
if name == 'footprints':
foot = 0
ox, oy = pos2
dist = ((pos1[0] - pos2[0])**2 + (pos1[1] - pos2[1])**2)**0.5
for n in range(int(dist / scale), 0, -1):
if foot == 1:
figure = Image.open(
os.path.dirname(__file__) +
'/samples/footprint1_gray.png')
foot = 0
else:
figure = Image.open(
os.path.dirname(__file__) +
'/samples/footprint2_gray.png')
foot = 1
x = int(pos1[0] + (pos2[0] - pos1[0]) / (dist / scale) * n)
y = int(pos1[1] + (pos2[1] - pos1[1]) / (dist / scale) * n)
dir = math.degrees(math.atan2(ox - x, oy - y))
sharp.paste(
figure.rotate(dir - 90,
fillcolor=(127, 127, 127)).resize(
(int(scale), int(scale))),
(int(x - scale / 2), int(y - scale / 2)))
ox, oy = x, y
sharp = sharp.filter(ImageFilter.GaussianBlur(radius=int(r / 4)))
guassian = sharp.filter(ImageFilter.GaussianBlur(radius=int(r / 2)))
white = ImageEnhance.Brightness(
sharp.filter(ImageFilter.GaussianBlur(radius=int(r * 2))).filter(
ImageFilter.FIND_EDGES())).enhance(40)
white = ImageEnhance.Brightness(
white.filter(ImageFilter.GaussianBlur(radius=r))).enhance(2)
out = Image.blend(Image.blend(sharp, guassian, 0.9), white, 0.25)
b = Image.new('RGB', (self.w, self.h), (127, 127, 127))
p = white.load()
d = ImageDraw.Draw(b)
for x in range(self.w):
for y in range(self.h):
if p[x, y][0] > 1 and random.randint(1, 500) == 10:
polygon = []
size = random.randint(r // 2, r * 2)
for f in range(3):
polygon.append((random.randint(x - size, x + size),
random.randint(y - size, y + size)))
d.polygon(polygon, fill=(size * 40 - 250, ) * 4)
b = b.filter(ImageFilter.GaussianBlur(radius=5))
out = Image.blend(out, b, 0.25)
out.save(os.path.dirname(__file__) + '/snowDisplacement.png')
def find_edges(image: Image.Image) -> Image.Image:
return _apply_filter(image, ImageFilter.FIND_EDGES())
from PIL import Image
from PIL import ImageFilter
from PIL import ImageOps
import numpy as np
import matplotlib.pyplot as plt
U2_surface = Image.open('U2_surface.pbm')
U2_surface = U2_surface.filter(ImageFilter.FIND_EDGES())
nblines = U2_surface.size[1]
nbrows = U2_surface.size[0]
i = 0
j = 0
while i < nbrows:
while j < nblines:
pixels = U2_surface.getpixel((i, j))
if pixels > 190:
U2_surface.putpixel((i, j), 0)
else:
U2_surface.putpixel((i, j), 255)
j += 1
i += 1
j = 0
#U2_surface = U2_surface.filter(ImageFilter.MedianFilter(3))
U2_surface.show()
