I'm trying to change the font type of the atom labels in RDKIT.
The default font type is 'sans'. I ran this code on colab:
from rdkit import Chem
from rdkit.Chem.Draw import IPythonConsole
from rdkit.Chem import Draw
smiles = 'C1=CC=C(C=C1)I'
mol = [Chem.MolFromSmiles(smiles)]
IPythonConsole.drawOptions.atomLabelFontFace = 'Times New Roman'
pic = Draw.MolsToGridImage(mol, returnPNG=False, subImgSize= (256, 256), molsPerRow=1)
display (pic)
But it seems that the font type doesn't change, neither when I tried other font types. What's wrong?
Use IPythonConsole.drawOptions.fontFile to choose the font.
Times New Roman is not installed in Colab, so you have to install it or you can use the existing serif font (LiberationSerif-Regular.ttf).
from rdkit import Chem
from rdkit.Chem import rdDepictor, Draw
rdDepictor.SetPreferCoordGen(True)
from rdkit.Chem.Draw import IPythonConsole
IPythonConsole.molSize = (600, 300)
IPythonConsole.drawOptions.fontFile = r'/usr/share/fonts/truetype/liberation/LiberationSerif-Regular.ttf'
IPythonConsole.drawOptions.explicitMethyl = True
m = Chem.MolFromSmiles('CC(F)CC(Cl)C(C(=O)O)C(P)CC(S)CC(Br)CN') # Dummy molecule
rdDepictor.Compute2DCoords(m)
m
On your local computer you also need to set the path to the font:
IPythonConsole.drawOptions.fontFile = r'C:\Windows\Fonts\times.ttf'
Related
I'm placeing a rotated image on top of another image of different anchor point in the same figure. However the top image partially covers the bottom image, shown below. Is there a way to remove the black border of the rotated image?
Sample codes here:
from bokeh.server.server import Server
from bokeh.application import Application
from bokeh.application.handlers.function import FunctionHandler
from bokeh.plotting import figure, ColumnDataSource, show
from bokeh.layouts import column
from bokeh.models.tools import PanTool, BoxZoomTool, WheelZoomTool, \
UndoTool, RedoTool, ResetTool, SaveTool, HoverTool
import numpy as np
from collections import namedtuple
from scipy import ndimage
def make_document(doc):
p = figure(match_aspect=True)
Anchor = namedtuple('Anchor', ['x', 'y'])
img1 = np.random.rand(256, 256)
anchor1 = Anchor(x=0, y=0)
img2= np.random.rand(256, 256)
anchor2 = Anchor(x=100, y=100)
img2 = ndimage.rotate(img2, 45, reshape=True)
p.image(image=[img1], x=anchor1.x, y=anchor1.y,
dw=img1.shape[0], dh=img1.shape[1], palette="Greys256")
p.image(image=[img2], x=anchor2.x, y=anchor2.y,
dw=img2.shape[0], dh=img2.shape[1], palette="Greys256")
doc.add_root(column(p, sizing_mode='stretch_both'))
apps = {'/': make_document}
server = Server(apps)
server.start()
server.io_loop.add_callback(server.show, "/")
try:
server.io_loop.start()
except KeyboardInterrupt:
print('keyboard interruption')
print('Done')
When you rotate an image, the new empty regions (black triangles on your image) are by default initialized with 0 (check out the mode and cval options at https://docs.scipy.org/doc/scipy/reference/generated/scipy.ndimage.rotate.html).
If you have a value that you know for sure will never be used in an image, you can pass it as cval. Then, you should be able to manually create a color mapper that maps that value to a transparent pixel and use the mapper instead of the palette (the arg name would be color_mapper).
If you don't have such a value, then you will have to use image_rgba and just make sure that whatever cval you decide to use will result in a transparent pixel.
So my problem is generating an animation from the list img_array. The code above that is basically used to get an image from the folder, annotate it and then save it into the array. Was wondering if anyone would have any suggestions on how to convert the images in the image array into an animation. Any help is appreciated! TIA.
I tried FFmepg and what not but none of them seem to work. I also tried videowriter in OpenCV but when I tried to open the file I get that this file type is not supported or corrupt.
import cv2
import numpy as np
import glob
import matplotlib.pyplot as plt
from skimage import io
import trackpy as tp
import pims
import pylab as pl
##########
pixel_min=23
min_mass=5000
Selector1=[1,2,3,4,5,6,7,11]
##########
frames = pims.ImageSequence('/Users/User/Desktop/eleventh_trial_2/*.tif', as_grey=True)
f1 = tp.locate(frames[0], pixel_min,minmass=min_mass)
plt.figure(1)
ax3=tp.annotate(f1,frames[0])
ax = plt.subplot()
ax.hist(f1['mass'], bins=20)
ax.set(xlabel='mass', ylabel='count');
f = tp.batch(frames[:], pixel_min, minmass=min_mass);
#f = tp.batch(frames[lower_frame:upper_frame], pixel, minmass=min_mass);
t=tp.link_df(f,10,memory=3)
##############
min_mass=8000#12000 #3000#2000 #6000#3000
pixel_min=23;
count=0
img_array = []
for filename in glob.glob('/Users/User/Desktop/eleventh_trial_2/*.tif'):
img = cv2.imread(filename)
height, width, layers = img.shape
size = (width,height)
img2 = io.imread(filename, as_gray=True)
fig, ax = plt.subplots()
ax.imshow(img)
#ax=pl.text(T1[i,1]+13,T1[i,0],str(int(T1[i,9])),color="red",fontsize=18)
T1=t.loc[t['frame']==count]
T1=np.array(T1.sort_values(by='particle'))
for i in Selector1:
pl.text(T1[i,1]+13,T1[i,0],str(int(T1[i,9])),color="red",fontsize=18)
circle2 = plt.Circle((T1[i,1], T1[i,0]), 5, color='r', fill=False)
ax.add_artist(circle2)
count=count+1
img_array.append(fig)
ani = animation.ArtistAnimation(fig, img_array, interval=50, blit=True,repeat_delay=1000)
When I run this I don't get an an error however I can't save the ani as tried in the past either using OpenCV videoWriter.
I found a work around although not the most efficient one. I saved the figures in a separate directory using os and plt.savefig() and then use ImageJ to automatically convert the sequentially numbered and saved figures into an animation. It ain't efficient but gets the job done. I am still open to more efficient answers. Thanks
Using python code we are able to create image segments as shown in the screenshot. our requirement is how to select specific segment in the image and apply different color to it ?
The following is our python snippet
from skimage.segmentation import felzenszwalb, slic,quickshift
from skimage.segmentation import mark_boundaries
from skimage.util import img_as_float
import matplotlib.pyplot as plt
from skimage import measure
from skimage import restoration
from skimage import img_as_float
image = img_as_float(io.imread("leaf.jpg"))
segments = quickshift(image, ratio=1.0, kernel_size=20, max_dist=10,return_tree=False, sigma=0, convert2lab=True, random_seed=42)
fig = plt.figure("Superpixels -- %d segments" % (500))
ax = fig.add_subplot(1, 1, 1)
ax.imshow(mark_boundaries(image, segments))
plt.axis("off")
plt.show()
do this:
seg_num = 64 # desired segment to be colored
color = float64([1,0,0]) # red color
image[segments == 64] = color # assign color to the segment
You can use OpenCV python module - example:
from scipy.misc import imread
from matplotlib import pyplot
import cv2
from cv2 import cv
from SRM import SRM ## Module for Statistical Regional Segmentation
im = imread("lena.png")
im2 = cv2.imread("lena.png")
print type(im), type(im2), im.shape, im2.shape
## Prints <type 'numpy.ndarray'> <type 'numpy.ndarray'> (120, 120, 3) (120, 120, 3)
srm = SRM(im, 256)
segmented = srm.run()
srm2 = SRM(im2, 256)
segmented2 = srm2.run()
pic = segmented/256
pic2 = segmented2/256
pyplot.imshow(pic)
pyplot.imsave("onePic.jpg", pic)
pic = pic.astype('uint8')
cv2.imwrite("onePic2.jpg", pic2)
pyplot.show()
onePic.jpg gives the correct segmented image but onePic2.jpg gives a complete black image.
Converting the datatype to uint8 using pic = pic.astype('uint8') did not help. I still gives a black image!
onePic.jpg using pyplot.imsave():
onePic2.jpg using cv2.imwrite():
Please help!
Before converting pic to uint8, you need to multiply it by 255 to get the correct range.
Although I agree with #sansuiso, in my case I found a possible edge case where my images were being shifted either one bit up in the scale or one bit down.
Since we're dealing with unsigned ints, a single shift means a possible underflow/overflow, and this can corrupt the whole image.
I found cv2's convertScaleAbs with an alpha value of 255.0 to yield better results.
def write_image(path, img):
# img = img*(2**16-1)
# img = img.astype(np.uint16)
# img = img.astype(np.uint8)
img = cv.convertScaleAbs(img, alpha=(255.0))
cv.imwrite(path, img)
This answer goes into more detail.
I encountered a similar situation with face detection, I wonder if there is a better way to execute this, here is my solution here as a reference.
from deepface import DeepFace
import cv2
import matplotlib.pyplot as plt
# import image and output
img_path = "image.jpg"
detected_face = DeepFace.detectFace(img_path, target_size = (128, 128))
plt.imshow(detected_face)
# image color scaling and saving
detected_face = cv2.cvtColor( detected_face,cv2.COLOR_BGR2RGB)
detected_face = cv2.convertScaleAbs(detected_face, alpha=(255.0))
cv2.imwrite("image_thumbnail.jpg", detected_face)
Can i resize images in python to given height and width,i use python 2.5, and i tried as this tutorial http://effbot.org/imagingbook/introduction.htm, and i installed PIL library for images,but when i try to write:
import Image
im = Image.open("test.jpg")
i got undefined variable from import:open
although import Imagedoesn't give errors?
Thanks in advance.
Your import appears to be the problem. Use this instead of "import Image":
from PIL import Image
Then go on like so:
image = Image.open('/example/path/to/image/file.jpg/')
image.thumbnail((80, 80), Image.ANTIALIAS)
image.save('/some/path/thumb.jpg', 'JPEG', quality=88)
To whom it may be of use: Just found that on the official Pillow website. You probably used Pillow and not PIL.
Warning
Pillow >= 1.0 no longer supports “import Image”. Please use “from PIL
import Image” instead.
This script resizes all images in a given folder:
import PIL
from PIL import Image
import os, sys
path = "path"
dirs = os.listdir( path )
def resize():
for item in dirs:
if os.path.isfile(path+item):
img = Image.open(path+item)
f, e = os.path.splitext(path+item)
img = img.resize((width,hight ), Image.ANTIALIAS)
img.save(f + '.jpg')
resize()
you can resize image using skimage
from skimage.transform import resize
import matplotlib.pyplot as plt
img=plt.imread('Sunflowers.jpg')
image_resized =resize(img, (244, 244))
plotting resized image
plt.subplot(1,2,1)
plt.imshow(img)
plt.title('original image')
plt.subplot(1,2,2)
plt.imshow(image_resized)
plt.title('image_resized')
for further code illustration : scikit-image
import os
from PIL import Image
imagePath = os.getcwd() + 'childFolder/myImage.png'
newPath = os.getcwd() + 'childFolder/newImage.png'
cropSize = 150, 150
img = Image.open(imagePath)
img.thumbnail(cropSize, Image.ANTIALIAS)
img.save(newPath)
if you have troubles with PIL the other alternative could be scipy.misc library. Assume that you want to resize to size 48x48 and your image located in same directory as script
from from scipy.misc import imread
from scipy.misc import imresize
and then:
img = imread('./image_that_i_want_to_resize.jpg')
img_resized = imresize(img, [48, 48])