I have been trying to teach myself more advanced methods in Python but can't seem to find anything similar to this problem to base my code off of.
First question: Is this only way to display an image in the terminal to install Pillow? I would prefer not to, as I'm trying to then teach what I learn to a very beginner student. My image.show() function doesn't do anything.
Second question: What is the best way to go about lowering the brightness of all RGB pixels in an image by 20%? What I have below doesn't do anything to the alter the brightness, but it also can compile completely. I would prefer the most simple way to go about this as far as importing minimal libraries.
Third Question: How do I made a new picture instead of changing the original? (IE- lower brightness 20%, "image-decreasedBrightness.jpg" is created from "image.jpg")
here is my code - sorry it isn't formatted correctly. Every time i tried to indent it would tab down to the tags bar.
import Image
import ImageEnhance
fileToBeOpened = raw_input("What is the file name? Include file type.")
image = Image.open(fileToBeOpened)
def decreaseBrightness(image):
image.show()
image = image.convert('L')
brightness = ImageEnhance.Brightness(image)
image = brightness.enhance(20)
image.show()
return image
decreaseBrightness(image)
To save the image as a file, there's an example on the documentation:
from PIL import ImageFile
fp = open("lena.pgm", "rb")
p = ImageFile.Parser()
while 1:
s = fp.read(1024)
if not s:
break
p.feed(s)
im = p.close()
im.save("copy.jpg")
The key function is im.save.
For a more in-depth solution, get a nice beverage, find a comfortable place to sit and enjoy your read:
Pillow 3.4.x Documentation.
Related
So working with windows, python 2.7 and simplecv I am making a live video with my webcam and want simplecv to give me a grayscale version of the video. Is there any simple way to achieve that?
I found the command
grayscale()
on the opencv page, which should do exactly that but when I run it I get the error:
NameError: name "grayscale" is not defined
I am currently using this prewritten code for object tracking but I don't know whether I should use the command I found, and where in the code I should put it, does anybody have an idea? :
print __doc__
import SimpleCV
display = SimpleCV.Display()
cam = SimpleCV.Camera()
normaldisplay = True
while display.isNotDone():
if display.mouseRight:
normaldisplay = not(normaldisplay)
print "Display Mode:", "Normal" if normaldisplay else "Segmented"
img = cam.getImage().flipHorizontal()
dist = img.colorDistance(SimpleCV.Color.BLACK).dilate(2)
segmented = dist.stretch(200,255)
blobs = segmented.findBlobs()
if blobs:
circles = blobs.filter([b.isCircle(0.2) for b in blobs])
if circles:
img.drawCircle((circles[-1].x, circles[-1].y), circles[-1].radius(),SimpleCV.Color.BLUE,3)
if normaldisplay:
img.show()
else:
segmented.show()
There are multiple ways to do this in SimpleCV.
One way has been already described, it's the toGray() method.
There's also a way you can do this with gaussian blur, which also helps to remove image noise:
from SimpleCV import *
img = Image("simplecv")
img.applyGaussianFilter(grayscale=True)
After the third line, img object contains the image with a lot less high-frequency noise, and converted to grayscale.
You may check out pyimagesearch.com who works with OpenCV, but he explains why applying Gaussian Blur is a good idea.
In simple cv theres a function called toGray() for example:
import SimpleCV as sv
img = img.jpg
sv.img.jpg.toGray()
return gimg.jpg
Okay, first thing first. This is a near duplicate of this question.
However, the issue I am facing is slightly different in a critical way.
In my application, I read a generic file name in, load said image, and display it. Where it gets tricky is I have overlay the appearance of being 'highlighted'. To do this, I was using the Image.blend() function, and blending it with a straight yellow image.
However, when dealing with blend, I was fighting the error that the two images are not compatible to be blended. To solve this, I opened the sample image I had in paint, and just pasted yellow over the whole thing, and saved it as a copy.
It just occurred to me that this will fail when a different type of image is read in by file name. Remember this needs to be generic.
So my question is: Instead of making a copy of the image manually, can I get python to generate one by copying the image and modifying it so it is solid yellow? Note: I do not need to save it after, so just making it happen is enough.
Unfortunately, I am not allowed to share my code, but hopefully the following will give an idea of what I need:
from PIL import Image
desiredWidth = 800
desiredHeight = 600
primaryImage = Image.open("first.jpg").resize((desiredWidth, desiredHeight), Image.ANTIALIAS)
# This is the thing I need fixed:
highlightImage = Image.open("highlight.jpg").resize((desiredWidth, desiredHeight), Image.ANTIALIAS)
toDisplay = Image.blend(primaryImage, highlightImage, 0.3)
Thanks to anyone who can help.
Sounds like you want to make a new image:
fill_color = (255,255,0) #define the colour as (R,G,B) tuple
highlightImage = Image.new(primaryImage.mode, #same mode as the primary
primaryImage.size, #same size as the primary
fill_color)#and the colour defined above
this creates a new image with the same mode and size as the already opened image, but with a solid colour. Cheers.
Also if you are using Pillow instead of original PIL you can even get the color by name:
from PIL.ImageColor import getcolor
overlay = 'yellow'
fill_color = getcolor(overlay, primaryImage.mode)
So I have implemented the following screenshot functionality into my game just to log progress and stuff like that. This is my code:
pygame.image.save(screen, save_file)
Pretty basic. I recently upgraded to python 3.3 and have since been having the issue of distorted colors using this function. Here is what I mean:
Distorted Color:
So it looks quite nice, but it isn't how it supposed to be. This is the actual image:
Is this a known issue or is it just me? Are there any fixes to it or is it just a broken function at the moment. I am using pygame 1.9.2pre and I am assuming it is just a bug with the pre release but I was having issues using any other versions of pygame with python 3.3.
Some users have reported difficulty with saving images as pngs:
I only get .tga files even when I specify .png. Very frustrating.
If you use .PNG (uppercase), it will result in an invalid file (at least on my win32). Use .png (lowercase) instead.
PNG does not seem to work, I am able to get a preview of it in Thunar, but everywhere else It says that it is not a valid PNG.
Saving in a different format may be helpful. For example, BMP is a simple format, so it's unlikely that Pygame's implementation will be buggy.
If you really want to save as PNG, you can reverse the distortion by swapping the red channel with the green one. This is fairly easy. For example, using PIL:
from PIL import Image
im = Image.open("screenshot.png")
width, height = im.size
pix = im.load()
for i in range(width):
for j in range(height):
r,g,b = pix[i,j]
pix[i,j] = (g,r,b)
im.save("output.png")
Or you can save as BMP and convert to PNG after the fact:
from PIL import Image
im = Image.open("screenshot.bmp")
im.save("screenshot.png")
for future reference, this trick worked for me:
from PIL import Image
imgdata = pygame.surfarray.array3d(screen).transpose([1,0,2])[:,:,::-1]
Image.fromarray(imgdata).save('output.png')
My question is why are the two histograms in following code the same.
Because the picture does change, first show shows original picture and second shows completely black picture.
Am I miss-using simpleCV or is this perhaps a bug?
Code:
from itertools import product
from SimpleCV import Image
from SimpleCV import Color
if __name__ == '__main__':
pass
def number_of_hues(picture):
image = Image(picture)
#convert the picture's space to HSV
image = image.toHSV()
image.show()
original_histogram = image.histogram()
(image_x_length, image_y_length) = image.size()
for i,j in product(range(image_x_length), range(image_y_length)):
image[i,j] = Color.BLACK
image.show()
new_histogram = image.histogram()
for o,n in zip(original_histogram, new_histogram):
if o != n:
print o,n
When was the last time you did a pull from the develop github repo? There was a bug in the set item call for the image class that kept images from getting set directly. It was fixed a couple weeks ago. Generally you should try to avoid directly looping over image objects and setting pixels directly as it can be really slow. If you think you found a bug please submit an issue to our github repo and we will try to address it as soon as we can.
I am trying to understand the basics for image processing an image of a corridor. I have have used PIL to convert find the edges in an image, then I have converted it to a 1 bit image. I know what I want to be able to extract - the longest horizontal and diagonal lines that can be found in the image. Any ideas?
from PIL import *
import Image, ImageFilter
im = im.open("c:\Python26\Lib\site-packages\PIL\corridor.jpg")
imageInfo=list(im.getdata())
im.putdata(imageInfo)
print pic.size
for i in imageInfo2[180:220]:
if i==0:
print "This is a BLACK pixel"
elif i==255:
print "This is a WHITE pixel"
else:
print "ERROR"
First don't call them 1 bit images - that normally refers to images (like icons) where each pixel is 1bit and so 8pixels can be packed into a single byte.
Images with only two levels are normally called 'binary' in image processing.
Now you only have to learn the science of image processing !
A good place to start is opencv a free image processing library that also works with python and interfaces reasonably well with PIL.
You shoudl also read their book - or one of the other good books on image processing