I wrote a python script to detect broken images and count them, The problem in my script is it detects all the images and does not detect broken images. How to fix this. I refe
You are building a bad path with
img=Image.open('/Users/ajinkyabobade/Desktop/2'+filename)
Try the following instead (by adding / to the end of the directory path)
img=Image.open('/Users/ajinkyabobade/Desktop/2/'+filename)
or
img=Image.open(os.path.join('/Users/ajinkyabobade/Desktop/2', filename))
I have added another SO answer here that extends the PIL solution to better detect broken images. I also implemented this solution in my Python script here on GitHub.
I also verified that damaged files (jpg) frequently are not 'broken' images i.e, a damaged picture file sometimes remains a legit picture file, the original image is lost or altered but you are still able to load it.
I quote the other answer for completeness:
You can use Python Pillow(PIL) module, with most image formats, to check if a file is a valid and intact image file.
In the case you aim at detecting also broken images, @Nadia Alramli correctly suggests the im.verify()
method, but this does not detect all the possible image defects, e.g., im.verify
does not detect truncated images (that most viewer often load with a greyed area).
Pillow is able to detect these type of defects too, but you have to apply image manipulation or image decode/recode in or to trigger the check. Finally I suggest to use this code:
try:
im = Image.load(filename)
im.verify() #I perform also verify, don't know if he sees other types o defects
im.close() #reload is necessary in my case
im = Image.load(filename)
im.transpose(PIL.Image.FLIP_LEFT_RIGHT)
im.close()
except:
#manage excetions here
In case of image defects this code will raise an exception. Please consider that im.verify is about 100 times faster than performing the image manipulation (and I think that flip is one of the cheaper transformations). With this code you are going to verify a set of images at about 10 MBytes/sec (modern 2.5Ghz x86_64 CPU).
For the other formats psd,xcf,.. you can use Imagemagick wrapper Wand, the code is as follows:
im = wand.image.Image(filename=filename)
temp = im.flip;
im.close()
But, from my experiments Wand does not detect truncated images, I think it loads lacking parts as greyed area without prompting.
I red that Imagemagick has an external command identify that could make the job, but I have not found a way to invoke that function programmatically and I have not tested this route.
I suggest to always perform a preliminary check, check the filesize to not be zero (or very small), is a very cheap idea:
statfile = os.stat(filename)
filesize = statfile.st_size
if filesize == 0:
#manage here the 'faulty image' case
I am getting an error that tells me that Image.load
is not available. Image.open
appears to work.
I was also getting errors using:
except (IOError, SyntaxError) as e:
I just changed that to:
except:
and it worked fine.
try the below: It worked fine for me. It identifies the bad/corrupted image and remove them as well. Or if you want you can only print the bad/corrupted file name and remove the final script to delete the file.
for filename in listdir('/Users/ajinkyabobade/Desktop/2/'):
if filename.endswith('.JPG'):
try:
img = Image.open('/Users/ajinkyabobade/Desktop/2/'+filename) # open the image file
img.verify() # verify that it is, in fact an image
except (IOError, SyntaxError) as e:
print(filename)
os.remove('/Users/ajinkyabobade/Desktop/2/'+filename)