def get_porn(path: str) -> float:
# Get p**n score
result = 0
try:
image = Image.open(path)
sfw, nsfw = classify(image)
result = nsfw
except Exception as e:
logger.warning(f"Get p**n error: {e}", exc_info=True)
return result
def process(self):
"""
Analyze the given image
"""
try:
logger.debug('Start analyzing the image')
img = Image.open(self.file_path)
img.convert('RGB')
self.sfw_ratio, self.nsfw_ratio = classify(img)
logger.debug('Ended analyzing the image')
except IOError as e:
logger.error("Exception with PIL Image: {}".format(e.message))
raise
finally:
remove(self.file_path)
def is_nsfw(self):
"""
Analyze the given image and return a boolean depending on the results
of the neural network
"""
try:
logger.debug('Start analyzing the image')
img = Image.open(self.file_path)
img.convert('RGB')
_, nsfw = classify(img)
return nsfw > 0.7 # Consider NSFW if ratio is higher than 0.7
except IOError as e:
logger.error("Exception with PIL Image: {}".format(e.message))
return False
finally:
remove(self.file_path)
def check():
"""
"""
files = sys.argv[1:]
if not files:
print("""\
Usage:
nsfwcheck files...
""")
return
for path in files:
image = Image.open(path)
sfw, nsfw = classify(image)
print("It is {} that this image is suitable for work.".format(
probs(sfw)))
print("It is {} that this image is *not* suitable for work.".format(
probs(nsfw)))
import PIL.Image as Image
from nsfw import classify
from sys import argv
import os
try:
image = Image.open(argv[1])
sfw, nsfw = classify(image)
print(nsfw)
os.remove(argv[1])
except Exception as err:
print('Erro ao analisar imagem\nErr: ', err)
def analyze_file(filename):
image = Image.open(filename)
sfw, nsfw = classify(image)
return nsfw
import nsfw img = 'p**n.jpeg' out = nsfw.classify(img) print(out) img = ['p**n.jpeg', 'd2.png'] out = nsfw.classify_many(img) print(out)