def isnude(self, file): #图像压缩处理 imagePath = IMAGE_DIR + file nudeImg = IMAGE_DIR + "nude_" + file # print(nudeImg) # disImg = IMAGE_DIR +file self.resizeImg(ori_img=imagePath, dst_img=nudeImg, dst_w=600, dst_h=600, save_q=100) # faces = self.face("dis"+file) faces = self.face("nude_" + file) if (len(faces) < 1): print("no face") return -1 else: self.cropImg("nude_" + file, faces) n = Nude(nudeImg) # n = Nude(newImg) # n.setFaces(faces) # n.resize(1000,1000) n.parse() # print n.result print(n.result, n.inspect(), '\n<br/>') print('stop waiting', time.strftime('%H:%M:%S'), '\n<br/>') return 1 if n.result else 0
def run(argv): for index in range(1, len(argv)): filename = str(argv[index]) n = Nude(filename) n.parse() print(filename, n.result, n.inspect()) return 0
def main(): if len(sys.argv) < 2: print("Usage: {0} <image>".format(sys.argv[0])) return 1 # else fname = sys.argv[1] print(is_nude(fname)) n = Nude(fname) n.parse() print("{0}: {1} {2}".format(fname, n.result, n.inspect())) return 0
def process(path): try: n = Nude(path) n.parse() logger.info('path:%s, result:%s, detail:%s', path, n.result, n.inspect()) if n.result: shutil.copy(path, porn_dir) else: shutil.copy(path, not_porn_dir) except Exception as err: logger.error('image error')
def main(): # 請插入媒體文件進行分析 __media_data = input("Please insert a media file for analysis: ") __isNude = Nude(__media_data) __isNude.parse() __isNudeInspection = __isNude.inspect() __isNudeResult = __isNude.result if "Nude!!" in __isNudeInspection: #print("result ", __isNude.result, __isNude.inspect()) # 結果: 該圖片包含色情數據 output = """ { "nude" = "true"; }; """ print(output) else: # 結果: 該圖片不包含色情數據 output = """ { "nude" = "false"; }; """ print(output)
def isnude(self,file): #图像压缩处理 imagePath = IMAGE_DIR + file nudeImg = IMAGE_DIR +"nude_"+file # disImg = IMAGE_DIR +file self.resizeImg(ori_img=imagePath,dst_img=nudeImg,dst_w=300,dst_h=300,save_q=100) # faces = self.face("dis"+file) faces = self.face("nude_"+file) if(len(faces)<1): print("no face") return -1 else: self.cropImg("nude_"+file, faces) n = Nude(nudeImg) # n = Nude(newImg) # n.setFaces(faces) # n.resize(1000,1000) n.parse() print(n.result, n.inspect(), '\n<br/>') # print n.result return 1 if n.result else 0
__FILENAME__ = testnude import nude from nude import Nude #print("damita :", nude.is_nude('./images/damita.jpg')) #print("damita2:", nude.is_nude('./images/damita2.jpg')) #print("test6 :", nude.is_nude('./images/test6.jpg')) #print("test2 :", nude.is_nude('./images/test2.jpg')) n = Nude('./images/damita.jpg') n.parse() print(n.result, n.inspect()) n = Nude('./images/damita2.jpg') n.parse() print(n.result, n.inspect()) n = Nude('./images/test6.jpg') n.parse() print(n.result, n.inspect()) n = Nude('./images/test2.jpg') n.parse() print(n.result, n.inspect()) ########NEW FILE######## __FILENAME__ = nude #!/usr/bin/env python # encoding: utf-8 from __future__ import (absolute_import, division, print_function,
from __future__ import print_function import time import os from nude import Nude ROOT = os.path.dirname(os.path.abspath(__file__)) start = time.time() n = Nude(os.path.join(ROOT, 'images/damita.jpg')) n.parse() print(time.time() - start) print(n.result, n.inspect()) # start = time.time() # n = Nude(os.path.join(ROOT, 'images/damita2.jpg')) # n.parse() # print(time.time() - start) # print(n.result, n.inspect()) # # start = time.time() # n = Nude(os.path.join(ROOT, 'images/test6.jpg')) # n.parse() # print(time.time() - start) # print(n.result, n.inspect()) # # start = time.time() # n = Nude(os.path.join(ROOT, 'images/test2.jpg')) # n.parse() # print(time.time() - start) # print(n.result, n.inspect())
import nude from nude import Nude print(nude.is_nude('images.jpg')) m = Nude('img.webp') m.parse() print("damita_1 :", m.result, m.inspect()) n = Nude('images2.jpg') n.parse() print("damita_2 :", n.result, n.inspect())
#coding:utf-8 ''' 基于肤色的裸体图像检测 ''' import nude from nude import Nude print(nude.is_nude('datas/images/test2.jpg')) n = Nude('datas/images/test2.jpg') n.parse() print("damita :", n.result, n.inspect())
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) # Detect faces in the image faces = facecascade.detectMultiScale( gray, scaleFactor=1.1, minNeighbors=5, minSize=(30, 30), flags=cv2.cv.CV_HAAR_SCALE_IMAGE ) # print("Found {0} faces!".format(len(faces))) # Draw a rectangle around the faces # for (x, y, w, h) in faces: # cv2.rectangle(image, (x, y), (x + w, y + h), (0, 255, 0), 2) return faces newImg = resizeImg(ori_img=file,dst_img=disImg,dst_w=300,dst_h=300,save_q=100) faces = facedetect(newImg) n = Nude(newImg) n.setFaces(faces) # n.resize(1000,1000) n.parse() print(n.result, n.inspect(), '\n<br/>') print('stop waiting', time.strftime('%H:%M:%S'), '\n<br/>')