gender accurate improved

AgeGenderDist/:wq

-import AgeGenderDist.face_model
-import argparse
-import cv2
-import sys
-import numpy as np
-import datetime
-from AgeGenderDist.mtcnn_detector import MtcnnDetector
-import os
-import mxnet as mx
-import math
-
-sys.path.append(os.path.join(os.path.dirname(__file__), '..', 'src', 'common'))
-
-parser = argparse.ArgumentParser(description='face model test')
-# general
-parser.add_argument('--image-size', default='112,112', help='')
-parser.add_argument('--image', default='Tom_Hanks_54745.png', help='')
-parser.add_argument('--model', default='model/model,0', help='path to load model.')
-parser.add_argument('--gpu', default=0, type=int, help='gpu id')
-parser.add_argument('--det', default=0, type=int, help='mtcnn option, 1 means using R+O, 0 means detect from begining')
-args = parser.parse_args()
-
-def get_age_gender_dist(img_src):
-   if args.gpu>=0:
-      ctx = mx.gpu(args.gpu)
-   else:
-      ctx = mx.cpu()
-   det_threshold = [0.6,0.7,0.8]
-   mtcnn_path = os.path.join(os.path.dirname(__file__), 'mtcnn-model')
-   if args.det==0:
-      detector = MtcnnDetector(model_folder=mtcnn_path, ctx=ctx, num_worker=1, accurate_landmark = True, threshold=det_threshold)
-   else:
-      detector = MtcnnDetector(model_folder=mtcnn_path, ctx=ctx, num_worker=1, accurate_landmark = True, threshold=[0.0,0.0,0.2])
-   ret = detector.detect_face(img_src, det_type = args.det)
-   if ret is None:
-      print('ret is none')
-   bbox, points = ret
-   points = points[0,:].reshape((2,5)).T
-   im=img_src.copy()
-   lf_eye=points[0]
-   rt_eye=points[1]
-   tmp=rt_eye-lf_eye
-   dist=math.hypot(tmp[0],tmp[1])
-  
-   model=face_model.FaceModel(args)
-   img=model.get_input(img_src)
-   gender,age=model.get_ga(img)
-    
-   return age,gender,dist
-
-def get_gender_age(img):
-    model=face_model.FaceModel(args)
-    img=model.get_input(img)
-    gender,age=model.get_ga(img)
-    return gender,age
-
-if __name__=='__main__':          
-   dirs= os.listdir(args.image)
-   for file in dirs:
-       print('file',file)
-       imgdir=os.path.join('testimg',file)
-       img_src = cv2.imread(imgdir)
-       gender,age=get_gender_age(img_src)
-       age,gender,dist=get_age_gender_dist(img_src)
-       print(age,gender,dist)
-       #print('gender:',gender)
-
-

AgeGenderDist/face_model.py

@@ -21,6 +21,7 @@ import AgeGenderDist.face_image
 import AgeGenderDist.face_preprocess
 
 
+
 def do_flip(data):
   for idx in range(data.shape[0]):
     data[idx,:,:] = np.fliplr(data[idx,:,:])

AgeGenderDist/mtcnn_detector.py

@@ -319,7 +319,7 @@ class MtcnnDetector(object):
         # check input
         height, width, _ = img.shape
         if det_type==0:
-            MIN_DET_SIZE = 12
+            MIN_DET_SIZE = 10 #12
 
             if img is None:
                 return None